PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?origin ?originLabel WHERE {
  wd:Q8216 wdt:P144 ?origin .
  OPTIONAL {
    ?origin rdfs:label ?originLabel FILTER ( LANG( ?originLabel ) = "en" )
  }
}

The Greek alphabet came from the Phoenician script.

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

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

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

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

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

[User] where did the greek alphabet come from?

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

[Tool]
Example 1:
Question:
where does the roman language come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q397 wdt:P279 ?x .
}

Using entities:
Latin, also known as Latina, Latin language, Latinum (wd:Q397): Indo-European language of the Italic branch

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

Example 2:
Question:
where does the spanish language come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1321 wdt:P279 ?x .
}

Using entities:
Spanish, also known as Castilian, Castilian language, es, esp, Español (wd:Q1321): Romance language originating in the Iberian Peninsula

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

Example 3:
Question:
where did the name rome come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q220 wdt:P138 ?x .
}

Using entities:
Rome, also known as Roma, City of Seven Hills, Rome, Italy, The Eternal City (wd:Q220): capital and largest city of Italy

Using properties:
named after, also known as toponym, namesake, named in honor of, named for, etymology (wd:P138 as wdt): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one

[Assistant]
The Greek alphabet is a writing system, so to find where it came from, we should look for its origin or predecessor writing system. The Greek alphabet is likely an entity in Wikidata, and it might have a property indicating its origin or derived from which writing system.

Step 1: Search for the entity "Greek alphabet" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Greek alphabet, also known as Greek script, Greek (wd:Q8216): script used to write the Greek language
2. history of the Greek alphabet, also known as Greek alphabet history, the Greek alphabet history (wd:Q2627294): aspect of history
3. Greek Albanian alphabet (wd:Q3305475): Greek alphabet adapted for writing the Albanian language
4. Greek spelling alphabet (wd:Q17003959): spelling alphabet for Greek letters
5. extended greek alphabet (wd:Q3237041)
6. ancient Greek alphabet, also known as archaic Greek alphabet (wd:Q3611036): writing system
7. archaic Greek alphabets (wd:Q2839562): Local variants of the ancient Greek alphabet
8. Inscriptions in Greek Alphabet (wd:Q106814193): drawing - Sir Robert Smirke the younger (YCBA B1977.14.581)
9. Inscriptions in Greek Alphabet (wd:Q106814190): drawing - Sir Robert Smirke the younger
10. Ancient Inscriptions in Greek Alphabet (wd:Q106812515): drawing - Sir Robert Smirke the younger

[Assistant]
The entity "Greek alphabet" (wd:Q8216) is the script used to write the Greek language. There is also "ancient Greek alphabet" (wd:Q3611036) which might be relevant for historical origin.

Step 2: Check properties of the Greek alphabet (wd:Q8216) to find any property related to its origin or derived from.

[Tool]
Top 10 property alternatives:
1. location of creation, also known as manufactured in, manufacturing location, mint, minted at, photographed at (wd:P1071 as p/wdt): place where the item was conceived or made; where applicable, location of final assembly, significant place
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
3. based on, also known as modelled after, inspired by, iteration of, modeled after, fork of (wd:P144 as p/wdt): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, references work, tradition or theory, inspired by
4. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
5. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as p/wdt): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))

No other items found

[Assistant]
The property "based on" (wdt:P144) seems relevant as it indicates the work or input used as the basis for the subject item. This could be used to find the origin or predecessor of the Greek alphabet.

Step 3: Query the Greek alphabet (wd:Q8216) for the property "based on" (wdt:P144) to find where the Greek alphabet came from.

