PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?language ?languageLabel WHERE {
  wd:Q730 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| language         | languageLabel |
| ---------------- | ------------- |
| Dutch (wd:Q7411) | Dutch (en)    |

The official language of Suriname is Dutch.

[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 http://amur:7001

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 official language of Suriname?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
Which country has the most official languages?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P37 ?language .
}
GROUP BY ?uri
ORDER BY DESC ( COUNT( ?language ) )
LIMIT 1

Using entities:
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

[Assistant]
From the example, we see that the property for official language is wdt:P37 and the entity for country is wd:Q6256. Suriname is a country, so we need to find the official language (wdt:P37) of Suriname.

Next, I will search for the entity Suriname in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Suriname, also known as Dutch Guiana, Republic of Surinam, Republic of Suriname, sr, SUR (wd:Q730): country in South America
2. Surinam, also known as Dutch Surinam, Suriname (Dutch colony), Suriname, Surinam (Dutch colony), Kolonie Suriname (wd:Q7646305): Dutch plantation colony in the Guianas
3. Suriname (wd:Q19901436): constituent country of the Kingdom of the Netherlands, 1954–1975
4. Suriname, also known as Suriname (district) (wd:Q2688457): former district in Suriname
5. Hussard, also known as HMS Sasnarang, Suriname, HMS Surinam, Hussar (wd:Q5502076): 1799 corvette
6. Javoco FC, also known as {{Start date and age|df=yes|1976...   = [[SVB Lidbondentoernooi | L, Suriname, {{short description|Association ...{Use dmy dates|date=March 2016}}, {{Infobox football club| clubnam...kerie| motto    =| founded     = (wd:Q131460311): Blue the White
7. Suriname (wd:Q2186454)
8. Suriname (wd:Q93183143): 2020 film by Danny Leysner
9. Suriname, also known as IMO 5345625 (wd:Q107067657): cargo ship built in 1960
10. Suriname, also known as Koloniaal Nieuwsblad (wd:Q55504192): Surinamese newspaper

[Assistant] The entity for the country Suriname is wd:Q730. Now I will write a SPARQL query to find the official language (wdt:P37) of Suriname (wd:Q730).

[Tool]
Got 1 row and 2 columns:
| language         | languageLabel |
| ---------------- | ------------- |
| Dutch (wd:Q7411) | Dutch (en)    |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?official_website WHERE {
  wd:Q37079 wdt:P856 ?official_website .
}

Got 1 row and 1 column:
| official_website           |
| -------------------------- |
| <http://www.tomcruise.com> |

The official website of Tom Cruise is http://www.tomcruise.com.

[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 http://amur:7001

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 official website of Tom Cruise?

[Assistant] Let's start by looking at some similar examples.

[Tool] No examples found

[Assistant] There are no similar examples available, so I will proceed by searching for the entity "Tom Cruise" in Wikidata to get his identifier. Then I will look for the property that corresponds to the official website.

[Tool]
Top 10 entity alternatives:
1. Tom Cruise, also known as Thomas Cruise Mapother IV (wd:Q37079): American actor and producer (born 1962), stunt performer, aircraft pilot, film producer, film director, screenwriter, film actor, producer, director, writer, actor
2. Being Tom Cruise (wd:Q4881315): 2007 television film directed by Elliot Hegarty
3. Tom Cruise: Unauthorized (wd:Q7815472): book by Wensley Clarkson
4. Tom Cruise Purple (wd:Q7815473): cannabis strain
5. BGM-109 Tomahawk, also known as Tomahawk, Tomahawk cruise missile (wd:Q150115): long-range, subsonic cruise missile by Raytheon
6. Tom Cruise: An Unauthorized Biography (wd:Q7815470): book by Andrew Morton
7. Tom Cruise? Or just normal? (wd:Q72264999): scientific article published on 01 June 1995
8. Tom Cruise or Don Knotts? (wd:Q70232908): scientific article published on 01 June 1991
9. Tom Cruise: entertaining or dangerous? (wd:Q51927027): scientific article published in June 2005
10. Tom Cruise orders €14,500 takeaway meal (wd:Q17661822): Wikinews article

[Assistant] The entity for Tom Cruise is wd:Q37079. Now I will search for properties related to "official website" for this entity.

