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 ?state ?stateLabel WHERE {
  wd:Q734774 wdt:P131 ?city .
  ?city wdt:P131 ?state .
  FILTER ( EXISTS {
    wd:Q734774 wdt:P131 ?city
  }
  ) OPTIONAL {
    ?state rdfs:label ?stateLabel FILTER ( LANG( ?stateLabel ) = "en" )
  }
}

Saint Louis University is located in the state of Missouri.

[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

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 state is saint louis university in?

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

[Tool]
Example 1:
Question:
where is st louis cardinals stadium?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q504309 wdt:P115 ?x .
}

Using entities:
St. Louis Cardinals, also known as St. Louis Brown Stockings, St. Louis Perfectos, St. Louis Browns, Saint Louis Cardinals, Red Birds (wd:Q504309): Major League Baseball franchise in St. Louis, Missouri

Using properties:
home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt): home stadium or venue of a sports team or applicable performing arts organization, location

Example 2:
Question:
where is the university of oregon state?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q861888 wdt:P131 ?x .
}

Using entities:
Oregon State University, also known as Corvallis College, Corvallis State Agricultural College, Oregon Agricultural College, Oregon State Agricultural College, Oregon State College (wd:Q861888): public research university in Corvallis, Oregon, United States

Using properties:
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): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of

Example 3:
Question:
where is santa clara university?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q992830 wdt:P131 ?x .
}

Using entities:
Santa Clara University, also known as University of Santa Clara, SCU (wd:Q992830): private non-profit Jesuit university located in Santa Clara, California, United States

Using properties:
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): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of

[Assistant] From the examples, it seems that the property "located in the administrative territorial entity" (wdt:P131) is used to find the state or administrative region where a university is located. Next, I will search for the entity "Saint Louis University" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Saint Louis University, also known as SLU, St. Louis University (wd:Q734774): private research university with campuses in St. Louis, Missouri, and Madrid, Spain
2. Saint Louis University, also known as SLU, St. Louis University (wd:Q7401676): university in Baguio, Philippines
3. Washington University in St. Louis, also known as WUSTL, WashU, Wash. U., Washington University in Saint Louis, Washington University (Saint Louis, Mo.) (wd:Q777403): private research university in St. Louis, Missouri, United States
4. Saint Louis Billikens, also known as Saint Louis University athletics (wd:Q7401655): athletic program of Saint Louis University
5. Saint Louis University Hospital, also known as Firmin Desloge Hospital, SLU Hospital (wd:Q7401677): hospital in Missouri, United States
6. Saint Louis University Bookstore (wd:Q99475974): bookshop in Saint Louis, MO, United States of America
7. Saint Louis University Madrid Campus (wd:Q4116998)
8. Maryville University, also known as Maryville College of the Sacred Heart, Maryville University of St. Louis, Maryville University of Saint Louis (wd:Q6781811): private university located in Missouri
9. University of Saint Louis Tuguegarao (wd:Q7896224): private university in the Philippines
10. Saint Louis University Law Journal (wd:Q15767443): journal

[Assistant] The entity "Saint Louis University" with the identifier wd:Q734774 matches the private research university with campuses in St. Louis, Missouri, and Madrid, Spain. Now I will query the state or administrative territorial entity where this university is located using the property "located in the administrative territorial entity" (wdt:P131).

[Tool]
Got 1 row and 2 columns:
| state                 | stateLabel     |
| --------------------- | -------------- |
| St. Louis (wd:Q38022) | St. Louis (en) |

[Assistant] The query result indicates that Saint Louis University is located in St. Louis, which is a city, not a state. Since the user asked for the state, I will now query the state or equivalent administrative division that contains St. Louis. I will use the entity for St. Louis (wd:Q38022) and again use the property "located in the administrative territorial entity" (wdt:P131) to find the state.

[Tool]
Got 1 row and 2 columns:
| state               | stateLabel    |
| ------------------- | ------------- |
| Missouri (wd:Q1581) | Missouri (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the state where Saint Louis University is located by traversing the administrative territorial entities. It returns the state entity and its English label, which matches the answer provided: Missouri. The query is well-formed, uses appropriate properties, and the result is accurate and complete. No further refinement is needed.


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 ?team ?teamLabel WHERE {
  wd:Q3887743 wdt:P54 ?team .
  OPTIONAL {
    ?team rdfs:label ?teamLabel FILTER ( LANG( ?teamLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| team                             | teamLabel                |
| -------------------------------- | ------------------------ |
| Philadelphia Eagles (wd:Q219714) | Philadelphia Eagles (en) |
| Seattle Seahawks (wd:Q221878)    | Seattle Seahawks (en)    |
| Las Vegas Raiders (wd:Q324523)   | Las Vegas Raiders (en)   |

Owen Schmitt plays for the Philadelphia Eagles, Seattle Seahawks, and Las Vegas Raiders.

[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

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 does owen schmitt play for?

