PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?entity WHERE {
  ?entity rdfs:label "Oskar Lafontaine" @en .
}

The entity for Oskar Lafontaine could not be identified in the knowledge graph through the available search functions, preventing the construction of a valid SPARQL query to determine his election count as a Member of the Landtag of Saarland.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] How many times was Oskar Lafontaine elected Member of the Landtag of Saarland?

[Tool]
Top 10 entity alternatives:
1. attempted assassination of Oskar Lafontaine (wd:Q124305001)
2. Oscar I of Sweden, also known as Oscar I, Oskar, Oskar I (wd:Q52926): King of Sweden and Norway between 1844-1859, composer, monarch
3. Unsinkable Sam, also known as Oscar, Oskar (wd:Q893453): nickname of an alleged German ship's cat, ship's cat
4. Oskar Davičo, also known as Davičo, Oskar (wd:Q782418): Serbian writer (1909–1989), political commissar, journalist, writer, poet
5. Oskar, also known as Oskar (first name), Oskar (given name) (wd:Q18145769): male given name
6. Oskar (wd:Q12330497): 1962 film by Gabriel Axel
7. Lafontaine, also known as Lafontaine, KS, Lafontaine, Kansas (wd:Q16893891): human settlement in United States of America
8. Pierre Joseph Lafontaine, also known as M. Lafonteyne, M. La Fontaine, M. Lafontaine, M. De La Fontaine, Lafontene (wd:Q3385620): Belgian painter (1758-1835), art collector, painter
9. Lafontaine, also known as LaFontaine (wd:Q18043422): family name
10. LaFontaine (wd:Q3206243): provincial electoral district in Quebec, Canada

[Tool]
Top 10 entity alternatives:
1. attempted assassination of Oskar Lafontaine (wd:Q124305001)
2. Saarland, also known as DE-SL (wd:Q1201): state of the Federal Republic of Germany
3. Oscar I of Sweden, also known as Oscar I, Oskar, Oskar I (wd:Q52926): King of Sweden and Norway between 1844-1859, composer, monarch
4. Unsinkable Sam, also known as Oscar, Oskar (wd:Q893453): nickname of an alleged German ship's cat, ship's cat
5. Oskar Davičo, also known as Davičo, Oskar (wd:Q782418): Serbian writer (1909–1989), political commissar, journalist, writer, poet
6. Oskar, also known as Oskar (first name), Oskar (given name) (wd:Q18145769): male given name
7. Oskar (wd:Q12330497): 1962 film by Gabriel Axel
8. .saarland (wd:Q16659628): top-level domain
9. Lafontaine, also known as Lafontaine, KS, Lafontaine, Kansas (wd:Q16893891): human settlement in United States of America
10. Pierre Joseph Lafontaine, also known as M. Lafonteyne, M. La Fontaine, M. Lafontaine, M. De La Fontaine, Lafontene (wd:Q3385620): Belgian painter (1758-1835), art collector, painter

[Tool]
Got 33 rows and 3 columns, showing the first 10 rows below:
| subject                                                     | property                                                    | object                                     |
| ----------------------------------------------------------- | ----------------------------------------------------------- | ------------------------------------------ |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | instance of (wdt:P31)                                       | assassination attempt (wd:Q88178910)       |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | country (wdt:P17)                                           | Germany (wd:Q183)                          |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | located in the administrative territorial entity (wdt:P131) | Mülheim (wd:Q327896)                       |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | coordinate location (wdt:P625)                              | POINT(7.005083 50.959861) (geo:wktLiteral) |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | location (wdt:P276)                                         | Stadthalle Köln-Mülheim (wd:Q15994245)     |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | point in time (wdt:P585)                                    | 1990-04-25T00:00:00Z (xsd:dateTime)        |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | number of deaths (wdt:P1120)                                | 0 (xsd:decimal)                            |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | armament (wdt:P520)                                         | knife (wd:Q32489)                          |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | number of injured (wdt:P1339)                               | 1 (xsd:decimal)                            |
| attempted assassination of Oskar Lafontaine (wd:Q124305001) | perpetrator (wdt:P8031)                                     | Adelheid Streidel (wd:Q124305040)          |
| ...                                                         | ...                                                         | ...                                        |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?event WHERE {
  wd:Q430 wdt:P524 ?end .
  ?event wdt:P31 wd:Q55814 .
  ?event wdt:P170 wd:Q430
}

Dinosaurs went extinct at the end of the Cretaceous period due to the Cretaceous–Paleogene extinction event (also known as the K-Pg extinction event). This mass extinction, which occurred approximately 66 million years ago, is widely attributed to a combination of factors including a massive asteroid impact and volcanic activity, leading to dramatic climate changes that wiped out around 75% of all species on Earth, including non-avian dinosaurs.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What happened to the dinosaurs ?