[Tool]
Top 10 property alternatives:
1. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
2. YouTube channel ID, also known as YouTube account, YouTube channel, YouTube channel identifier, official YouTube channel, youtube.com/channel/ (wd:P2397 as wdt/p): ID of the YouTube channel of a person or organisation (not to be...f the channel) The ID can also be used for music.youtube.com IDs, website username or ID
3. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
4. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
5. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
6. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
8. documentation files at, also known as clipping files at, documentary records at, documentary records held at, documentary records held by, documentation at (wd:P10527 as wdt/p): institution that holds documentation files about the subject
9. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as wdt/p/wdtn): identifier from an international authority file of names, subjects, and organizations
10. NDL Authority ID, also known as NDLSH (NDL Subject Headings), NDLNA (NDL Name Authority), NDLNAId, NDL identifier, NDL ID (wd:P349 as wdt/p/wdtn): identifier for authority control per the National Diet Library of Japan

No other items found

[Assistant] The property for official website is wd:P856. Now I will write a SPARQL query to get the official website of Tom Cruise using the entity wd:Q37079 and property wd:P856.

[Tool]
Got 1 row and 1 column:
| official_website           |
| -------------------------- |
| <http://www.tomcruise.com> |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?mouth ?mouthLabel WHERE {
  wd:Q106588 wdt:P403 ?mouth .
  OPTIONAL {
    ?mouth rdfs:label ?mouthLabel FILTER ( LANG( ?mouthLabel ) = "en" )
  }
}

The Isar river flows into the Danube river, which is a river and not a lake. Therefore, the Isar does not flow into a lake.

[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 http://amur:7001

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] Does the Isar flow into a lake?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
Which rivers flow into the North Sea?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q4022 .
  ?uri wdt:P403 wd:Q1693 .
}

Using entities:
North Sea, also known as German Ocean, the North Sea, the German Sea, the British Ocean, German Sea (wd:Q1693): marginal sea of the Atlantic Ocean
river, also known as rivers (wd:Q4022): larger natural watercourse

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
mouth of the watercourse, also known as flows into, watercourse outflow, watercourse ends in, watercourse drain, tributary of (wd:P403 as wdt): the body of water to which the watercourse drains

[Assistant]
From the example, we see that the property "mouth of the watercourse" (wdt:P403) is used to indicate where a river flows into. We can use this property to check if the Isar river flows into a lake.

Next, I will search for the entity "Isar" to get its Wikidata identifier.

[Tool]
Top 10 entity alternatives:
1. Isar, also known as Iser (wd:Q106588): river in Tyrol, Austria and Bavaria, Germany
2. Isar (wd:Q2001258): municipality in Spain
3. Isar (wd:Q15622057): archaeological site in Macedonia
4. Istanbul Research and Education Foundation, also known as ISAR (wd:Q20477093): educational support foundation in Turkey
5. Isar (wd:Q24010480): capital of Isar Municipality, Spain
6. Isār (wd:Q21754941): mountain in Afghanistan
7. Isar, also known as IMO 5248346 (wd:Q97990686): ship launched in 1929
8. Isar (wd:Q97990690): 1929 reefer ship
9. Isar (wd:Q56509793): musician
10. Isar (wd:Q31766831): mountain in Pakistan

[Assistant] The Isar river is identified as wd:Q106588. Now I will query the mouth of the watercourse (wdt:P403) for the Isar river to see if it flows into a lake.

[Tool]
Got 1 row and 2 columns:
| mouth             | mouthLabel  |
| ----------------- | ----------- |
| Danube (wd:Q1653) | Danube (en) |

[Assistant] The Isar river flows into the Danube river, not a lake. To confirm, I will check if the Danube is classified as a lake or not.

[Tool]
Got 2 rows and 2 columns:
| type                              | typeLabel                |
| --------------------------------- | ------------------------ |
| river (wd:Q4022)                  | river (en)               |
| transboundary river (wd:Q4366834) | transboundary river (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?capital ?capitalLabel ?largestCity ?largestCityLabel WHERE {
  wd:Q79 wdt:P36 ?capital .
  OPTIONAL {
    ?capital rdfs:label ?capitalLabel FILTER ( LANG( ?capitalLabel ) = "en" )
  }
  ?largestCity wdt:P31 / wdt:P279 * wd:Q515 ; wdt:P17 wd:Q79 ; wdt:P1082 ?population .
  OPTIONAL {
    ?largestCity rdfs:label ?largestCityLabel FILTER ( LANG( ?largestCityLabel ) = "en" )
  }
}
ORDER BY DESC ( ?population )
LIMIT 1

Got 1 row and 4 columns:
| capital        | capitalLabel | largestCity    | largestCityLabel |
| -------------- | ------------ | -------------- | ---------------- |
| Cairo (wd:Q85) | Cairo (en)   | Cairo (wd:Q85) | Cairo (en)       |

Yes, Egypt's largest city is also its capital, Cairo.

[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 http://amur:7001

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] Is Egypts largest city also its capital?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
What is the capital of Cameroon?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1009 wdt:P36 ?uri
}

Using entities:
Cameroon, also known as CAM, CM, CMR, Republic of Cameroon (wd:Q1009): sovereign state in West-Central Africa

Using properties:
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

[Assistant]
The example shows how to find the capital of a country using the property "capital" (wdt:P36). To answer the question if Egypt's largest city is also its capital, we need to find both the largest city and the capital of Egypt and then compare them.

