PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?team ?teamLabel WHERE {
  wd:Q221048 wdt:P54 ?team .
  OPTIONAL {
    ?team rdfs:label ?teamLabel FILTER ( LANG( ?teamLabel ) = "en" )
  }
}

Jackie Robinson was on the baseball team Los Angeles Dodgers.

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

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

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

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

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

[User] what baseball team was jackie robinson on?

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

[Tool]
Example 1:
Question:
where is tommy emmanuel from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q310298 wdt:P19 ?x .
}

Using entities:
Tommy Emmanuel, also known as William Thomas Emmanuel (wd:Q310298): Australian guitarist, jazz guitarist, percussionist, jazz musician, songwriter, guitarist, composer, lecturer, singer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 2:
Question:
who was the president of indian national congress?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P39 wd:Q7241327 .
}

Using entities:
President of the Indian National Congress, also known as president of Indian National Congress (wd:Q7241327): head of INC

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

Example 3:
Question:
where did saki live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q311526 wdt:P19 ?x .
}

Using entities:
Saki, also known as H. H. Munro, Hector Hugh Munro (wd:Q311526): British writer, playwright, journalist, historian, novelist, writer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

[Assistant] The question is about the baseball team that Jackie Robinson was on. Jackie Robinson is a well-known historical figure in baseball, so I will first search for the entity "Jackie Robinson" in Wikidata to find his identifier. Then I will look for properties related to the baseball team or sports team he was associated with.

[Tool]
Top 10 entity alternatives:
1. Jackie Robinson, also known as Jack Roosevelt "Jackie" Robinson (wd:Q221048): American baseball player, athletics competitor, military officer, basketball coach, baseball player, vice president
2. Jackie Robinson, also known as Jack Robinson, Robert Lloyd Jackson Robinson (wd:Q731871): American basketball player (1927–2022), basketball player
3. Jackie Robinson (wd:Q1631748): American basketball player, basketball player
4. Jackie Robinson (wd:Q6116621): English footballer (1917–1972), association football player
5. Jackie Robinson, also known as Harry Hippy, Loren Jackson Robinson (wd:Q3805723): Jamaican musician, singer
6. Jackie Robinson (wd:Q25206446): 2016 film by Ken Burns
7. Jackie Robinson (wd:Q110043656): sketch from Saturday Night Live
8. Jackie Robinson (wd:Q100985462): college basketball player (1991–1993) South Carolina State, basketball player
9. Jackie Robinson (wd:Q112457903): 1944-
10. Jackie Robinson (wd:Q124413502): lecturer of marketing, academic, university teacher, researcher, academic

[Assistant] The most relevant entity for Jackie Robinson, the American baseball player, is wd:Q221048. Now I will search for properties related to the baseball team or sports team he was on. I will search for properties of this entity with a query related to "team" or "baseball team."

[Tool]
Top 10 property alternatives:
1. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
2. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as p/wdt): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
3. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team
4. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
5. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
6. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
7. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as p/wdt): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
8. sport, also known as play, plays, sport played, sports (wd:P641 as p/wdt): sport that the subject participates or participated in or is associated with
9. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant] The property "member of sports team" (wdt:P54) seems to be the most relevant for finding the baseball team Jackie Robinson was on. I will now query the team(s) Jackie Robinson was a member of using this property.

[Tool]
Got 1 row and 2 columns:
| team                             | teamLabel                |
| -------------------------------- | ------------------------ |
| Los Angeles Dodgers (wd:Q334634) | Los Angeles Dodgers (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the baseball team Jackie Robinson was a member of using the property 'member of sports team' (wdt:P54). The query returns the team's identifier and English label, which is appropriate and follows the guidelines. The answer 'Los Angeles Dodgers' is accurate and complete. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?party ?partyLabel WHERE {
  wd:Q91 wdt:P102 ?party .
  OPTIONAL {
    ?party rdfs:label ?partyLabel FILTER ( LANG( ?partyLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| party                            | partyLabel                |
| -------------------------------- | ------------------------- |
| Republican Party (wd:Q29468)     | Republican Party (en)     |
| Whig Party (wd:Q42183)           | Whig Party (en)           |
| National Union Party (wd:Q80719) | National Union Party (en) |

Abraham Lincoln was part of the Republican Party, the Whig Party, and the National Union Party.

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

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

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

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

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

[User] what party was abe lincoln part of?