[Tool]
Got 1 row and 2 columns:
| origin                        | originLabel            |
| ----------------------------- | ---------------------- |
| Phoenician script (wd:Q26752) | Phoenician script (en) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?movie ?movieLabel WHERE {
  ?movie wdt:P161 wd:Q6107 ; wdt:P31 / wdt:P279 * wd:Q11424 .
  OPTIONAL {
    ?movie rdfs:label ?movieLabel FILTER ( LANG( ?movieLabel ) = "en" )
  }
}

Got 13 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                                            | movieLabel                             |
| ------------------------------------------------ | -------------------------------------- |
| Thug Angel: The Life of an Outlaw (wd:Q11704796) | Thug Angel: The Life of an Outlaw (en) |
| Poetic Justice (wd:Q1537562)                     | Poetic Justice (en)                    |
| Straight Outta Compton (wd:Q18154625)            | Straight Outta Compton (en)            |
| Above the Rim (wd:Q2128630)                      | Above the Rim (en)                     |
| Biggie & Tupac (wd:Q2451402)                     | Biggie & Tupac (en)                    |
| ...                                              | ...                                    |
| Juice (wd:Q642419)                               | Juice (en)                             |
| Tupac: Resurrection (wd:Q749899)                 | Tupac: Resurrection (en)               |
| Tupac: Assassination (wd:Q7853467)               | Tupac: Assassination (en)              |
| Bullet (wd:Q911823)                              | Bullet (en)                            |
| Gridlock'd (wd:Q951966)                          | Gridlock'd (en)                        |

Tupac starred in the following movies: Thug Angel: The Life of an Outlaw, Poetic Justice, Straight Outta Compton, Above the Rim, Biggie & Tupac, Juice, Tupac: Resurrection, Tupac: Assassination, Bullet, and Gridlock'd among 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 https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

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

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

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

[User] what movies did tupac star in?

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

[Tool]
Example 1:
Question:
what movies does tupac act in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q6107 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Tupac Shakur, also known as Tupac, Tupac Amaru Shakur, Makaveli, Tupac Omar Shakur, Lesane Crooks (wd:Q6107): American rapper (1971–1996), television actor, songwriter, film actor, lyricist, activist, writer, singer, rapper, actor, poet

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
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)

Example 2:
Question:
what was tupac name in juice?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q642419 p:P161 ?p .
  ?p ps:P161 wd:Q6107 ; pq:P453 ?x .
}

Using entities:
Tupac Shakur, also known as Tupac, Tupac Amaru Shakur, Makaveli, Tupac Omar Shakur, Lesane Crooks (wd:Q6107): American rapper (1971–1996), television actor, songwriter, film actor, lyricist, activist, writer, singer, rapper, actor, poet
Juice (wd:Q642419): 1992 film directed by Ernest Dickerson

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

Example 3:
Question:
who was killed first tupac or biggie?

SPARQL:
SELECT DISTINCT ?x WHERE {
  {
    wd:Q6107 wdt:P570 ?y ; rdfs:label ?x .
    FILTER ( LANGMATCHES( LANG( ?x ) , "EN" ) )
  } UNION {
    wd:Q179157 wdt:P570 ?y ; rdfs:label ?x .
    FILTER ( LANGMATCHES( LANG( ?x ) , "EN" ) )
  }
}
ORDER BY ?y
LIMIT 1

Using entities:
The Notorious B.I.G., also known as Frank White, Notorious B.I.G., King of Brooklyn, Christopher Wallace, Notorious BIG (wd:Q179157): American rapper, songwriter, producer and actor (1972–1997), record producer, songwriter, rapper, actor
Tupac Shakur, also known as Tupac, Tupac Amaru Shakur, Makaveli, Tupac Omar Shakur, Lesane Crooks (wd:Q6107): American rapper (1971–1996), television actor, songwriter, film actor, lyricist, activist, writer, singer, rapper, actor, poet

Using properties:
date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as wdt): dissolved, abolished or demolished date, date on which the subject died, end time

[Assistant] From the examples, we see that Tupac Shakur is wd:Q6107 and movies are instances or subclasses of wd:Q11424 (film). The property for starring or cast member in a movie is wdt:P161. We can use this information to write a query that finds all movies where Tupac Shakur starred. I will now write and execute this query.