Step 1: Identify Egypt entity in Wikidata.
Step 2: Find the capital of Egypt using property wdt:P36.
Step 3: Find the largest city of Egypt. We need to find a property that indicates the largest city or population of cities in Egypt.
Step 4: Compare the two cities.

I will start by searching for the entity "Egypt" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Egypt, also known as Republic of Egypt, Rep. Egypt, EGY, eg, Arab Republic of Egypt (wd:Q79): country in Northeast Africa and Southwest Asia
2. Khedivate of Egypt, also known as Egypt, Egyptian Khedivate (wd:Q127861): 1867-1914 monarchy in Northeastern Africa
3. Egypt Eyalet, also known as QASR of Egypt, Pashalik of Egypt, Egypt, Mısır Eyalet, Beylerbeyilik of Egypt (wd:Q491507): Egyptian State (1517–1867)
4. Egypt, also known as Egypt, AK, Egypt, AR (wd:Q2083973): town in Arkansas
5. Egypt, also known as Egypt, Etowah County, Alabama, Egypt, AL (wd:Q5348296): census-designated place in Etowah County, Alabama
6. Egypt, also known as Egypt, Pennsylvania (wd:Q5348306): human settlement in Pennsylvania, United States
7. Egypt 1156 B.C., also known as Egypt, Egypt 1156 B.C.: Tomb of the Pharaoh (wd:Q3586212): 1999 video game
8. Egypt, also known as Egypt, WV (wd:Q5348310): unincorporated community in Jefferson County, West Virginia
9. Egypt (wd:Q5348317): 2004 album by Youssou N'Dour
10. Egypt, also known as Egypt, IN, Egypt, Indiana (wd:Q5348297): unincorporated community in Jasper County, Minnesota

[Assistant]
The entity for Egypt as a country is wd:Q79.

Next, I will find the capital of Egypt using the property "capital" (wdt:P36).

[Tool]
Got 1 row and 2 columns:
| capital        | capitalLabel |
| -------------- | ------------ |
| Cairo (wd:Q85) | Cairo (en)   |

[Assistant]
The capital of Egypt is Cairo (wd:Q85).

Now, I need to find the largest city in Egypt. I will search for properties related to "largest city" or "population" for the entity Egypt (wd:Q79) to find the appropriate property to get the largest city.

[Tool]
Top 10 property alternatives:
1. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as wdt/p): (list of) direct subdivisions of an administrative territorial entity, has part(s)
2. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt/p): seat of government of a country, province, state or other type of administrative territorial entity
3. urban population (wd:P6343 as wdt/p): number of people living within the territorial entity who live in its urban parts, population
4. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt/p): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
5. population, also known as inhabitants, human population (wd:P1082 as wdt/p): number of people inhabiting the place; number of people of subject
6. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as wdt/p): market value of all officially recognized final goods and services produced within a country in a given period of time
7. highest point, also known as tallest point, zenith, summit, pinnacle, highest peak (wd:P610 as wdt/p): point with highest elevation in a region or path, has part(s)
8. continent (wd:P30 as wdt/p): continent of which the subject is a part, located in/on physical feature
9. culture, also known as archaeological culture, civilisation, civilization (wd:P2596 as wdt/p): human culture or people (or several cultures) associated with this item, part of
10. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

No other items found

[Assistant]
There is no direct property for "largest city" of Egypt. However, we can find cities in Egypt and their populations, then determine the largest city by population.

I will find cities located in Egypt (wd:Q79) and their population (wdt:P1082), then order by population descending to get the largest city.

[Tool]
Got 1 row and 3 columns:
| city           | cityLabel  | population            |
| -------------- | ---------- | --------------------- |
| Cairo (wd:Q85) | Cairo (en) | 9606916 (xsd:decimal) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?creator ?creatorLabel WHERE {
  wd:Q111135 wdt:P170 ?creator .
  OPTIONAL {
    ?creator rdfs:label ?creatorLabel FILTER ( LANG( ?creatorLabel ) = "en" )
  }
}

The creator of Goofy is Art Babbitt.

[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 http://amur:7001

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] Who created Goofy?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
Who created Family Guy?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q5930 wdt:P170 ?uri
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)

Example 2:
Question:
What was the original occupation of the inventor of Lego?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q170484 wdt:P61 / wdt:P106 ?uri
}

Using entities:
LEGO (wd:Q170484): construction toy

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as wdt): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory

Example 3:
Question:
Who wrote Harry Potter?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q8337 wdt:P50 ?uri
}

Using entities:
Harry Potter, also known as Harry Potter series (wd:Q8337): 1997–2007 fantasy book series by J. K. Rowling

Using properties:
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

[Assistant]
From the examples, the property "creator" (wdt:P170) is used to find the creator of a work or character. Goofy is a Disney character, so we can use the entity for Goofy and query for its creator using the property wdt:P170.