[Tool]
Top 10 entity alternatives:
1. dinosaur, also known as dino, Dinosauria, dinosaurs (wd:Q430): clade of archosaurian reptiles (Archosauria)
2. Dinosaurs (wd:Q1211977): television program
3. Dinosaurs, also known as Dinosaurs: The Most Complete, Up... for Dinosaur Lovers of All Ages (wd:Q5186590): book by Thomas R. Holtz, Jr.
4. Dinosaurs (wd:Q18351859): 1987 novelette by Walter Jon Williams
5. Dinosaurs (wd:Q28419612): anthology of science fiction short works
6. Dinosaurs! (wd:Q28401115): 1990 anthology
7. Dinosaurs (wd:Q97359951): 2018 song by Australian musician Ruby Fields
8. Dinosaurs (wd:Q120970468): 2023 Indian Tamil-language action film by M. R. Madhavan
9. Dinosaurs (wd:Q58999596): scientific article published in Nature
10. Dinosaurs (wd:Q93927541): scholarly article authored by James Willis and published in British Journal of General Practice in 2007

[Tool]
Top 10 property alternatives:
1. temporal range end, also known as geologic time frame end, geologic time range end (wd:P524 as p): the end of a process such as a geological unit or extinction of a life form relative to the geologic time scale, end time
2. parent taxon, also known as higher taxon, taxon parent (wd:P171 as p/wdt): closest parent taxon of the taxon in question, subclass of
3. taxon name, also known as correct name (ICNafp), Latin name of a taxon (deprecated), scientific name of a taxon, taxonomic name, valid name (ICZN) (wd:P225 as p/wdt): correct scientific name of a taxon (according to the reference given)
4. taxon rank, also known as taxonomic rank, type of taxon, rank (wd:P105 as p/wdt): level in a taxonomic hierarchy, instance of
5. different from, also known as not to be confused with, to be distinguished from, similar to, see also, rejected match (wd:P1889 as p/wdt): item that is different from another item, with which it may be confused
6. mode of reproduction, also known as mode of biological reproduction (wd:P13318 as p/wdt): ways for living organisms to propagate or produce their offsprings
7. this taxon is source of, also known as this taxon is the source of, this taxon is a source of, natural product, taxon is source of, secretes (wd:P1672 as p/wdt): links a taxon to natural products it produces. Note that it does...s may vary. Some products may be yielded by more than one taxon.
8. Paleobiology Database taxon ID, also known as PaleoBioDB ID, PaleoDB ID, PBDB ID (wd:P10907 as p/wdt): identifier for a fossil taxon in the Paleobiology Database
9. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as p): significant or notable events associated with the subject
10. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Tool] Got no rows and 1 columns

[Tool] Got no rows and 1 columns

[Tool]
Top 10 entity alternatives:
1. Cretaceous-Paleogene mass extinction, also known as end-Cretaceous mass extinction, KTME, K-T mass extinction event, K-T mass extinction, K-T extinction event (wd:Q55811): extinction event ending the Mesozoic Era
2. Timeline of Cretaceous–Paleogene extinction event research (wd:Q28231431): research timeline
3. extinction event, also known as biotic crisis, ELE, extinction-level event, mass extinction (wd:Q55814): widespread and rapid decrease in the amount of life on earth
4. Extinction Event (wd:Q132797197): short story by Eliza Clark
5. Roveacrinids (Crinoidea, Echinod...aleogene (K-Pg) extinction event (wd:Q58082902): scholarly article
6. Permian-Triassic mass extinction, also known as Late Permian mass extinction events, Permian-Triassic extinction, Permian-Triassic extinction event, Permian-Triassic mass extinction event, P–T extinction (wd:Q141118): mass extinction event at the end of the Permian Period approximately 250 million years ago
7. Ordovician–Silurian extinction event, also known as Late Ordovician mass extinction, LOME, end-Ordovician mass extinction (wd:Q1065985): mass extinction event at the end of the Ordovician period and th...lurian period in the Paleozoic era, around 444 million years ago
8. Triassic-Jurassic mass extinction, also known as Tr-J mass extinction event, Tr-J mass extinction, Tr-J extinction event, Tr-J extinction, Triassic-Jurassic mass extinction event (wd:Q835034): mass extinction at the end of the Triassic
9. Quaternary extinction event, also known as Late Quaternary Extinctions, LQE, Pleistocene-Holocene extinction, QME, Quaternary Megafauna Extinction (wd:Q1759232): mass extinction event, around 10000 BCE, marking the end of the ...ized to be caused by human hunting and/or natural climate change
10. Eocene–Oligocene extinction event, also known as Grande Coupure (wd:Q1542955): mass extinction

[Tool] Got no rows and 1 columns

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?band ?inception WHERE {
  VALUES ?band {
    wd:Q15862 wd:Q2306
  }
  ?band wdt:P571 ?inception
}

Pink Floyd was created earlier than Queen.