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

[Tool]
Example 1:
Question:
who does john beck play for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q6221292 wdt:P54 ?x .
}

Using entities:
John Beck, also known as John Dalton Beck (wd:Q6221292): American gridiron football player and coach (born 1981), American football player, Canadian football player

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

Example 2:
Question:
who does michael vick play for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q505431 wdt:P54 ?x .
}

Using entities:
Michael Vick, also known as Michael Dwayne Vick (wd:Q505431): American football player (born 1980), American football player, offensive coordinator

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

Example 3:
Question:
what team does chris humphrey play for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q797835 wdt:P54 ?x .
}

Using entities:
Chris Humphrey (wd:Q797835): Professional footballer (born 1987), association football player

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

[Assistant] From the similar examples, it is clear that the property "member of sports team" (wdt:P54) is used to indicate the team a sports player plays for. Next, I will search for the entity "Owen Schmitt" in Wikidata to find his identifier. Then I will use that identifier to query the team he plays for.

[Tool]
Top 10 entity alternatives:
1. Owen Schmitt (wd:Q3887743): American football fullback, American football player
2. Richard Owen, also known as R. Owen, Owen, Richard, Prof OWEN F.R.S., Sir Richard Owen, Sir R. Owen (wd:Q151556): English biologist and paleontologist (1804–1892), paleoanthropologist, university teacher, paleontologist, zoologist, anatomist, biologist, curator, writer
3. Wilfred Owen, also known as Owen, Wilfred Edward Salter Owen (wd:Q212719): English poet and soldier (1893-1918), writer, poet
4. Owen (wd:Q81006): municipality in Germany
5. Owen, also known as City of Owen, Owen, WI (wd:Q1569456): city in Clark County, Wisconsin
6. Schmitt (wd:Q654052): municipality of Germany
7. Owain Owain, also known as Owen Owen (wd:Q3398027): Welsh novelist, short story writer and poet (1929–1993), nuclear physicist, educator, writer, poet
8. Schmitt (wd:Q2246512): family name
9. Owen, also known as Owen surname, Owen family name (wd:Q1158545): family name
10. Mount Owen, also known as Mount Owen (Antarctica), Owen (wd:Q6922630): mountain in Antarctica

[Assistant] The entity "Owen Schmitt" corresponds to wd:Q3887743 in Wikidata, who is an American football fullback. Now I will query which sports team Owen Schmitt (wd:Q3887743) plays for using the property "member of sports team" (wdt:P54).

[Tool]
Got 3 rows and 2 columns:
| team                             | teamLabel                |
| -------------------------------- | ------------------------ |
| Philadelphia Eagles (wd:Q219714) | Philadelphia Eagles (en) |
| Seattle Seahawks (wd:Q221878)    | Seattle Seahawks (en)    |
| Las Vegas Raiders (wd:Q324523)   | Las Vegas Raiders (en)   |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all sports teams that Owen Schmitt has played for using the property 'member of sports team' (wdt:P54). The query returns the identifiers and English labels of the teams, which matches the user's question about who Owen Schmitt plays for. The answer is complete and accurate, listing the Philadelphia Eagles, Seattle Seahawks, and Las Vegas Raiders. No further refinement is necessary.


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 ?religion ?religionLabel WHERE {
  wd:Q801 wdt:P3075 ?religion .
  OPTIONAL {
    ?religion rdfs:label ?religionLabel FILTER ( LANG( ?religionLabel ) = "en" )
  }
}

Got 4 rows and 2 columns:
| religion                | religionLabel     |
| ----------------------- | ----------------- |
| Druzism (wd:Q163943)    | Druzism (en)      |
| Islam (wd:Q432)         | Islam (en)        |
| Christianity (wd:Q5043) | Christianity (en) |
| Judaism (wd:Q9268)      | Judaism (en)      |

The official religions in Israel are Judaism, Islam, Christianity, and Druzism, as retrieved from Wikidata. However, Wikidata does not have a direct property indicating the predominant religion by population. Based on common knowledge, Judaism is the predominant religion in Israel.

[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

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 predominant religion in israel?

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

[Tool]
Example 1:
Question:
what are the major religions practiced in israel?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q801 wdt:P3075 ?x .
}

Using entities:
Israel, also known as Yisrael, State of Israel, IL, ISR, il (wd:Q801): country in Western Asia

Using properties:
official religion, also known as established religion, state religion (wd:P3075 as wdt): official religion in this administrative entity

Example 2:
Question:
what is the religion of israel people?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q801 wdt:P3075 ?x .
}

Using entities:
Israel, also known as Yisrael, State of Israel, IL, ISR, il (wd:Q801): country in Western Asia

Using properties:
official religion, also known as established religion, state religion (wd:P3075 as wdt): official religion in this administrative entity

Example 3:
Question:
what is the dominant language in israel?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q801 wdt:P37 ?x .
}

Using entities:
Israel, also known as Yisrael, State of Israel, IL, ISR, il (wd:Q801): country in Western Asia

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, the property wdt:P3075 (official religion, also known as established religion, state religion) is used to find the religion related to a country. The entity for Israel is wd:Q801.

I will now execute a query to find the official or predominant religion in Israel using this property.

[Tool]
Got 4 rows and 2 columns:
| religion                | religionLabel     |
| ----------------------- | ----------------- |
| Druzism (wd:Q163943)    | Druzism (en)      |
| Islam (wd:Q432)         | Islam (en)        |
| Christianity (wd:Q5043) | Christianity (en) |
| Judaism (wd:Q9268)      | Judaism (en)      |

[Assistant]
The query returned multiple religions listed as official or established religions in Israel: Druzism, Islam, Christianity, and Judaism. However, the user asked for the predominant religion, which is typically the religion with the largest number of adherents.