Next, I will search for the entity "Goofy" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Goofy, also known as Dippy Dawg, George Geef, Goofy Goof (wd:Q111135): Disney cartoon character
2. Goofy (wd:Q5583788): dance music and hip hop trio
3. Goofy (wd:Q3028317): series of animated short films
4. GFY, also known as Goofy, golgi associated olfactory signaling regulator (wd:Q18068088): protein-coding gene in the species Homo sapiens
5. goofy stance, also known as goofy, goofy foot, goofy style, right-footed, right-footedness (wd:Q99533732): leading with one's right foot, in boardsports
6. Goofy (wd:Q131593548)
7. Gfy, also known as Gm581, Goofy, golgi-associated olfactory signaling regulator, Gm2515 (wd:Q18315119): protein-coding gene in the species Mus musculus
8. Richard "Goofy" Campbell, also known as Chad Simpson, Goofy (wd:Q99697433): musician
9. goofy (wd:L23413)
10. goofy (wd:L23413-F1)

[Assistant] The entity for the Disney cartoon character Goofy is wd:Q111135. Now I will query for the creator of Goofy using the property wdt:P170 (creator).

[Tool]
Got 1 row and 2 columns:
| creator                   | creatorLabel     |
| ------------------------- | ---------------- |
| Art Babbitt (wd:Q2420722) | Art Babbitt (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?tvShow ?tvShowLabel WHERE {
  ?tvShow wdt:P31 wd:Q5398426 .
  ?tvShow wdt:P170 wd:Q25014 .
  OPTIONAL {
    ?tvShow rdfs:label ?tvShowLabel FILTER ( LANG( ?tvShowLabel ) = "en" )
  }
}

The television shows created by John Cleese are "Fawlty Towers" and "At Last the 1948 Show."

[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 http://amur:7001

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 television shows were created by John Cleese?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
Who created Family Guy?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q5930 wdt:P170 ?uri
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)

[Assistant]
The property "creator" (wdt:P170) is used to indicate the creator of a creative work. We can use this property to find television shows created by John Cleese.

Next, I will search for the entity John Cleese in Wikidata to get his identifier.

[Tool]
Top 10 entity alternatives:
1. John Cleese, also known as John Marwood Cleese (wd:Q25014): English comedian and actor (born 1939), television actor, autobiographer, film producer, film director, screenwriter, stage actor, voice actor, film actor, comedian, writer, actor
2. Landfill named after comedian John Cleese (wd:Q17665651): Wikinews article
3. John the Apostle, also known as John, St. John, St John the Apostle, St. John the Apostle, Saint John the Apostle (wd:Q44015): apostle of Jesus; son of Zebedee and Salome, brother of James; t...th John the Evangelist, John of Patmos, and the Beloved Disciple, theologian, author, fisher, mystic
4. John, King of England, also known as John I Lackland, King John of England, King John, John of England, John Lackland (wd:Q129308): King of England from 1199 to 1216, monarch
5. John I, also known as Ioannes I, Pope John I, Pope John, John (wd:Q160916): Catholic priest, writer, pope
6. Guy Fawkes, also known as Guido Fawkes, John Johnson (wd:Q13898): English member of the Gunpowder Plot of 1605, military personnel, soldier
7. John XV, also known as Pope John XV, John, Ioannes XV (wd:Q228649): Catholic priest, writer, pope
8. John the Evangelist, also known as St. John the Evangelist, St John the Evangelist, Saint John the Evangelist, John (wd:Q328804): author of the Gospel of John; traditionally identified with John...s, John of Patmos (author of Revelation), and John the Presbyter, evangelist
9. John Wick, also known as John, John Wick: Chapter 1 (wd:Q15732802): 2014 film directed by Chad Stahelski and David Leitch
10. Jack Johnson, also known as Black Jack Johnson, Galveston Giant, John Arthur Johnson, John Johnson (wd:Q316689): American boxer (1878–1946), boxer

[Assistant] The entity for John Cleese is wd:Q25014. Now, I will search for television shows created by John Cleese using the property "creator" (wdt:P170). I will look for items that are instances of television shows.