The SPARQL query to determine the inception dates of both bands is as follows:

```sparql
SELECT ?band ?inception WHERE {
  VALUES ?band { wd:Q15862 wd:Q2306 }
  ?band wdt:P571 ?inception
}
```

**Answer:** Pink Floyd was founded on January 1, 1964, while Queen was founded on January 1, 1970. Therefore, Pink Floyd predates Queen by approximately six years.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] which band is created earlier, queen or pink floyd?

[Tool]
Top 10 entity alternatives:
1. Queen (wd:Q15862): British musical group; rock band
2. queen, also known as ♕, ♛, lady, Q (wd:Q139): chess piece, able to move any number of squares vertically, horizontally or diagonally
3. Queen (wd:Q193490): 1973 debut studio album by Queen
4. queen (wd:Q16511993): class of female monarch
5. The Queen, also known as Queen (wd:Q223367): 2006 film directed by Stephen Frears
6. Khatun, also known as queen consort, queen, khatan, khaness, kadin (wd:Q2272188): Title of nobility in Mongolia, Turkey, and related cultures for female khans, typically the wife of a khan, emperor, or king
7. Khatun, also known as queen consort, consort, hatun, queen, kadin (wd:Q2272188): Title of nobility in Mongolia, Turkey, and related cultures for female khans, typically the wife of a khan, emperor, or king
8. queen regnant, also known as female monarch, queen (wd:Q19643): female monarch who rules a country in her own right
9. queen (wd:Q505744): playing card
10. Queen (wd:Q15907466): 2014 film directed by Vikas Bahl

[Tool]
Top 10 entity alternatives:
1. Pink Floyd, also known as The Pink Floyd, The Pink Floyd Sound (wd:Q2306): English rock band
2. Pink Floyd, also known as Floyd Pinkerton (wd:Q3653015): character
3. Pink Floyd (wd:Q3388741): book by François Ducray
4. Rosa 'Pink Floyd', also known as Pink Floyd (wd:Q83670291): rose cultivar
5. Pink Floyd (wd:Q62068103): chapter, in The Rock and Roll Hall of Fame’s eleventh annual induction dinner programme
6. Why Pink Floyd...? (wd:Q3512037): marketing campaign
7. Pink Floyd pigs, also known as Algie (wd:Q2269820): Staple prop used by English progressive/psychedelic rock band Pink Floyd during live shows
8. WikiProject Pink Floyd (wd:Q13341445): Wikimedia subject-area collaboration
9. Brain Damage, also known as Tributo Pink Floyd (wd:Q2923592): French rock band
10. Pink Floyd Revisited (wd:Q2309415): live album by Mostly Autumn

[Tool]
Got 2 rows and 2 columns:
| band                  | inception                           |
| --------------------- | ----------------------------------- |
| Queen (wd:Q15862)     | 1970-01-01T00:00:00Z (xsd:dateTime) |
| Pink Floyd (wd:Q2306) | 1964-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
Pink Floyd was created earlier than Queen.

The SPARQL query to determine the inception dates of both bands is as follows:

```sparql
SELECT ?band ?inception WHERE {
  VALUES ?band { wd:Q15862 wd:Q2306 }
  ?band wdt:P571 ?inception
}
```

**Answer:** Pink Floyd was founded on January 1, 1964, while Queen was founded on January 1, 1970. Therefore, Pink Floyd predates Queen by approximately six years.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coordinate WHERE {
  wd:Q15174 wdt:P625 ?coordinate
}

The coordinate location of Shenzhen is 22.535° N, 114.054° E.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the coordinate location of Shenzhen ?

[Tool]
Top 10 entity alternatives:
1. Shenzhen, also known as Sham Chun (wd:Q15174): Sub-provincial division in China
2. Shenzhen (wd:Q2278115): graphic novel by the Canadian Québécois author Guy Delisle
3. Zhao Shenzhen, also known as Zunlu, Zhulou, Yuchao, Shengkanyanshi, Wenke (wd:Q15929422): Qing dynasty politician, politician
4. Shenzhen (wd:Q132803992): journal article from 'Cities' published in 2003
5. Shenzhen (wd:Q58926455): scientific article published in Nature
6. Shenzhen (wd:L453047-F1)
7. Shenzhen (wd:L453047)
8. Shenzhen Bao'an International Airport, also known as Shenzhen-Bao'an, SZX, ZGSZ (wd:Q842297): international airport in Shenzhen, China
9. Shenzhen Metro (wd:Q867680): rapid transit network in Shenzhen, China
10. Shenzhen Airlines, also known as Shenzhen Air (wd:Q974899): airline headquartered in Bao'an, Shenzhen, Guangdong, China and based in Shenzhen Bao'an International Airport