[Tool]
Got 13 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                                            | movieLabel                             |
| ------------------------------------------------ | -------------------------------------- |
| Thug Angel: The Life of an Outlaw (wd:Q11704796) | Thug Angel: The Life of an Outlaw (en) |
| Poetic Justice (wd:Q1537562)                     | Poetic Justice (en)                    |
| Straight Outta Compton (wd:Q18154625)            | Straight Outta Compton (en)            |
| Above the Rim (wd:Q2128630)                      | Above the Rim (en)                     |
| Biggie & Tupac (wd:Q2451402)                     | Biggie & Tupac (en)                    |
| ...                                              | ...                                    |
| Juice (wd:Q642419)                               | Juice (en)                             |
| Tupac: Resurrection (wd:Q749899)                 | Tupac: Resurrection (en)               |
| Tupac: Assassination (wd:Q7853467)               | Tupac: Assassination (en)              |
| Bullet (wd:Q911823)                              | Bullet (en)                            |
| Gridlock'd (wd:Q951966)                          | Gridlock'd (en)                        |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?movie ?movieLabel WHERE {
  ?movie wdt:P161 wd:Q169982 ; wdt:P31 / wdt:P279 * wd:Q11424 .
  OPTIONAL {
    ?movie rdfs:label ?movieLabel FILTER ( LANG( ?movieLabel ) = "en" )
  }
}

Got 53 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                             | movieLabel                |
| --------------------------------- | ------------------------- |
| Fast Food (wd:Q10280250)          | Fast Food (en)            |
| Copshop (wd:Q103822078)           | Copshop (en)              |
| Plane (wd:Q108131599)             | Plane (en)                |
| Kandahar (wd:Q111940088)          | Kandahar (en)             |
| Last Seen Alive (wd:Q112343991)   | Last Seen Alive (en)      |
| ...                               | ...                       |
| The Ugly Truth (wd:Q922630)       | The Ugly Truth (en)       |
| Reign of Fire (wd:Q925384)        | Reign of Fire (en)        |
| Gamer (wd:Q947885)                | Gamer (en)                |
| Law Abiding Citizen (wd:Q951071)  | Law Abiding Citizen (en)  |
| Butterfly on a Wheel (wd:Q967489) | Butterfly on a Wheel (en) |

Gerard Butler has been in movies such as Fast Food, Copshop, Plane, Kandahar, Last Seen Alive, The Ugly Truth, Reign of Fire, Gamer, Law Abiding Citizen, and Butterfly on a Wheel, among others. The query returned 53 movies in total.

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

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

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

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

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

[User] what movies gerard butler has been in?

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

[Tool]
Example 1:
Question:
what films has gerard butler starred in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q169982 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Gerard Butler, also known as Gerard James Butler (wd:Q169982): Scottish actor and film producer (born 1969), television actor, film producer, stage actor, film actor, lawyer, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
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)

Example 2:
Question:
what movies did james franco play in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q306403 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
James Franco, also known as James Edward Franco (wd:Q306403): television presenter, television actor, American actor, film producer, film director, screenwriter, film editor, film actor, playwright, teacher, writer, actor, poet

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
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)

Example 3:
Question:
what are all the movies channing tatum has been in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q212064 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Channing Tatum, also known as Channing Matthew Tatum (wd:Q212064): American actor, dancer and model (born 1980), television actor, film director, film producer, voice actor, film actor, dancer, model, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
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)

[Assistant]
From the similar examples, the pattern to find movies an actor has been in is to find films (?x) where the actor is a cast member (wdt:P161) and the film is an instance of or subclass of film (wd:Q11424).

Next, I will search for the entity Gerard Butler to get his Wikidata ID.