[Tool]
Top 10 entity alternatives:
1. television program, also known as TV show, television broadcast, T.V. show, T. V. show, TV programme (wd:Q15416): segment of audiovisual content intended for broadcast on television
2. television series, also known as TV show, TV-series, television show, TV series (wd:Q5398426): connected set of television program episodes under the same title
3. reality television, also known as reality TV program, TV reality show, TV reality program, television reality show, television reality program (wd:Q182415): genre of television programming that documents unscripted situations and actual occurrences
4. television presenter, also known as television anchor, TV show host, TV presenter, TV host, TV anchor (wd:Q947873): person who introduces or hosts television programs
5. variety show, also known as television variety program, television variety show, variety, variety entertainment, variety program (wd:Q336181): television genre characterized by a series of specialty acts such as music, dance, comedy, magic, acrobatics and ventriloquism
6. showrunner, also known as television show creator (wd:Q1440873): person who is responsible for the day-to-day operation of a television show
7. breakfast television, also known as breakfast show, morning show, morning talk show, morning television show (wd:Q1472288): type of morning television show
8. reality show, also known as reality television program, TV reality show, TV reality program, television reality show, television reality program (wd:Q3421644): television genre
9. television series season, also known as TV show season, TV series season, TV season, season of a TV show, television show season (wd:Q3464665): set of episodes produced for a television series
10. drama television program, also known as TV drama, television drama show, television drama program, television drama, teledrama (wd:Q110593089): television genre

[Assistant] The entity for television show or television series is wd:Q5398426. I will now write a SPARQL query to find television shows (wd:Q5398426) where John Cleese (wd:Q25014) is the creator (wdt:P170).

[Tool]
Got 2 rows and 2 columns:
| tvShow                             | tvShowLabel                |
| ---------------------------------- | -------------------------- |
| Fawlty Towers (wd:Q212731)         | Fawlty Towers (en)         |
| At Last the 1948 Show (wd:Q752945) | At Last the 1948 Show (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?dissolutionDate WHERE {
  wd:Q9903 wdt:P576 ?dissolutionDate .
}

The Ming dynasty dissolved in the year 1644.

[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 http://amur:7001

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] When did the Ming dynasty dissolve?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
How many emperors did China have?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) as ?count ) WHERE {
  ?uri wdt:P39 wd:Q268218
}

Using entities:
Emperor of China, also known as Huang-ti, Huang Ti, Son of Heaven, thearch, Ti (wd:Q268218): sovereign of Imperial China

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt): subject currently or formerly holds the object position or public office

Example 2:
Question:
When did the Boston Tea Party take place?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q19024 wdt:P585 ?uri
}

Using entities:
Boston Tea Party, also known as Boston Tea-party, Destruction of the Tea (wd:Q19024): 1773 American protest against British taxation

Using properties:
point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)

[Assistant]
The Ming dynasty is an entity we need to identify. The question asks for the date when the Ming dynasty dissolved, which is a point in time or date related to the end of the dynasty. The property we are looking for is likely related to the end date or dissolution date of an entity.

I will first search for the entity "Ming dynasty" in Wikidata to get its identifier. Then I will look for properties related to the end or dissolution date of the dynasty.

[Tool]
Top 10 entity alternatives:
1. Ming dynasty, also known as Ming period, Ming imperium, Ming China, Ming-era, Ming Empire (wd:Q9903): imperial dynasty of China from 1368 to 1644
2. Empress of the Ming, also known as Ming Dynasty (wd:Q61650149): Chinese TV series or program
3. Ming Dynasty (wd:Q6864636): 2007 Chinese television series
4. Ming Dynasty (wd:Q6864635): Australian Thoroughbred racehorse
5. Ming dynasty (wd:Q103958345): encyclopedia article
6. Ming dynasty (wd:L663750-S5)
7. Ming tombs, also known as Ming dynasty tombs (wd:Q41135): collection of mausoleums built by the emperors of the Ming dynasty of China
8. Southern Ming dynasty, also known as Southern Ming (wd:Q1198163): dynasty
9. history of the Ming dynasty, also known as history of Ming dynasty, Ming dynasty history, the Ming dynasty history (wd:Q16843870): aspect of history
10. Ming dynasty painting (wd:Q6864640): overview of Ming dynasty painting

[Assistant] The Ming dynasty entity in Wikidata is wd:Q9903. Now I will look for properties related to the end date or dissolution date of this dynasty. I will search for properties related to "end", "dissolve", or "end date" for this entity.