[Tool]
Got 1 row and 1 column:
| coordinate                                   |
| -------------------------------------------- |
| POINT(114.054000 22.535000) (geo:wktLiteral) |

[Assistant] The coordinate location of Shenzhen is retrieved from Wikidata as POINT(114.054000 22.535000), which corresponds to **22.535° N, 114.054° E** in standard latitude-longitude format.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( AVG( ?spouseCount ) AS ?averageSpouses ) {
  {
    SELECT ?headOfState ( COUNT( ?spouse ) AS ?spouseCount ) {
      ?country wdt:P35 ?headOfState .
      OPTIONAL {
        ?headOfState wdt:P26 ?spouse .
      }
    }
    GROUP BY ?headOfState
  }
}

The average number of spouses among heads of state is approximately 1.2.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] How many spouses do head of states have on average?

[Tool]
Top 10 entity alternatives:
1. head of state (wd:Q48352): official who holds the highest-ranked executive position in a sovereign state
2. Head of State (wd:Q1592282): 2003 American comedy film by Chris Rock
3. Head of State (wd:Q65225964): 2016 Armenian film
4. Başkan, also known as chairman, head of state, mayor, president (wd:Q60982271): Elected administrative position
5. Head of state (wd:Q116754472): scientific article published on 7 May 2002
6. Head of State (wd:Q114498865): episode of The Wayans Bros. (S2 E8)
7. Head of State (wd:Q74408294): episode of the 2003–2009 Teenage Mutant Ninja Turtles animated television series
8. head of state (wd:L383741-S1)
9. head of state, also known as leader, state headed by, queen, president, monarch (wd:P35): official with the highest formal authority in a country/state
10. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906): political office that is fulfilled by the head of state of this item

[Tool]
Got 1 row and 1 column:
| averageSpouses        |
| --------------------- |
| 1.19715 (xsd:decimal) |

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT ?animal ?sequence WHERE {
  wd:Q1976204 p:P527 ?statement .
  ?statement ps:P527 ?animal .
  ?statement pq:P1545 ?sequence .
}
ORDER BY ?sequence

The Chinese zodiac animal that follows the ox (sequence 2) is the tiger (sequence 3).

**Answer:** Tiger.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the Chinese zodiac animal that follows the ox?

[Tool]
Top 10 entity alternatives:
1. Chinese zodiac, also known as Celestial Branches, Earthly Branches (wd:Q1976204): lunar calendar classification, assigning a symbolic animal and i... year for a repeating cycle of twelve forming the Earthly Branch
2. Chinese Zodiac, also known as CZ12 (wd:Q391143): 2012 film directed by Jackie Chan
3. 12 Chinese Zodiac Signs (wd:Q108781655): 1995 animated series
4. Panel with Chinese Zodiac (wd:Q78712547): painting by anonymous painter
5. goat (Chinese zodiac animal) (wd:L1116276-S2)
6. horse (Chinese zodiac animal) (wd:L1116275-S2)
7. dragon (Chinese zodiac animal) (wd:L1116273-S2)
8. dog (Chinese zodiac animal) (wd:L293489-S2)
9. Dog (Chinese zodiac sign) (wd:L363339-S2)
10. rabbit (Chinese zodiac animal) (wd:L1116272-S2)

[Tool]
Got 12 rows and 3 columns, showing the first 10 rows below:
| subject                      | property               | object               |
| ---------------------------- | ---------------------- | -------------------- |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Rat (wd:Q721997)     |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Rooster (wd:Q822621) |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Monkey (wd:Q740674)  |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Rabbit (wd:Q844723)  |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Ox (wd:Q599644)      |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Dog (wd:Q755126)     |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Goat (wd:Q867696)    |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Horse (wd:Q869595)   |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Dragon (wd:Q731434)  |
| Chinese zodiac (wd:Q1976204) | has part(s) (wdt:P527) | Tiger (wd:Q740762)   |
| ...                          | ...                    | ...                  |

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 140 for token VAR1 with content '?sequence' (the input most likely does not follow the grammar)

[Tool]
Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| animal               | sequence |
| -------------------- | -------- |
| Rat (wd:Q721997)     | 1        |
| Rooster (wd:Q822621) | 10       |
| Dog (wd:Q755126)     | 11       |
| Pig (wd:Q877261)     | 12       |
| Ox (wd:Q599644)      | 2        |
| ...                  | ...      |
| Dragon (wd:Q731434)  | 5        |
| Snake (wd:Q756692)   | 6        |
| Horse (wd:Q869595)   | 7        |
| Goat (wd:Q867696)    | 8        |
| Monkey (wd:Q740674)  | 9        |

[Assistant]
The Chinese zodiac animal that follows the ox (sequence 2) is the tiger (sequence 3).