[Tool]
Top 10 entity alternatives:
1. Gerard Butler, also known as Gerard James Butler (wd:Q169982): Scottish actor and film producer (born 1969), television actor, film producer, stage actor, film actor, lawyer, actor
2. Gerard A Butler (wd:Q11309355): horse trainer
3. Locky Butler, also known as Lochlann Gerard Butler (wd:Q125534277): Irish rugby union player, rugby union player
4. Gerard Butler/Shakira, also known as Saturday Night Live S35E4, Saturday Night Live, season 35 episode 4 (wd:Q110037076): episode of Saturday Night Live (S35 E4)
5. Michael Gerard Butler (wd:Q102340012): Ph.D. University of Michigan 1993
6. Butler, Edward Gerard (DNB00) (wd:Q19095193): entry in Dictionary of National Biography
7. James Robert Gerard Butler (wd:Q112436568): university teacher, economist
8. Gerard 't Hooft, also known as G. Hooft, Gerardus 't Hooft, Gerardus, G.W. 't Hooft, Hooft (wd:Q184592): Dutch theoretical physicist, theoretical physicist, university teacher, non-fiction writer, physicist, pedagogue, professor
9. Butler, also known as Butler, PA, Butler, Pennsylvania (wd:Q1017948): city and the county seat of Butler County, Pennsylvania, United States
10. Butler, also known as Butler, MO, Butler, Missouri (wd:Q955151): city in Missouri, United States

[Assistant] The entity for Gerard Butler, the Scottish actor, is wd:Q169982. Now I will write a SPARQL query to find movies where Gerard Butler is a cast member and the movie is an instance or subclass of film.

[Tool]
Got 53 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                             | movieLabel                |
| --------------------------------- | ------------------------- |
| Fast Food (wd:Q10280250)          | Fast Food (en)            |
| Copshop (wd:Q103822078)           | Copshop (en)              |
| Plane (wd:Q108131599)             | Plane (en)                |
| Kandahar (wd:Q111940088)          | Kandahar (en)             |
| Last Seen Alive (wd:Q112343991)   | Last Seen Alive (en)      |
| ...                               | ...                       |
| The Ugly Truth (wd:Q922630)       | The Ugly Truth (en)       |
| Reign of Fire (wd:Q925384)        | Reign of Fire (en)        |
| Gamer (wd:Q947885)                | Gamer (en)                |
| Law Abiding Citizen (wd:Q951071)  | Law Abiding Citizen (en)  |
| Butterfly on a Wheel (wd:Q967489) | Butterfly on a Wheel (en) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?language ?languageLabel WHERE {
  {
    wd:Q145 wdt:P37 ?language .
  } UNION {
    wd:Q145 wdt:P2936 ?language .
  }
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| language                    | languageLabel        |
| --------------------------- | -------------------- |
| Polari (wd:Q1359130)        | Polari (en)          |
| Scots (wd:Q14549)           | Scots (en)           |
| English (wd:Q1860)          | English (en)         |
| Welsh Romani (wd:Q2097387)  | Welsh Romani (en)    |
| Cornish (wd:Q25289)         | Cornish (en)         |
| ...                         | ...                  |
| Scottish Cant (wd:Q3915671) | Scottish Cant (en)   |
| Angloromani (wd:Q541279)    | Angloromani (en)     |
| Irish (wd:Q9142)            | Irish (en)           |
| Welsh (wd:Q9309)            | Welsh (en)           |
| Scottish Gaelic (wd:Q9314)  | Scottish Gaelic (en) |

The major languages spoken in the United Kingdom include English (official language), Welsh, Scots, Irish, Scottish Gaelic, Cornish, Polari, Welsh Romani, Scottish Cant, Angloromani, and 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 https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

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

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

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

[User] what are the major languages spoken in the united kingdom?

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

[Tool]
Example 1:
Question:
what language is mainly spoken in england?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q21 wdt:P2936 ?x .
}

Using entities:
England, also known as England, United Kingdom, England, UK, ENG (wd:Q21): country in north-west Europe, part of the United Kingdom

Using properties:
language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt): language widely used (spoken or written) in this place or at this event or organisation

Example 2:
Question:
what are the major religions in uk?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q145 wdt:P140 ?x .
}

Using entities:
United Kingdom, also known as U.K., UK, U. K., U K, United Kingdom of Great Britain and Northern Ireland (wd:Q145): country in north-west Europe

Using properties:
religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as wdt): religion of a person, organization or religious building, or associated with this subject

Example 3:
Question:
which countries speak english?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q1860 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
English, also known as English (language), The English language, English the Global Language, English-language, English language (wd:Q1860): West Germanic language
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
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 examples, I see that the property "language used" (wdt:P2936) is used to find languages spoken in a place. The entity for the United Kingdom is wd:Q145.