[Tool]
Top 10 property alternatives:
1. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as wdt/p): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
3. follows, also known as prev, successor to, succeeds to, succeeds, split from (wd:P155 as wdt/p): immediately prior item in a series of which the subject is a par... preceding item, e.g. political offices, use "replaces" (P1365)]
4. replaced by, also known as heir, superseded by, successor, succeeded by, next job holder (wd:P1366 as wdt/p): other person or item which continues the item by replacing it in... nor identical, but adds to the series (e.g. books in a series)., followed by
5. replaces, also known as supersedes, succeeds, replaced, previous job holder, preceded by (wd:P1365 as wdt/p): person, state or item replaced. Use "structure replaces" (P1398)...item was not replaced or predecessor and successor are identical, follows
6. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as wdt/p): official name of the subject in its official language(s), name
7. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
8. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt/p): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
9. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
10. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as wdt/p): (list of) direct subdivisions of an administrative territorial entity, has part(s)

No other items found

[Assistant] The property "dissolved, abolished or demolished date" (wdt:P576) seems to be the most relevant for the dissolution date of the Ming dynasty. I will now construct a SPARQL query to get the dissolution date of the Ming dynasty (wd:Q9903) using this property.

[Tool]
Got 1 row and 1 column:
| dissolutionDate                     |
| ----------------------------------- |
| 1644-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?highestPoint ?highestPointLabel WHERE {
  wd:Q35600 wdt:P610 ?highestPoint .
  OPTIONAL {
    ?highestPoint rdfs:label ?highestPointLabel FILTER ( LANG( ?highestPointLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| highestPoint                  | highestPointLabel    |
| ----------------------------- | -------------------- |
| Mount Narodnaya (wd:Q1142817) | Mount Narodnaya (en) |

The highest place of the Ural Mountains is Mount Narodnaya (wd:Q1142817).

[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 http://amur:7001

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 highest place of the Urals?

[Assistant] Let's start by looking at some similar examples.

[Tool] No examples found

[Assistant] There are no similar examples found for this question. Now, I will identify the entity "Urals" in Wikidata to understand what it refers to (likely the Ural Mountains). Then I will find the highest place (peak) associated with it.

[Tool]
Top 10 entity alternatives:
1. Ural Mountains, also known as the Urals, Urals (wd:Q35600): mountain range in Russia
2. Ural Mountains, also known as the Urals, Urals (wd:Q35600): mountain range in Russia
3. Oral, also known as Uralsk (wd:Q487439): city in Kazakhstan
4. Polar Ural, also known as Polar Urals, Poljarny Ural (wd:Q2641506): northernmost part of the Ural Mountains
5. Polar Ural, also known as Polar Urals, Poljarny Ural (wd:Q2641506): northernmost part of the Ural Mountains
6. North Urals, also known as Severnyy Ural (wd:Q2476466)
7. Subpolar Ural, also known as Pripolyarnyy Ural, Subarctic Ural, Subpolar Urals (wd:Q2371368): highest part of the Ural mountains
8. Uralsky (wd:Q1049127): human settlement in Abzelilovsky District, Republic of Bashkortostan, Russia
9. Uralsk (wd:Q4476704): human settlement in Uchalinsky District, Republic of Bashkortostan, Russia
10. Uralskaya (wd:Q2389728): Yekaterinburg Metro Station

[Assistant] The entity "Urals" corresponds to the Ural Mountains (wd:Q35600). There is also a specific entity for the highest part of the Ural Mountains called Subpolar Ural (wd:Q2371368). I will now search for the highest place (peak) of the Ural Mountains. To do this, I will look for the highest mountain or peak within the Ural Mountains.

[Tool]
Top 10 property alternatives:
1. highest point, also known as tallest point, zenith, summit, pinnacle, highest peak (wd:P610 as wdt/p): point with highest elevation in a region or path, has part(s)
2. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as wdt/p): height of the item (geographical object) as measured relative to sea level
3. Peakbagger area ID, also known as Peakbagger range ID (wd:P3635 as wdt/p): identifier for a mountain range or an area, on the peakbagger.com website
4. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
5. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
6. winter view, also known as snowy picture, winter image, snowy image, snowscape, image in winter (wd:P5252 as wdt/p): image of the subject in winter, preferably with snow, image
7. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
8. length, also known as size, long, LOA, distance, dimension (wd:P2043 as wdt/p): measured dimension of an object
9. locator map image, also known as locator map, map image, map (wd:P242 as wdt/p): geographic map image which highlights the location of the subject within some larger entity, image

No other items found

[Assistant] The property "highest point" (wdt:P610) is used to indicate the highest point or peak in a region. I will now query for the highest point of the Ural Mountains (wd:Q35600) using this property.

[Tool]
Got 1 row and 2 columns:
| highestPoint                  | highestPointLabel    |
| ----------------------------- | -------------------- |
| Mount Narodnaya (wd:Q1142817) | Mount Narodnaya (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?country ?countryLabel WHERE {
  wd:Q78707 wdt:P205 ?country .
  ?country rdfs:label ?countryLabel .
  FILTER ( LANG( ?countryLabel ) = "en" )
}

Got 2 rows and 2 columns:
| country            | countryLabel  |
| ------------------ | ------------- |
| Russia (wd:Q159)   | Russia (en)   |
| Mongolia (wd:Q711) | Mongolia (en) |

The Yenisei river flows through the countries Russia and Mongolia.