**Answer:** Tiger.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?month WHERE {
  wd:Q183 wdt:P30 ?continent .
  ?continent wdt:P31 wd:Q457608 .
}

The knowledge graph does not contain explicit information about the winter months in Germany. General knowledge indicates winter in the Northern Hemisphere spans December, January, and February, but no SPARQL query can be constructed from the provided data to confirm this.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] How many months does winter consist of in Germany?

[Tool]
Top 10 entity alternatives:
1. Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
2. Weimar Republic, also known as German Republic, Weimar Germany, Republic of Germany, Germany, German Reich (wd:Q41304): Germany in the years 1918/1919–1933
3. German Reich, also known as Deutsches Reich, German Empire, German Realm, Germany, Imperial Germany (wd:Q1206012): official name for the German nation state from 1871 to 1945, and name of Germany until 1949
4. Burg Drachenfels, also known as Germany (wd:Q1011486): castle
5. Germany (wd:Q5552078): European Parliament constituency
6. Geilenkirchen-Heinsberg, also known as Germany (wd:Q2268218)
7. Germany, also known as Germany, IN, Germany, Indiana (wd:Q18151573): unincorporated community in Clark County, Indiana
8. Germany (wd:Q19147844): poem by Vladimir Mayakovsky
9. Germany, also known as Ludwig, West (wd:Q3839160): Hetalia character
10. Germany, also known as Germany, Texas, Germany, TX (wd:Q15221573): unincorporated community in Houston County, Texas, United States

[Tool]
Top 10 property alternatives:
1. minimum temperature record, also known as lowest temperature (wd:P7422 as p/wdt): lowest temperature reached at this location, temperature
2. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as p/wdt): body of water on or next to which a place is located, location
3. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as p/wdt): area occupied by an object
4. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. coordinates of northernmost point, also known as coordinate of northernmost point, extreme point north, farthest north, most northerly, northerly (wd:P1332 as p/wdt): northernmost point of a location. For an administrative entity this includes offshore islands
6. maximum temperature record, also known as highest temperature (wd:P6591 as p/wdt): maximum temperature reached at this location, temperature
7. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as p/wdt): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
8. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
9. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
10. continent (wd:P30 as p/wdt): continent of which the subject is a part, located in/on physical feature

No other items found

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?river WHERE {
  wd:Q118841 wdt:P206 ?river
}

The river that flows through the Grand Canyon is the Colorado River.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Which river flows through the Grand Canyon?

[Tool]
Top 10 entity alternatives:
1. Grand Canyon, also known as Cañon of Colorado (wd:Q118841): steep-sided canyon carved by the Colorado River in Arizona, United States
2. Grand Canyon (wd:Q1542548): 1991 film directed by Lawrence Kasdan
3. Grand Canyon (wd:Q2062523): 1958 film by James Algar
4. Grand Canyon (wd:Q2901889): mall in Haifa, Israel
5. Snake River Canyon, also known as Grand Canyon (wd:Q7547072): canyon in Lincoln County, Wyoming, United States
6. Grand Canyon (wd:Q15701160): 1949 film by Paul Landres
7. Grand Canyon (wd:Q60752901): 2017 picture book by Jason Chin
8. Grand Canyon, also known as IMO 9614608 (wd:Q52514537): offshore supply ship built in 2012
9. Grand Canyon (wd:Q49805880): valley in Crook County, Wyoming, United States of America
10. Grand Canyon (wd:Q49805879)

[Tool]
Got 655 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                                                    | object                                                                                |
| ------------------------- | ----------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------- |
| Grand Canyon (wd:Q118841) | instance of (wdt:P31)                                       | canyon (wd:Q150784)                                                                                |
| Grand Canyon (wd:Q118841) | country (wdt:P17)                                           | United States (wd:Q30)                                                                                |
| Grand Canyon (wd:Q118841) | located in the administrative territorial entity (wdt:P131) | Arizona (wd:Q816)                                                                                |
| Grand Canyon (wd:Q118841) | coordinate location (wdt:P625)                              | POINT(-112.095278 36.097500) (geo:wktLiteral)                                                               |
| Grand Canyon (wd:Q118841) | Commons category (wdt:P373)                                 | Grand Canyon                                                                                |
| Grand Canyon (wd:Q118841) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Grand%20Canyon%20view%20from%20Pima%20Point%202010.jpg> |
| Grand Canyon (wd:Q118841) | heritage designation (wdt:P1435)                            | America's Most Endangered Historic Places (wd:Q4742563)                                                     |
| Grand Canyon (wd:Q118841) | described by source (wdt:P1343)                             | Encyclopædia Britannica 11th edition (wd:Q867541)                                                           |
| Grand Canyon (wd:Q118841) | on focus list of Wikimedia project (wdt:P5008)              | wd:Q6173448                                                                                |
| Grand Canyon (wd:Q118841) | native label (wdt:P1705)                                    | Grand Canyon (en)                                                                                |
| ...                       | ...                                                         | ...                                                                                |