I will now write a SPARQL query to find the major languages spoken in the United Kingdom using the property wdt:P2936. I will also try to get the labels of the languages.

[Tool]
Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| language                    | languageLabel        |
| --------------------------- | -------------------- |
| Polari (wd:Q1359130)        | Polari (en)          |
| Scots (wd:Q14549)           | Scots (en)           |
| English (wd:Q1860)          | English (en)         |
| Welsh Romani (wd:Q2097387)  | Welsh Romani (en)    |
| Cornish (wd:Q25289)         | Cornish (en)         |
| ...                         | ...                  |
| Scottish Cant (wd:Q3915671) | Scottish Cant (en)   |
| Angloromani (wd:Q541279)    | Angloromani (en)     |
| Irish (wd:Q9142)            | Irish (en)           |
| Welsh (wd:Q9309)            | Welsh (en)           |
| Scottish Gaelic (wd:Q9314)  | Scottish Gaelic (en) |

[Assistant]
The query returned several languages spoken in the United Kingdom, including English, Welsh, Scots, Irish, Scottish Gaelic, Cornish, and some Romani languages.

I will now refine the query to focus on the major languages by checking if there is a way to filter by "major" or "official" languages. I will search for properties related to "major language" or "official language" for the United Kingdom.

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as p/wdt): language designated as official by this item, language used
2. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
3. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as p/wdt): language widely used (spoken or written) in this place or at this event or organisation
4. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as p/wdt): official name of the subject in its official language(s), name
5. basic form of government, also known as form of government, government, type of government (wd:P122 as p/wdt): subject's government
6. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity
7. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): 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
8. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as p/wdt): political office that is fulfilled by the head of the government of this item
9. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as p/wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
10. anthem, also known as national anthem, team anthem, official song, official hymn, club anthem (wd:P85 as p/wdt): subject's official anthem

No other items found

[Assistant] The property "official language" (wdt:P37) is the appropriate property to find official languages designated by the United Kingdom. I will now query the official languages of the United Kingdom using this property.

[Tool]
Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| English (wd:Q1860) | English (en)  |

[Assistant]
The query returned only English as the official language of the United Kingdom. However, we know there are other major languages spoken in the UK that may not be official but are significant.

I will combine the results of languages widely used (wdt:P2936) and official languages (wdt:P37) to provide a comprehensive list of major languages spoken in the United Kingdom. I will also include labels for better readability.

[Tool]
Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| language                    | languageLabel        |
| --------------------------- | -------------------- |
| Polari (wd:Q1359130)        | Polari (en)          |
| Scots (wd:Q14549)           | Scots (en)           |
| English (wd:Q1860)          | English (en)         |
| Welsh Romani (wd:Q2097387)  | Welsh Romani (en)    |
| Cornish (wd:Q25289)         | Cornish (en)         |
| ...                         | ...                  |
| Scottish Cant (wd:Q3915671) | Scottish Cant (en)   |
| Angloromani (wd:Q541279)    | Angloromani (en)     |
| Irish (wd:Q9142)            | Irish (en)           |
| Welsh (wd:Q9309)            | Welsh (en)           |
| Scottish Gaelic (wd:Q9314)  | Scottish Gaelic (en) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?causeOfDeath ?causeOfDeathLabel WHERE {
  wd:Q40933 wdt:P509 ?causeOfDeath .
  OPTIONAL {
    ?causeOfDeath rdfs:label ?causeOfDeathLabel FILTER ( LANG( ?causeOfDeathLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| causeOfDeath                       | causeOfDeathLabel          |
| ---------------------------------- | -------------------------- |
| cervix uterine cancer (wd:Q160105) | cervix uterine cancer (en) |

Eva Peron died from cervix uterine cancer.