[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 http://amur:7001

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] Through which countries does the Yenisei river flow?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
What form of government does Russia have?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q159 p:P122 ?q .
  ?q ps:P122 ?uri .
  FILTER NOT EXISTS {
    ?q pq:P582 ?x
  }
}

Using entities:
Russia, also known as Russian Federation, RUS, RU, RF, ISO 3166-1:RU (wd:Q159): country in Eastern Europe and Northern Asia

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as ps/p): subject's government
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 2:
Question:
Which rivers flow into the North Sea?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q4022 .
  ?uri wdt:P403 wd:Q1693 .
}

Using entities:
North Sea, also known as German Ocean, the North Sea, the German Sea, the British Ocean, German Sea (wd:Q1693): marginal sea of the Atlantic Ocean
river, also known as rivers (wd:Q4022): larger natural watercourse

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
mouth of the watercourse, also known as flows into, watercourse outflow, watercourse ends in, watercourse drain, tributary of (wd:P403 as wdt): the body of water to which the watercourse drains

[Assistant]
The Yenisei river is an entity we need to identify. We want to find the countries through which it flows. This means we are looking for a property that relates the Yenisei river to countries it flows through.

Step 1: Search for the entity "Yenisei river" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Yenisey, also known as River Yenisei, Yenisei River, Yenisei R., Yenisei, R. Yenisei (wd:Q78707): river in Asia; the 5th-longest in the world
2. Yenisei River (wd:Q34969643): river in Russia
3. Yenisei River, also known as IMO 9629586 (wd:Q113553726): ship built in 2013
4. Little Yenisey, also known as Little Yenisei River, Shishged River, Shishged Gol, Maly Yenisey, Malyj Enisej (wd:Q1511505): river in Russia and Mongolia
5. A new ferrobacterium from Yenisei River (wd:Q82038486): scientific article published on October 29, 2010
6. river, also known as rivers (wd:Q4022): larger natural watercourse
7. Club Atlético River Plate, also known as CA River Plate, C.A.R.P., CARP, River, River Plate (wd:Q15799): Argentine professional sports club based in Buenos Aires
8. Khakas people, also known as Yenisei Kirgiz, Yennisej Tatars, Yenisei Turks, Yenisei Tatars, Yenisei Kyrgyz (wd:Q240293): ethnic group
9. main stream, also known as main stem, mainstem, river, trunk, veletok (wd:Q573344): final large channel of a riverine system
10. Kaduna River, also known as River (wd:Q2338605): river in Nigeria

[Assistant] The Yenisei river is represented by wd:Q78707 in Wikidata. Now, I want to find the property that relates the Yenisei river to the countries it flows through. I will search for properties of the Yenisei river related to countries or flowing through.

[Tool]
Top 10 property alternatives:
1. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
2. continent (wd:P30 as wdt/p): continent of which the subject is a part, located in/on physical feature
3. 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 wdt/p): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
6. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
7. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
9. basin country, also known as basin countries (wd:P205 as wdt/p): country that have drainage to/from or border the body of water
10. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as wdt/p): label for the items in their official language  or their original language, name

No other items found

[Assistant]
The property "basin country" (wdt:P205) seems to be the most relevant for the question "Through which countries does the Yenisei river flow?" because it indicates countries that have drainage to/from or border the body of water.

I will now write a SPARQL query to find the countries through which the Yenisei river (wd:Q78707) flows using the property "basin country" (wdt:P205).

[Tool]
Got 2 rows and 2 columns:
| country            | countryLabel  |
| ------------------ | ------------- |
| Russia (wd:Q159)   | Russia (en)   |
| Mongolia (wd:Q711) | Mongolia (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?actor ?actorLabel WHERE {
  ?actor wdt:P31 wd:Q5 .
  ?actor wdt:P106 wd:Q33999 .
  ?actor wdt:P19 ?birthPlace .
  ?birthPlace wdt:P17 wd:Q183 .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel FILTER ( LANG( ?actorLabel ) = "en" )
  }
}
LIMIT 100

Got 100 rows and 2 columns, showing the first 5 and last 5 rows below:
| actor                        | actorLabel           |
| ---------------------------- | -------------------- |
| Florian Jahr (wd:Q1000015)   | Florian Jahr (en)    |
| Renee Goddard (wd:Q1000204)  | Renee Goddard (en)   |
| Jörg Hube (wd:Q100028)       | Jörg Hube (en)       |
| Peter Buchholz (wd:Q1000416) | Peter Buchholz (en)  |
| Jona Mues (wd:Q1000748)      | Jona Mues (en)       |
| ...                          | ...                  |
| Marie Zielcke (wd:Q101888)   | Marie Zielcke (en)   |
| Rolf Weih (wd:Q101897)       | Rolf Weih (en)       |
| Gerd Baltus (wd:Q101969)     | Gerd Baltus (en)     |
| Jesko Friedrich (wd:Q101990) | Jesko Friedrich (en) |
| Heinrich Becker (wd:Q102030) | Heinrich Becker (en) |

The query returns actors who were born in Germany. The results include actors such as Florian Jahr, Renee Goddard, Jörg Hube, Peter Buchholz, and many others.