[Tool]
Top 10 property alternatives:
1. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as p/wdt): body of water on or next to which a place is located, location
2. drainage basin, also known as watershed, water basin, river basin district, river basin, catchment area (wd:P4614 as p/wdt): area where precipitation collects and drains off into a common outlet, such as into a river, bay, or other body of water, located in/on physical feature
3. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
4. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
5. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
6. subreddit, also known as r/, reddit, Reddit community ID, Reddit forum, Reddit sub ID (wd:P3984 as p/wdt): name of the Reddit forum associated to this subject
7. vertical depth, also known as depth, oceandepth, lakedepth (wd:P4511 as p/wdt): vertical distance from a horizontal area to a point below. Compare with "horizontal depth" (P5524), length
8. length, also known as size, long, LOA, distance, dimension (wd:P2043 as p/wdt): measured dimension of an object
9. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Tool]
Got 1 row and 1 column:
| river                     |
| ------------------------- |
| Colorado River (wd:Q1265) |

[Assistant] The river that flows through the Grand Canyon is the Colorado River.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?spouse WHERE {
  wd:Q567 wdt:P26 ?spouse
}

Yes, Angela Merkel, the first female chancellor in Germany, was married to Joachim Sauer (wd:Q62085). The SPARQL query confirms this by retrieving her spouse from Wikidata.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Was the first female chancellor in Germany ever married?

[Tool]
Top 10 entity alternatives:
1. Angela Merkel, also known as Angela Dorothea Merkel, leader of the free world, Angela Kasner (wd:Q567): chancellor of Germany from 2005 to 2021, politician, physicist
2. Angela Merkel (wd:Q94746073)
3. Angela Merkel (wd:Q41495976): Polish Biography of Angela Merkel
4. Angela Merkel (wd:Q41495489): German biography of Angela Merkel
5. Angela Merkel (wd:Q125701744)
6. family of Angela Merkel (wd:Q27973987): family of Angela Merkel, the Chancellor of Germany
7. Lentapedia / Angela Merkel (wd:Q17316816): encyclopedia article
8. Angela Merkel and Vladimir Putin (wd:Q127786484)
9. public image of Angela Merkel (wd:Q106041150)
10. Angela Merkel - The Unexpected (wd:Q28464539): 2016 documentary film by Torsten Körner and Matthias Schmidt

[Tool]
Got 2 rows and 1 column:
| spouse                       |
| ---------------------------- |
| Ulrich Merkel (wd:Q13415350) |
| Joachim Sauer (wd:Q62085)    |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?subject WHERE {
  wd:Q11419997 wdt:P921 ?subject
}

The main subject of the manga 'Your Lie in April' is a middle school student (wd:Q16003532).

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] what is the main subject of the manga "your lie in april": primary school, middle school or high school student?

[Tool]
Top 10 entity alternatives:
1. Your Lie in April, also known as Kimiuso, Shigatsu wa Kimi no Uso (wd:Q11419997): Japanese manga series
2. Your Lie in April (wd:Q26810037): 2016 film by Takehiko Shinjō
3. Your Lie in April (wd:Q123944284): your Lie in April stage musical
4. Your Lie in April, also known as Kimiuso, Shigatsu wa Kimi no Uso (wd:Q91333870): Japanese anime television series
5. Your Lie in April: A Six Person Etude, also known as Shigatsu wa Kimi no Uso: 6-nin no Études (wd:Q91334211): Japanese light novel
6. Lies in Your Eyes (wd:Q6544290): extended play by Dive
7. Your Lies in Check (wd:Q4023078): album by Cripple Bastards
8. Lier in Your Eyes (wd:Q29424453): X-Ray song
9. The Lies in Your Eyes (wd:Q5409466): single
10. [It lies in your hand!] (wd:Q87357297): scientific article published on 01 February 2014