I will now search for a property or statement that indicates the predominant or majority religion in Israel. One possible property to check is "religion" (P140) in relation to the population or demographics of Israel. I will search for properties related to religion and population or demographics for Israel.

[Tool]
Top 10 property alternatives:
1. official religion, also known as established religion, state religion (wd:P3075 as wdt/p): official religion in this administrative entity
2. 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
3. flag, also known as flag description (wd:P163 as wdt/p): subject's flag
4. political ideology, also known as editorial viewpoint, has political ideology, ideology, official ideology, official political ideology (wd:P1142 as wdt/p): political ideology of an organization or person or of a work (such as a newspaper)
5. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as wdt/p): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
6. basic form of government, also known as form of government, government, type of government (wd:P122 as wdt/p): subject's government
7. population, also known as inhabitants, human population (wd:P1082 as wdt/p): number of people inhabiting the place; number of people of subject
8. 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)
9. external data available at URL, also known as data, external data URL, URL with external data (wd:P1325 as wdt/p): URL where external data on this item can be found
10. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt/p): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

No other items found

[Assistant]
The property "official religion" (wdt:P3075) is the main property related to religion for Israel. There is no direct property indicating the predominant religion by population in the entity Israel.

I will try another approach: check if there is a statement or qualifier related to the population or majority religion in Israel. I will look for statements about Israel with the property "religion" (P140) or related to population (P1082) and see if there is any qualifier or statement indicating the predominant religion.

[Tool] Got no rows and 3 columns

[Tool]
Got 1 row and 3 columns:
| subject          | property               | object                |
| ---------------- | ---------------------- | --------------------- |
| Israel (wd:Q801) | population (wdt:P1082) | 9840000 (xsd:decimal) |

[Assistant]
There is no direct statement about religion (P140) for Israel, but there is a population statement (P1082).

Since the official religion property (P3075) lists multiple religions, I will check if there is a statement about the majority religion or predominant religion in Israel by searching for the property "majority religion" or similar. I will search for properties related to "majority religion" or "predominant religion."

[Tool]
Top 10 property alternatives:
1. official religion, also known as established religion, state religion (wd:P3075 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): official religion in this administrative entity
2. religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): religion of a person, organization or religious building, or associated with this subject
3. located in the religious territorial entity, also known as Deanery, Vicariate, religious territorial entity, Parish, located in the ecclesiastical territorial entity (wd:P5607 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): the item is located on the territory of the following religious entity. Use P708 (diocese) for dioceses, location, part of
4. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
5. denomination (wd:P12949 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): value of a currency or type of currency
6. majority opinion by (wd:P5826 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): judicial opinion agreed to by more than half of the members of a court
7. religious name, also known as baptismal name, monastic name, name in religion (wd:P1635 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): name taken or used as a member of a religious community
8. demographics of topic, also known as demography of topic (wd:P9241 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): item that deals with demographics of the subject
9. population, also known as inhabitants, human population (wd:P1082 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): number of people inhabiting the place; number of people of subject
10. political ideology, also known as editorial viewpoint, has political ideology, ideology, official ideology, official political ideology (wd:P1142 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): political ideology of an organization or person or of a work (such as a newspaper)

[Assistant]
There is no specific property for "majority religion" or "predominant religion" other than the official religion property (wdt:P3075).

Given this, the best approach is to return the official religions listed for Israel, which include Judaism, Islam, Christianity, and Druzism. Among these, Judaism is widely known as the predominant religion in Israel.

I will provide a query that returns the official religions of Israel and mention in the answer that Judaism is the predominant religion.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the official religions of Israel but does not directly answer the question about the predominant religion. The query should be refined to identify the predominant religion, which is typically the religion with the largest number of adherents or the most significant cultural presence. Since Wikidata does not have a direct property for 'predominant religion,' a better approach might be to query for the religion with the largest population or majority status in Israel. Alternatively, the answer can be explicitly stated based on common knowledge that Judaism is predominant, but the query should reflect this by linking Israel to the religion with the largest population or majority. Therefore, the current output is sensible but needs refinement to better address the user's question.

[Assistant]
Thank you for the feedback. Since Wikidata does not have a direct property for "predominant religion," I will try to find data on the religious demographics of Israel that might indicate the majority religion by population.

I will look for statements or qualifiers related to religion and population or majority status in Israel. One approach is to check if there is a statement about the religious composition or majority religion in Israel using qualifiers or references.

I will search for statements about Israel with the property "religion" (P140) or related to population (P1082) and see if there is any qualifier or statement indicating the predominant religion by population or majority.

[Tool] Got no rows and 3 columns

[Assistant]
There are no direct statements about religion (P140) for Israel. I will now try to find if there is a statement about the religious composition or majority religion in Israel using the property "demographics of topic" (P9241) which might link to a topic about religious demographics.

I will check if Israel has a statement with property P9241.

[Tool]
Got 1 row and 3 columns:
| subject          | property                          | object                              |
| ---------------- | --------------------------------- | ----------------------------------- |
| Israel (wd:Q801) | demographics of topic (wdt:P9241) | demographics of Israel (wd:Q968767) |

[Assistant] Israel has a statement with the property "demographics of topic" (P9241) linking to "demographics of Israel" (wd:Q968767). I will now check if the demographics of Israel entity has information about religion or religious composition.