[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 http://amur:7001

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 actors were born in Germany?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
Give me all federal chancellors of Germany.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P39 wd:Q4970706 .
}

Using entities:
Federal Chancellor of Germany, also known as German Federal Chancellor, prime minister of Germany, German Chancellor, Federal Chancellor of the Federal Republic of Germany, Federal Chancellor (wd:Q4970706): head of government of the Federal Republic of Germany (1949–present)

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt): subject currently or formerly holds the object position or public office

[Assistant]
The example found is about federal chancellors of Germany, which is not directly related to actors born in Germany. So, I will proceed with identifying the entities and properties needed for the query.

Step 1: Identify the entity for "actor."
Step 2: Identify the entity for "Germany."
Step 3: Identify the property for "place of birth."

I will start by searching for the entity "actor" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. actor, also known as actress, actresses, movie actress, movie actresses, actors (wd:Q33999): person who acts in a dramatic or comic production and works in film, television, theatre, or radio
2. 12238 Actor, also known as Actor (wd:Q2213115): asteroid
3. Actor (wd:Q421957): actor in the Unified Modeling Language (UML) "specifies a role p... by a user or any other system that interacts with the subject."
4. Actor (wd:Q423424): king in Greek mythology, son of Phorbas
5. Actor (wd:Q2473937): Son of Deion, figure of Greek mythology
6. television actor, also known as actor, actress, television actress, TV actor, TV actress (wd:Q10798782): actor who performs on television
7. Actor, also known as Acton (wd:Q2823762): king in Greek mythology, son of Myrmidon
8. actor (wd:Q421946): person performing an action
9. Actor (wd:Q4677715): album by St. Vincent
10. Actor (wd:Q2823758): son of Azeus in Greek mythology

[Assistant]
The entity "actor" in the sense of a person who acts in dramatic or comic productions is wd:Q33999. This is the appropriate entity for our query.

Next, I will search for the entity "Germany" in Wikidata.

[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

[Assistant]
The entity for the country Germany is wd:Q183.

Now, I will search for the property that represents "place of birth" to find actors born in Germany.

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): most specific known birth location of a person, animal or fictional character, location
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): date on which the subject was born, inception
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): the object is a country that recognizes the subject as its citizen, country
4. birthday, also known as b-day, bday, birth day (wd:P3150 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
5. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): full name of a person at birth, if different from their current, generally used name, name
6. category for people born here, also known as category for place of birth, category of people born here (wd:P1464 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): category item that groups people born in this place, related category
7. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): place where a statement is valid, applies to part
8. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
9. country, also known as sovereign state, state, land, host country (wd:P17 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
10. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as p/pqv/psn/wdtn/pqn/prv/psv/pr/pq/wdt/ps/prn): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant]
The property "place of birth" is wd:P19. This property is used to indicate the most specific known birth location of a person.

Now, I will construct a SPARQL query to find actors (wd:Q33999) who have a place of birth (wdt:P19) in Germany (wd:Q183).

[Tool]
Got 100 rows and 2 columns, showing the first 5 and last 5 rows below:
| actor                        | actorLabel           |
| ---------------------------- | -------------------- |
| Florian Jahr (wd:Q1000015)   | Florian Jahr (en)    |
| Renee Goddard (wd:Q1000204)  | Renee Goddard (en)   |
| Jörg Hube (wd:Q100028)       | Jörg Hube (en)       |
| Peter Buchholz (wd:Q1000416) | Peter Buchholz (en)  |
| Jona Mues (wd:Q1000748)      | Jona Mues (en)       |
| ...                          | ...                  |
| Marie Zielcke (wd:Q101888)   | Marie Zielcke (en)   |
| Rolf Weih (wd:Q101897)       | Rolf Weih (en)       |
| Gerd Baltus (wd:Q101969)     | Gerd Baltus (en)     |
| Jesko Friedrich (wd:Q101990) | Jesko Friedrich (en) |
| Heinrich Becker (wd:Q102030) | Heinrich Becker (en) |

[Assistant]
I have found actors who were born in Germany by querying for humans with the occupation "actor" and a place of birth located in Germany. The query returned several actors with their Wikidata identifiers and English labels.

Now I will provide the final SPARQL query and answer.

[Tool] Stopped generation process