[Tool]
Got 263 rows and 3 columns, showing the first 10 rows below:
| subject                          | property                            | object                               |
| -------------------------------- | ----------------------------------- | ------------------------------------ |
| Your Lie in April (wd:Q11419997) | instance of (wdt:P31)               | manga series (wd:Q21198342)          |
| Your Lie in April (wd:Q11419997) | title (wdt:P1476)                   | 四月は君の嘘 (ja)                          |
| Your Lie in April (wd:Q11419997) | published in (wdt:P1433)            | Monthly Shōnen Magazine (wd:Q909935) |
| Your Lie in April (wd:Q11419997) | author (wdt:P50)                    | Naoshi Arakawa (wd:Q11502103)        |
| Your Lie in April (wd:Q11419997) | main subject (wdt:P921)             | middle school student (wd:Q16003532) |
| Your Lie in April (wd:Q11419997) | language of work or name (wdt:P407) | Japanese (wd:Q5287)                  |
| Your Lie in April (wd:Q11419997) | Commons category (wdt:P373)         | Your Lie in April                    |
| Your Lie in April (wd:Q11419997) | country of origin (wdt:P495)        | Japan (wd:Q17)                       |
| Your Lie in April (wd:Q11419997) | official website (wdt:P856)         | <http://www.kimiuso.jp/>             |
| Your Lie in April (wd:Q11419997) | genre (wdt:P136)                    | school anime and manga (wd:Q5366097) |
| ...                              | ...                                 | ...                                  |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?country ) AS ?count ) WHERE {
  wd:Q54078 wdt:P2541 ?area .
  ?area wdt:P31 wd:Q6256 .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

The available data in Wikidata does not contain the necessary information to determine the number of countries where IKEA has been established. Queries using properties like service outlet (P192) and operating area (P2541) returned zero results, indicating either missing data or incorrect property usage. Further data verification or alternative sources would be required to answer this question accurately.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] In how many countries has IKEA been established?

[Tool]
Top 10 entity alternatives:
1. IKEA, also known as Ikea, Ingvar Kamprad Elmtaryd Agunnaryd (wd:Q54078): international furniture store chain
2. Ikea (wd:Q18587732): genus of insects
3. Ikea effect (wd:Q1653973): cognitive bias in which consumers place a disproportionately high value on products they partially created
4. Swedish meatballs, also known as IKEA meatballs, Köttbullar (wd:Q1501015): Swedish dish made from ground meat
5. Blåhaj, also known as BLÅHAJ, funny meme shark, IKEA shark, Klappar Haj, Smolhaj (wd:Q107133815): stuffed toy shark sold at IKEA
6. IKEA Catalogue (wd:Q2941621): catalogue published annually by the Swedish home furnishing retailer IKEA
7. IKEA pencil (wd:Q18350690): small pencils provided for free in IKEA stores worldwide
8. IKEA Museum (wd:Q25063953): museum in Älmhult, Sweden
9. IKEA Heights (wd:Q15995166): Comedy web series
10. IKEA Sendai (wd:Q17988690)

[Tool]
Top 10 property alternatives:
1. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as p/wdt): location where a group or organization was formed, location of creation
2. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
3. typically sells, also known as product, sells, sold products, usually sells (wd:P7163 as p/wdt): type of goods particular type of shops typically sell
4. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as p/wdt): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
5. used by, also known as armiger, user, played by, of (wd:P1535 as p/wdt): item or concept that makes use of the subject (use sub-properties when appropriate)
6. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
8. industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as p/wdt): specific industry of company or organization, part of
9. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
10. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name

No other items found

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Tool]
Top 10 property alternatives:
1. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
2. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
3. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): area occupied by an object
4. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): specialization of a person or organization; see P106 for the occupation, interested in
5. applies to part, also known as when viewed as, valid for part, section, region, per (wd:P518 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): part, aspect, or form of the item to which the claim applies
6. local dialing code, also known as area code, dialling code, local calling code, local dialling code, STD code (wd:P473 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): identifier dedicated to subject city by the area communication network
7. place served by transport hub, also known as serves city, train station serves, served by transport hub, city served, area served by transport hub (wd:P931 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): territorial entity or entities served by this transport hub (airport, train station, etc.), significant place
8. product or material produced, also known as products, product or service provided, product, material, or service produced or provided, product, producer of (wd:P1056 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
9. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
10. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as prn/psn/pq/pqv/prv/wdtn/psv/pr/pqn/p/wdt/ps): person, profession, organization or entity that operates the equipment, facility, or service, used by

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?place WHERE {
  wd:Q1048 wdt:P20 ?place
}

Julius Caesar was murdered at the Theatre of Pompey (wd:Q944814).

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Where was Caesar murdered?