[Tool] Got no rows and 3 columns

[Tool]
Got 1 row and 3 columns:
| subject                             | property               | object                                        |
| ----------------------------------- | ---------------------- | --------------------------------------------- |
| demographics of Israel (wd:Q968767) | subclass of (wdt:P279) | demographics of the Middle East (wd:Q5256114) |

[Tool]
Got 184 rows and 3 columns, showing the first 10 rows below:
| subject                             | property                         | object                                                                                |
| ----------------------------------- | -------------------------------- | ------------------------------------------------------------------------------------------------ |
| demographics of Israel (wd:Q968767) | instance of (wdt:P31)            | demographics of country or region (wd:Q23983664)                                                 |
| demographics of Israel (wd:Q968767) | country (wdt:P17)                | Israel (wd:Q801)                                                                                |
| demographics of Israel (wd:Q968767) | Commons category (wdt:P373)      | Demographics of Israel                                                                           |
| demographics of Israel (wd:Q968767) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Population%20of%20Israel%20since%201949.svg> |
| demographics of Israel (wd:Q968767) | subclass of (wdt:P279)           | demographics of the Middle East (wd:Q5256114)                                                    |
| demographics of Israel (wd:Q968767) | location (wdt:P276)              | Israel (wd:Q801)                                                                                |
| demographics of Israel (wd:Q968767) | population (wdt:P1082)           | 9463500 (xsd:decimal)                                                                            |
| demographics of Israel (wd:Q968767) | different from (wdt:P1889)       | demographics of the State of Palestine (wd:Q5256116)                                             |
| demographics of Israel (wd:Q968767) | topic's main category (wdt:P910) | wd:Q6909257                                                                                |
| demographics of Israel (wd:Q968767) | facet of (wdt:P1269)             | Israelis (wd:Q875556)                                                                            |
| ...                                 | ...                              | ...                                                                                |

[Assistant]
The entity "demographics of Israel" (wd:Q968767) has many statements but none directly about religion (P140). I will now check if there are any statements about religious groups or population groups within this demographics entity.

I will search for statements with the property "has part" (P527) or similar that might list religious groups or population groups within the demographics of Israel.

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Assistant]
There is no direct data on the predominant religion in Israel in the demographics entity or linked statements.

Given the limitations in the data, the best approach is to rely on the official religion property (wdt:P3075) for Israel and state that Judaism is the predominant religion based on common knowledge, as the data does not provide a direct property or qualifier for the predominant religion by population.

I will finalize the answer accordingly.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the official religions of Israel but does not directly answer the question about the predominant religion. The query uses the property for official religions (wdt:P3075), which lists all official religions but does not indicate which one is predominant by population. The answer text correctly states that Judaism is the predominant religion, but this is based on general knowledge rather than the query result. To improve, the system should clarify that Wikidata does not have a direct property for predominant religion by population and that the answer is based on common knowledge. Alternatively, the system could attempt to find population statistics related to religions in Israel if available, but this might be complex. The current output is sensible but needs refinement to better align the query results with the user's question and to explicitly state the limitation of the data source.

[Assistant]
Thank you for the detailed feedback. I understand that the SPARQL query should better reflect the data available in Wikidata and explicitly clarify the limitations regarding the predominant religion by population.

Since Wikidata does not have a direct property for the predominant religion by population in Israel, I will provide a refined answer that:
1. Returns the official religions of Israel using the property wdt:P3075.
2. Explicitly states that Wikidata does not have a direct property for the predominant religion by population.
3. Clarifies that based on common knowledge, Judaism is the predominant religion in Israel.

I will now finalize the answer with this clarification.

[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 ?location ?locationLabel WHERE {
  wd:Q55464116 wdt:P159 ?location .
  OPTIONAL {
    ?location rdfs:label ?locationLabel FILTER ( LANG( ?locationLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| location                | locationLabel     |
| ----------------------- | ----------------- |
| Indianapolis (wd:Q6346) | Indianapolis (en) |

The National FFA Foundation is located in Indianapolis.

[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

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 is the national ffa foundation located today?

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

[Tool]
Example 1:
Question:
where is the mtv headquarters?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q43359 wdt:P159 ?x .
}

Using entities:
MTV, also known as Music Television, Music television, MTV HD (wd:Q43359): American cable television channel

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place

Example 2:
Question:
where is the pepsi center?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q795470 wdt:P131 ?x .
}

Using entities:
Ball Arena, also known as Denver Debacle, Pepsi Center, The Can, The Denver Debacle (wd:Q795470): indoor arena in Denver, Colorado, USA

Using properties:
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): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of

Example 3:
Question:
what city and state was the air force academy established?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1331280 wdt:P159 ?x .
}

Using entities:
United States Air Force Academy, also known as Air Force Academy, USAFA (wd:Q1331280): military academy near Colorado Springs, Colorado, USA

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place

[Assistant]
From the examples, it seems the property "headquarters location" (wdt:P159) is commonly used to find the location of an organization's headquarters.

Next, I will search for the entity "National FFA Foundation" in Wikidata to find its identifier.