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

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

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

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

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

[User] what type of cancer did eva peron die from?

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

[Tool]
Example 1:
Question:
what type of cancer did donna summer died from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q908933 wdt:P509 ?x .
}

Using entities:
Donna Summer, also known as Donna Sommer, LaDonna Gaines (wd:Q908933): American singer (1948–2012), recording artist, songwriter, musician, composer, singer, actor

Using properties:
cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide

Example 2:
Question:
what cancer did audrey hepburn died of?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q42786 wdt:P509 ?x .
}

Using entities:
Audrey Hepburn, also known as Edda Kathleen Ruston, Audrey Kathleen Ruston, Edda van Heemstra, Audrey Kathleen Hepburn-Ruston (wd:Q42786): British actress (1929–1993), philanthropist, ballet dancer, humanitarian, stage actor, film actor, dancer, actor, model

Using properties:
cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide

Example 3:
Question:
what type of cancer did huell howser die of?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2837916 wdt:P509 ?x .
}

Using entities:
Huell Howser, also known as Huel Howser, Huel Burnley Howser (wd:Q2837916): American television personality (1945-2013), television presenter, television actor, screenwriter, voice actor, film actor

Using properties:
cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide

[Assistant] From the examples, it is clear that the property "cause of death" (wdt:P509) is used to find the type of cancer or cause of death for a person. Now, I will search for the entity "Eva Peron" in Wikidata to get her identifier.

[Tool]
Top 10 entity alternatives:
1. Eva Perón, also known as Evita Perón, Maria Eva Duarte de Peron, Evita, María Eva Duarte de Perón, Maria Eva Duarte Peron (wd:Q40933): Argentine actress and politician (1919–1952), women's rights activist, trade unionist, stage actor, suffragist, politician, film actor
2. Eva Perón: The True Story, also known as Eva Peron, Eva Perón (wd:Q953441): 1996 film by Juan Carlos Desanzo
3. Fray Luis Beltrán, also known as Eva Perón, Eva Perón tanker, Fray Luis Beltrán tanker (wd:Q113059537): tanker
4. Eva Perón (wd:Q113030601): tanker
5. Hospital Lagomarsino, also known as Eva Perón (wd:Q5902632): hospital in Merlo, Buenos Aires
6. Uruguay, also known as Eva Perón (wd:Q113330807): 1951 passenger ship
7. Eva Perón (wd:Q47512378): painting by Boris Chaliapin
8. Estadio Eva Perón, also known as Estadio Eva Peron (wd:Q5400194): football stadium in Junín, Argentina
9. Puerto Eva Perón (wd:Q972928): ciudad en la provincia de Chaco, Argentina
10. Eva Perón Foundation (wd:Q2004004): former Argentine foundation

[Assistant] The entity for Eva Peron is wd:Q40933. Based on the examples, the property for cause of death is wdt:P509. I will now query the cause of death for Eva Peron.

[Tool]
Got 1 row and 2 columns:
| causeOfDeath                       | causeOfDeathLabel          |
| ---------------------------------- | -------------------------- |
| cervix uterine cancer (wd:Q160105) | cervix uterine cancer (en) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?language ?languageLabel WHERE {
  wd:Q408 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| language                       | languageLabel           |
| ------------------------------ | ----------------------- |
| Auslan (wd:Q29525)             | Auslan (en)             |
| Australian English (wd:Q44679) | Australian English (en) |

People in Australia speak Australian English and Auslan as official languages.

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

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

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

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

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

[User] what do people in australia speak?