[Tool]
Top 10 entity alternatives:
1. Julius Caesar, also known as Divine Julius (wd:Q1048): Roman general and dictator (100 – 44 BC), ancient Roman military personnel, Ancient Roman politician, Ancient Roman historian, Ancient Roman priest, military leader, politician, historian, memoirist, writer, orator, ruler, poet
2. Julius Caesar, also known as The Tragedy of Julius Caesar, Tragedy of Julius Caesar (wd:Q215750): play by William Shakespeare
3. Julius Caesar (wd:Q734950): 1953 film by Joseph L. Mankiewicz
4. Julius Caesar (wd:Q631476): lunar impact crater
5. Julius Caesar, also known as Cajus Julius Caesar (wd:Q3649980): 1914 film directed by Enrico Guazzoni
6. Julius Caesar (wd:Q1612412): 1970 film by Stuart Burge
7. Julius Caesar (wd:Q315616): 2002 TV miniseries directed by Uli Edel
8. Julius Caesar (wd:Q3534298): English cricketer (1830-1878), cricketer
9. Julius Caesar, also known as Sir Julius Caesar, Sir Julius Cæser, Julius Caesar Aldemare, Cesare Adelmare (wd:Q1712531): English judge, politician, jurist, judge
10. Julius Caesar, also known as Giulio Cesare (wd:Q3769550): 1909 film by Giovanni Pastrone

[Tool]
Got 1 row and 1 column:
| place                          |
| ------------------------------ |
| Theatre of Pompey (wd:Q944814) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?startDate WHERE {
  wd:Q23001951 wdt:P580 ?startDate .
}

Riverdale was first aired in the year 2017.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What year was Riverdale first aired?

[Tool]
Top 10 entity alternatives:
1. Riverdale (wd:Q23001951): American teen drama television series (2017–2023)
2. Riverdale, also known as Riverdale, Georgia, Riverdale, GA (wd:Q3260888): city in Clayton County, Georgia, United States siiii
3. Riverdale, also known as Riverdale, GA, Riverdale, Georgia (wd:Q3260888): city in Clayton County, Georgia, United States siiii
4. Riverdale, also known as Riverdale, IA, Riverdale, Iowa (wd:Q1925935): city in Scott County, Iowa, United States
5. Riverdale, also known as Riverdale, UT, Riverdale, Utah (wd:Q129941): city in Weber County, Utah, United States
6. Riverdale, also known as Riverdale, New Jersey, Riverdale, NJ (wd:Q1083010): borough in Morris County, New Jersey, United States
7. Riverdale, also known as Riverdale, IL (wd:Q2668893): village in Cook County, Illinois, United States
8. Riverdale Park, also known as Riverdale, Riverdale, Maryland, Riverdale Park, Maryland, Riverdale Park, MD (wd:Q754948): town in Prince George's County, Maryland, United States
9. Riverdale, also known as Riverdale, NE, Riverdale, Nebraska (wd:Q2516346): village in Nebraska
10. Riverdale, also known as Riverdale, ND, Riverdale, North Dakota (wd:Q2373536): human settlement in McLean County, North Dakota, United States of America

[Tool]
Got 450 rows and 3 columns, showing the first 10 rows below:
| subject                  | property                     | object                                |
| ------------------------ | ---------------------------- | ------------------------------------- |
| Riverdale (wd:Q23001951) | instance of (wdt:P31)        | television series (wd:Q5398426)       |
| Riverdale (wd:Q23001951) | title (wdt:P1476)            | Riverdale (en)                        |
| Riverdale (wd:Q23001951) | Commons category (wdt:P373)  | Riverdale (2017 TV series)            |
| Riverdale (wd:Q23001951) | has part(s) (wdt:P527)       | Riverdale, season 1 (wd:Q28533018)    |
| Riverdale (wd:Q23001951) | country of origin (wdt:P495) | United States (wd:Q30)                |
| Riverdale (wd:Q23001951) | official website (wdt:P856)  | <http://www.cwtv.com/shows/riverdale> |
| Riverdale (wd:Q23001951) | genre (wdt:P136)             | drama television series (wd:Q1366112) |
| Riverdale (wd:Q23001951) | cast member (wdt:P161)       | Luke Perry (wd:Q318165)               |
| Riverdale (wd:Q23001951) | creator (wdt:P170)           | Roberto Aguirre-Sacasa (wd:Q7351575)  |
| Riverdale (wd:Q23001951) | start time (wdt:P580)        | 2017-01-26T00:00:00Z (xsd:dateTime)   |
| ...                      | ...                          | ...                                   |

[Assistant]
The SPARQL query to find the first air date of Riverdale is as follows:

```sparql
SELECT ?startDate WHERE {
  wd:Q23001951 wdt:P580 ?startDate.
}
```

The result from the query shows the start date as `2017-01-26T00:00:00Z`, so the year Riverdale was first aired is **2017**.

[Tool] Stopped generation process