[Tool]
Top 10 entity alternatives:
1. National FFA Foundation (wd:Q55464116): https://www.ffa.org/support/foundation
2. 2017 National FFA Foundation Convention (wd:Q123701667)
3. 2017 National FFA Foundation Convention Opening Session (wd:Q123701666)
4. national foundation, also known as foundation of a country, foundation of a nation (wd:Q2324975): event or process, usually mythical or legendary, through which a nation is founded
5. National Science Foundation, also known as N.S.F., NSF, United States National Science Foundation, U.S. National Science Foundation, US National Science Foundation (wd:Q304878): United States government agency
6. National Foundation Day, also known as Kenkoku Kinen no Hi, National Foundation Day of Japan (wd:Q1059995): Japanese holiday to celebrate the foundation of Japan.
7. Gaecheonjeol, also known as National Foundation Day (wd:Q485634): public holiday in South Korea
8. National Bonsai Foundation (wd:Q3539656): nonprofit organization that was created to sustain the National Bonsai and Penjing Museum
9. Cuban American National Foundation, also known as CANF, Cuban-American National Foundation, FNCA (wd:Q391051)
10. National Research Foundation, also known as National Research Foundation, South Africa, nrf.ac.za, NRF, National Research Foundation of South Africa (wd:Q6978050): autonomous statutory body of South Africa

[Assistant]
The entity "National FFA Foundation" corresponds to wd:Q55464116 in Wikidata.

Now, I will query the headquarters location (wdt:P159) of the National FFA Foundation to find where it is located today.

[Tool]
Got 1 row and 2 columns:
| location                | locationLabel     |
| ----------------------- | ----------------- |
| Indianapolis (wd:Q6346) | Indianapolis (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the headquarters location (property P159) of the National FFA Foundation (wd:Q55464116) and returns both the identifier and the English label of the location. The answer 'Indianapolis' matches the query result and is accurate. The query follows the rules by returning the actual identifier and an optional label. No further refinement is needed.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?actor ?actorLabel WHERE {
  ?film p:P161 ?castStatement .
  ?castStatement ps:P161 ?actor ; pq:P453 wd:Q51746 .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel FILTER ( LANG( ?actorLabel ) = "en" )
  }
}
LIMIT 10

Got 3 rows and 2 columns:
| actor                       | actorLabel         |
| --------------------------- | ------------------ |
| Peter Shukoff (wd:Q1280173) | Peter Shukoff (en) |
| Mark Hamill (wd:Q210447)    | Mark Hamill (en)   |
| Seth Gamble (wd:Q3069394)   | Seth Gamble (en)   |

The actors who have played Luke Skywalker are Mark Hamill, Peter Shukoff, and Seth Gamble. Mark Hamill is the most well-known actor for this role.

[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

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 would play luke skywalker?

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

[Tool]
Example 1:
Question:
who play luke skywalker?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q51746 .
}

Using entities:
Luke Skywalker, also known as Luke Starkiller (wd:Q51746): fictional character from Star Wars, starship pilot, mechanic, rebel, Jedi

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as ps/p): 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 2:
Question:
who played luke skywalker in star wars episode 4?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q17738 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q51746 .
}

Using entities:
Star Wars: Episode IV – A New Hope, also known as 1977 Star Wars, A New Hope, Star Wars, Star Wars: A New Hope, Star Wars: Episode IV (wd:Q17738): 1977 film directed by George Lucas
Luke Skywalker, also known as Luke Starkiller (wd:Q51746): fictional character from Star Wars, starship pilot, mechanic, rebel, Jedi

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as ps/p): 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:
where does luke skywalker live in star wars?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q51746 wdt:P1165 ?x .
}

Using entities:
Luke Skywalker, also known as Luke Starkiller (wd:Q51746): fictional character from Star Wars, starship pilot, mechanic, rebel, Jedi

Using properties:
home world, also known as homeworld, home planet (wd:P1165 as wdt): home planet or natural satellite for a fictional character or species

[Assistant]
From the examples, the property "cast member" (P161) with the qualifier "character role" (P453) is used to find the actor who played a specific character. The entity for Luke Skywalker is wd:Q51746.

I will now write a SPARQL query to find the actor who played Luke Skywalker using these properties.

[Tool]
Got 3 rows and 2 columns:
| actor                       | actorLabel         |
| --------------------------- | ------------------ |
| Peter Shukoff (wd:Q1280173) | Peter Shukoff (en) |
| Mark Hamill (wd:Q210447)    | Mark Hamill (en)   |
| Seth Gamble (wd:Q3069394)   | Seth Gamble (en)   |

[Assistant]
The actors who have played Luke Skywalker according to the data are Mark Hamill, Peter Shukoff, and Seth Gamble. Mark Hamill is the most well-known actor for this role.

I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves actors who have played the character Luke Skywalker by using the property 'cast member' with the qualifier 'character role'. The query returns the IRIs and English labels of the actors, fulfilling the requirement to provide actual identifiers and human-readable names. The answer includes the well-known actor Mark Hamill as well as other actors who have portrayed the character, which is accurate and complete. No further refinement is necessary.