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

[Tool]
Example 1:
Question:
what language does people speak in australia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q408 wdt:P37 ?x .
}

Using entities:
Australia, also known as AU, The Commonwealth of Australia, Stria, Straya, Stralia (wd:Q408): country in Oceania

Using properties:
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

Example 2:
Question:
what language do australian people speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q408 wdt:P37 ?x .
}

Using entities:
Australia, also known as AU, The Commonwealth of Australia, Stria, Straya, Stralia (wd:Q408): country in Oceania

Using properties:
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

Example 3:
Question:
what do people in south africa speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q258 wdt:P37 ?x .
}

Using entities:
South Africa, also known as zaf, R.S.A., za, RSA, SA (wd:Q258): country in southern Africa

Using properties:
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 similar examples, it is clear that the property "official language" (wdt:P37) is used to find the languages spoken in a country. The entity for Australia is wd:Q408. I will now write a SPARQL query to find the languages spoken in Australia using this property.

[Tool]
Got 2 rows and 2 columns:
| language                       | languageLabel           |
| ------------------------------ | ----------------------- |
| Auslan (wd:Q29525)             | Auslan (en)             |
| Australian English (wd:Q44679) | Australian English (en) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?currency ?currencyLabel WHERE {
  wd:Q38 wdt:P38 ?currency .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| currency        | currencyLabel |
| --------------- | ------------- |
| Euro (wd:Q4916) | euro (en)     |

The money used in Italy is called the Euro.

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

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

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

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

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

[User] what is money called in italy?

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

[Tool]
Example 1:
Question:
what money do they have in italy?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q38 wdt:P38 ?x .
}

Using entities:
Italy, also known as Italia, Republic of Italy, Repubblica Italiana, Italian Republic, ITA (wd:Q38): country in Southern Europe

Using properties:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

Example 2:
Question:
what currency should i bring to italy?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q38 wdt:P38 ?x .
}

Using entities:
Italy, also known as Italia, Republic of Italy, Repubblica Italiana, Italian Republic, ITA (wd:Q38): country in Southern Europe

Using properties:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

Example 3:
Question:
what is the money called in spain?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29 wdt:P38 ?x .
}

Using entities:
Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa

Using properties:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

[Assistant] From the examples, it is clear that the property "currency" (wdt:P38) is used to find the money used in a country. Italy is represented by wd:Q38. So, the query to find what money is called in Italy is to select the currency used by Italy. I will now write and execute this query.

[Tool]
Got 1 row and 2 columns:
| currency        | currencyLabel |
| --------------- | ------------- |
| Euro (wd:Q4916) | euro (en)     |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?wife ?wifeLabel WHERE {
  wd:Q34969 wdt:P26 ?wife .
  ?wife rdfs:label ?wifeLabel .
  FILTER ( LANG( ?wifeLabel ) = "en" )
}

The name of Benjamin Franklin's wife was Deborah Read Franklin.

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

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

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

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

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

[User] what was the name of benjamin franklin wife?

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

[Tool]
Example 1:
Question:
where did benjamin franklin died?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q34969 wdt:P20 ?x .
}

Using entities:
Benjamin Franklin, also known as The First American, Silence Dogood, Poor Richard, Ben Franklin, Franklin (wd:Q34969): American polymath and statesman (1706–1790), politician, polymath, diplomat, writer

Using properties:
place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location

Example 2:
Question:
what was one of benjamin franklin's inventions?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P61 wd:Q34969 .
}

Using entities:
Benjamin Franklin, also known as The First American, Silence Dogood, Poor Richard, Ben Franklin, Franklin (wd:Q34969): American polymath and statesman (1706–1790), politician, polymath, diplomat, writer

Using properties:
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:
what was lincoln's wife's name?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q91 wdt:P26 ?x .
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

[Assistant] From the similar examples, I see that the entity for Benjamin Franklin is wd:Q34969 and the property for spouse (wife or husband) is wdt:P26. I will now write a SPARQL query to find the name of Benjamin Franklin's wife using these.

[Tool]
Got 1 row and 2 columns:
| wife                                | wifeLabel                  |
| ----------------------------------- | -------------------------- |
| Deborah Read Franklin (wd:Q3020859) | Deborah Read Franklin (en) |

[Tool] Stopped generation process