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 {
  ?country wdt:P37 wd:Q1321 ; wdt:P31 ?type .
  FILTER ( ?type IN ( wd:Q3624078 , wd:Q6256 ) ) FILTER NOT EXISTS {
    ?country wdt:P31 wd:Q3024240
  }
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = "en" )
  }
}

Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| country                     | countryLabel           |
| --------------------------- | ---------------------- |
| Cuba (wd:Q241)              | Cuba (en)              |
| Spain (wd:Q29)              | Spain (en)             |
| Chile (wd:Q298)             | Chile (en)             |
| Argentina (wd:Q414)         | Argentina (en)         |
| Peru (wd:Q419)              | Peru (en)              |
| ...                         | ...                    |
| Costa Rica (wd:Q800)        | Costa Rica (en)        |
| Panama (wd:Q804)            | Panama (en)            |
| Nicaragua (wd:Q811)         | Nicaragua (en)         |
| Mexico (wd:Q96)             | Mexico (en)            |
| Equatorial Guinea (wd:Q983) | Equatorial Guinea (en) |

The countries that have Spanish as their national (official) language are Cuba, Spain, Chile, Argentina, Peru, Costa Rica, Panama, Nicaragua, Mexico, Equatorial Guinea, and others. The query returned 20 recognized countries excluding historical countries.

[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

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 countries have spanish as the national language?

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

[Tool]
Example 1:
Question:
what countries has spanish as their official language?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q1321 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

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

Example 2:
Question:
what countries speak spanish wikipedia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q1321 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

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

Example 3:
Question:
what countries use english as national language?

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 similar examples, we see that the property "official language" (wdt:P37) is used to find countries that have a specific language as their official language. The entity for Spanish language is wd:Q1321. The entity for country is wd:Q6256.

I will now write a SPARQL query to find countries that have Spanish as their official language.

[Tool]
Got 27 rows and 2 columns, showing the first 5 and last 5 rows below:
| country                                                        | countryLabel                                          |
| -------------------------------------------------------------- | ----------------------------------------------------- |
| Tilandia Kingdom (wd:Q130337131)                               | Tilandia Kingdom (en)                                 |
| Kingdom of Patones (wd:Q131839713)                             | Kingdom of Patones (en)                               |
| Gay and Lesbian Kingdom of the Coral Sea Islands (wd:Q1423680) | Gay and Lesbian Kingdom of the Coral Sea Islands (en) |
| Republic of Cuba (wd:Q14905932)                                | Republic of Cuba (en)                                 |
| Cuba (wd:Q241)                                                 | Cuba (en)                                             |
| ...                                                            | ...                                                   |
| Costa Rica (wd:Q800)                                           | Costa Rica (en)                                       |
| Panama (wd:Q804)                                               | Panama (en)                                           |
| Nicaragua (wd:Q811)                                            | Nicaragua (en)                                        |
| Mexico (wd:Q96)                                                | Mexico (en)                                           |
| Equatorial Guinea (wd:Q983)                                    | Equatorial Guinea (en)                                |

[Assistant]
The query returned 27 entities that have Spanish as their official language, including some fictional or micronations like "Tilandia Kingdom" and "Kingdom of Patones," along with recognized countries such as Cuba, Costa Rica, Panama, Nicaragua, Mexico, and Equatorial Guinea.

I will refine the query to exclude entities that are not recognized sovereign countries. I will do this by adding a condition to only include entities that are instances of sovereign state (wd:Q3624078).

[Tool]
Got 21 rows and 2 columns, showing the first 5 and last 5 rows below:
| country                            | countryLabel            |
| ---------------------------------- | ----------------------- |
| Kingdom of Patones (wd:Q131839713) | Kingdom of Patones (en) |
| Cuba (wd:Q241)                     | Cuba (en)               |
| Spain (wd:Q29)                     | Spain (en)              |
| Chile (wd:Q298)                    | Chile (en)              |
| Argentina (wd:Q414)                | Argentina (en)          |
| ...                                | ...                     |
| Costa Rica (wd:Q800)               | Costa Rica (en)         |
| Panama (wd:Q804)                   | Panama (en)             |
| Nicaragua (wd:Q811)                | Nicaragua (en)          |
| Mexico (wd:Q96)                    | Mexico (en)             |
| Equatorial Guinea (wd:Q983)        | Equatorial Guinea (en)  |

[Assistant]
The refined query returned 21 entities that are instances of sovereign states and have Spanish as their official language. However, "Kingdom of Patones" is still included, which might not be a widely recognized sovereign state.

I will further refine the query to exclude entities that are not recognized as countries by adding a condition to check if the entity is a subclass of country (wd:Q6256) or is an instance of country. This should help filter out entities like "Kingdom of Patones."

[Tool]
Got 27 rows and 2 columns, showing the first 5 and last 5 rows below:
| country                                                        | countryLabel                                          |
| -------------------------------------------------------------- | ----------------------------------------------------- |
| Tilandia Kingdom (wd:Q130337131)                               | Tilandia Kingdom (en)                                 |
| Kingdom of Patones (wd:Q131839713)                             | Kingdom of Patones (en)                               |
| Gay and Lesbian Kingdom of the Coral Sea Islands (wd:Q1423680) | Gay and Lesbian Kingdom of the Coral Sea Islands (en) |
| Republic of Cuba (wd:Q14905932)                                | Republic of Cuba (en)                                 |
| Cuba (wd:Q241)                                                 | Cuba (en)                                             |
| ...                                                            | ...                                                   |
| Costa Rica (wd:Q800)                                           | Costa Rica (en)                                       |
| Panama (wd:Q804)                                               | Panama (en)                                           |
| Nicaragua (wd:Q811)                                            | Nicaragua (en)                                        |
| Mexico (wd:Q96)                                                | Mexico (en)                                           |
| Equatorial Guinea (wd:Q983)                                    | Equatorial Guinea (en)                                |

[Assistant]
The previous approach to filter by subclass or instance of country (wd:Q6256) brought back the same results including non-sovereign entities.

I will now try a different approach: I will filter for entities that are instances of sovereign state (wd:Q3624078) or country (wd:Q6256) to get recognized countries and sovereign states. This should exclude micronations and fictional entities.

[Tool]
Got 22 rows and 2 columns, showing the first 5 and last 5 rows below:
| country                            | countryLabel            |
| ---------------------------------- | ----------------------- |
| Kingdom of Patones (wd:Q131839713) | Kingdom of Patones (en) |
| Republic of Cuba (wd:Q14905932)    | Republic of Cuba (en)   |
| Cuba (wd:Q241)                     | Cuba (en)               |
| Spain (wd:Q29)                     | Spain (en)              |
| Chile (wd:Q298)                    | Chile (en)              |
| ...                                | ...                     |
| Costa Rica (wd:Q800)               | Costa Rica (en)         |
| Panama (wd:Q804)                   | Panama (en)             |
| Nicaragua (wd:Q811)                | Nicaragua (en)          |
| Mexico (wd:Q96)                    | Mexico (en)             |
| Equatorial Guinea (wd:Q983)        | Equatorial Guinea (en)  |

[Assistant]
The query still returns "Kingdom of Patones," which is not a widely recognized country. It seems that filtering by instance of sovereign state or country is not sufficient to exclude such entities.

I will now try to exclude entities that have a "fictional" or "micronation" classification by checking if they have an instance of or subclass of property pointing to such entities. But first, I will check the instance of "Kingdom of Patones" to understand its classification better.

[Tool]
Got 3 rows and 3 columns:
| subject                            | property              | object                           |
| ---------------------------------- | --------------------- | -------------------------------- |
| Kingdom of Patones (wd:Q131839713) | instance of (wdt:P31) | sovereign state (wd:Q3624078)    |
| Kingdom of Patones (wd:Q131839713) | instance of (wdt:P31) | microstate (wd:Q244381)          |
| Kingdom of Patones (wd:Q131839713) | instance of (wdt:P31) | historical country (wd:Q3024240) |

[Assistant]
The "Kingdom of Patones" is classified as a sovereign state (wd:Q3624078), microstate (wd:Q244381), and historical country (wd:Q3024240). It is a historical country, which might be why it appears in the results.

I will exclude historical countries (wd:Q3024240) from the results to filter out such entities.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| country                     | countryLabel           |
| --------------------------- | ---------------------- |
| Cuba (wd:Q241)              | Cuba (en)              |
| Spain (wd:Q29)              | Spain (en)             |
| Chile (wd:Q298)             | Chile (en)             |
| Argentina (wd:Q414)         | Argentina (en)         |
| Peru (wd:Q419)              | Peru (en)              |
| ...                         | ...                    |
| Costa Rica (wd:Q800)        | Costa Rica (en)        |
| Panama (wd:Q804)            | Panama (en)            |
| Nicaragua (wd:Q811)         | Nicaragua (en)         |
| Mexico (wd:Q96)             | Mexico (en)            |
| Equatorial Guinea (wd:Q983) | Equatorial Guinea (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves countries that have Spanish as an official language, filtering for sovereign states and countries while excluding historical countries. The answer lists relevant countries and matches the query results. The use of wdt:P37 for official language and filtering by instance of sovereign state or country is appropriate. The query also includes English labels for readability. Overall, the output is accurate, complete, and well-structured for the user's question.


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 ?position ?positionLabel WHERE {
  wd:Q193637 wdt:P413 ?position .
  OPTIONAL {
    ?position rdfs:label ?positionLabel FILTER ( LANG( ?positionLabel ) = "en" )
  }
}

Scottie Pippen was good at playing the position of small forward in basketball.

[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

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 scottie pippen good at?

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

[Tool]
Example 1:
Question:
what year did scottie pippen come into the nba?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q193637 p:P54 ?p .
  ?p ps:P54 ?y .
  ?y wdt:P118 wd:Q155223 .
  ?p pq:P580 ?x .
}
ORDER BY ?x
LIMIT 1

Using entities:
National Basketball Association, also known as Basketball Association of America, BAA, NBA, National Basketball Assn., Nat'l Basketball Assn. (wd:Q155223): North American professional men's basketball league
Scottie Pippen, also known as No Tippin' Pippen, Scotty Maurice Pippen, Scott Pippen, Robin, Pip (wd:Q193637): American basketball player, basketball player, actor

Using properties:
league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt): league or competition in which team or player has played, or in which an event occurs, participant in
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as ps/p): sports teams or clubs that the subject represents or represented, member of
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time

Example 2:
Question:
what position did john stockton play?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q213346 wdt:P413 ?x .
}

Using entities:
John Stockton, also known as Stock, John Houston Stockton (wd:Q213346): American basketball player, basketball player

Using properties:
position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as wdt): position or specialism of a player on a team

Example 3:
Question:
who did kevin garnett play for before celtics?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q189240 p:P54 ?p .
  ?p ps:P54 ?x ; pq:P582 ?y .
  wd:Q189240 p:P54 ?q .
  ?q ps:P54 wd:Q131371 ; pq:P580 ?z .
  FILTER ( ?y <= ?z )
}

Using entities:
Boston Celtics, also known as Celtics, Celts, C's, Green and White (wd:Q131371): NBA team based in Boston; tied with most NBA Championships
Kevin Garnett, also known as The Kid, The Big Ticket, KG, Kevin Maurice Garnett (wd:Q189240): American retired professional basketball player and actor, basketball player, actor

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as ps/p): sports teams or clubs that the subject represents or represented, member of
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time
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

[Assistant]
The examples show that questions about what a basketball player was good at or their skills might be answered by looking at their "position played" or "speciality" or other attributes related to their skills or roles.

Step 1: Identify the entity for Scottie Pippen.
Step 2: Identify properties related to skills, positions, or what he was good at.

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

[Tool]
Top 10 entity alternatives:
1. Scottie Pippen, also known as No Tippin' Pippen, Scotty Maurice Pippen, Scott Pippen, Robin, Pip (wd:Q193637): American basketball player, basketball player, actor
2. Scotty Pippen Jr., also known as Scottie Pippen Jr. (wd:Q100901254): American basketball player, basketball player
3. Slam City with Scottie Pippen (wd:Q3486520): 1994 video game
4. Scottish Terrier, also known as Aberdeen Terrier, Scottie, Scotty Dog (wd:Q39035): dog breed
5. 2024 in anime, also known as Scottie (wd:Q116673398): overview of anime-related events during the year of 2024
6. Pippen, also known as Pippen (surname), Pippen (family name) (wd:Q7197481): family name
7. pronunciation respelling for English, also known as Scottie (wd:Q7249972): non-IPA notation used to convey the pronunciation of English words (lookig like "lew-TEE-shee-əm")
8. Scottie (wd:Q7437589): album by Shirley Scott
9. English-language vowel changes before historic /r/, also known as Scottie (wd:Q5378157): vowel shifts
10. IBM Open Class, also known as scottie (wd:Q5968916): C++ class library

[Assistant] The entity for Scottie Pippen is wd:Q193637. Now, I will search for properties related to what Scottie Pippen was good at, such as skills, positions, or specialities. I will search properties of the entity Scottie Pippen with the query "good at" or "skill".

[Tool]
Top 10 property alternatives:
1. 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)
2. 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
3. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
4. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
5. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt/p): sports teams or clubs that the subject represents or represented, member of
6. 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)
7. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as wdt/p): position or specialism of a player on a team
8. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as wdt/p): country a person or a team represents when playing a sport, country
9. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
10. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception

No other items found

[Assistant] The property "position played on team / speciality" (wdt:P413) seems to be the most relevant to what Scottie Pippen was good at in basketball. I will query the value of this property for Scottie Pippen.

[Tool]
Got 1 row and 2 columns:
| position                   | positionLabel      |
| -------------------------- | ------------------ |
| small forward (wd:Q308879) | small forward (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer correctly identifies that Scottie Pippen was good at playing the position of small forward in basketball, which aligns with the property P413 (position played on team) used in the SPARQL query. The query is well-formed, retrieves the position identifier and its English label, and the result matches the expected information. No further refinement is necessary.


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 ?continent ?continentLabel WHERE {
  wd:Q16 wdt:P30 ?continent .
  OPTIONAL {
    ?continent rdfs:label ?continentLabel FILTER ( LANG( ?continentLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| continent              | continentLabel     |
| ---------------------- | ------------------ |
| North America (wd:Q49) | North America (en) |

Canada belongs to the continent North America.

[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

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 continent does canada belong to?

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

[Tool]
Example 1:
Question:
on what continent is canada found?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q16 wdt:P30 ?x .
}

Using entities:
Canada, also known as CA, CAN, Dominion of Canada, ISO 3166-1:CA (wd:Q16): country in North America

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature

Example 2:
Question:
what continent does the bahamas belong to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q778 wdt:P30 ?x .
}

Using entities:
The Bahamas, also known as BAH, Bahama Islands, Bahamas, bs, Commonwealth of the Bahamas (wd:Q778): island sovereign state in the West Indies

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature

Example 3:
Question:
what continent do the falkland islands belong to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9648 wdt:P30 ?x .
}

Using entities:
Falkland Islands, also known as 🇫🇰, Falklands, FK, FLK, Islas Malvinas (wd:Q9648): archipelago in the South Atlantic Ocean, and a British Overseas Territory, disputed by Argentina

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature

[Assistant] From the examples, the property for continent is wdt:P30 and the entity for Canada is wd:Q16. I will now write a SPARQL query to get the continent of Canada using this property and entity.

[Tool]
Got 1 row and 2 columns:
| continent              | continentLabel     |
| ---------------------- | ------------------ |
| North America (wd:Q49) | North America (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the continent of Canada using the property wdt:P30. The query returns the continent's identifier and its English label, which matches the user's question. The answer 'Canada belongs to the continent North America.' is accurate and complete. No further refinement is necessary.