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

[Tool]
Example 1:
Question:
what do people from guam speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q16635 wdt:P37 ?x .
}

Using entities:
Guam, also known as GU, 🇬🇺, US-GU, Territory of Guam, ISO 3166-1:GU (wd:Q16635): unincorporated territory of the United States of America

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 2:
Question:
where did the flemish live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q242485 wdt:P495 ?x .
}

Using entities:
Flemish people, also known as Flemings (wd:Q242485): Germanic ethnic group native to Flanders

Using properties:
country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country

Example 3:
Question:
where is canadian county oklahoma?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q486614 wdt:P131 ?x .
}

Using entities:
Canadian County, also known as Canadian County, OK, Canadian County, Oklahoma (wd:Q486614): county in Oklahoma, 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]
The question is "what party was abe lincoln part of?" We want to find the political party of Abraham Lincoln.

Step 1: Identify the entity for "Abe Lincoln." We should search for the entity "Abe Lincoln" or "Abraham Lincoln" in Wikidata.

Step 2: Identify the property that relates a person to their political party. Common properties for political party affiliation are "member of political party" (wdt:P102).

I will first search for the entity "Abe Lincoln" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer
2. Abe Lincoln, also known as Abram Lincoln (wd:Q4666410): American jazz trombonist (1907-2000), jazz musician
3. Abraham Lincoln, also known as Abe Lincoln (wd:Q4669012): named passenger train
4. Abe Lincoln (wd:Q49395851): mine in Santa Fe County, New Mexico, United States
5. Abe Lincoln (wd:Q63889409): musical character in the musical Abe
6. Abe Lincoln Mine (wd:Q49395856): mine in Lincoln County, Nevada, United States of America
7. Abe Lincoln Playground (wd:Q34631707)
8. Abe Lincoln Mountain (wd:Q49008420)
9. Abe Lincoln Mine (wd:Q49395859): mine in Colfax County, New Mexico, United States of America
10. Abe Lincoln Mine (wd:Q49395857): mine in Pershing County, Nevada, United States of America

[Assistant] The entity for the person "Abe Lincoln" is Abraham Lincoln (wd:Q91). Now I will search for the property that relates a person to their political party. I will search for properties related to "political party" or "party" for the entity Abraham Lincoln.

[Tool]
Top 10 property alternatives:
1. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as p/wdt): the political party of which a person is or has been a member or otherwise affiliated, member of
2. position held, also known as function, held position, holds position, job, office held (wd:P39 as p/wdt): subject currently or formerly holds the object position or public office
3. candidacy in election, also known as ran in election, running in election, election candidacy, candidate in election, candidate in (wd:P3602 as p/wdt): election where the subject is a candidate, participant in
4. NLA Trove people ID, also known as Trove people ID, Trove person ID, Trove party ID, Trove organization ID, Trove organisation ID (wd:P1315 as p/wdt): identifier for people or organizations per National Library of A...he older Libraries Australia identifier). Format: 5 to 7 digits.
5. Ballotpedia ID, also known as Ballotpedia article (wd:P2390 as p/wdt): title of corresponding article on the Ballotpedia encyclopedia of American politics
6. Political Graveyard politician ID, also known as Political Graveyard ID, Political Graveyard identifier, The Political Graveyard ID (wd:P8462 as p/wdt): identifier for a politician in the Political Graveyard database
7. Our Campaigns candidate ID, also known as OurCampaigns candidate ID (wd:P8445 as p/wdt): identifier of a candidate in the Our Campaigns political candidate database
8. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
9. Met Constituent ID, also known as Metropolitan Museum of Art constituent ID, Metropolitan Museum of Art constituent identifier, Met constituent identifier (wd:P10882 as p/wdt): identifier from the Metropolitan Museum of Art that describes pe... institutions, or entities attributed for the creation of a work
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The property "member of political party" (wdt:P102) is the relevant property to find the political party of Abraham Lincoln.

Now I will write a SPARQL query to get the political party of Abraham Lincoln (wd:Q91) using the property wdt:P102.

[Tool]
Got 3 rows and 2 columns:
| party                            | partyLabel                |
| -------------------------------- | ------------------------- |
| Republican Party (wd:Q29468)     | Republican Party (en)     |
| Whig Party (wd:Q42183)           | Whig Party (en)           |
| National Union Party (wd:Q80719) | National Union Party (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all political parties Abraham Lincoln was part of, returning their identifiers and English labels. The answer is complete and accurate, listing the Republican Party, Whig Party, and National Union Party as expected. The query follows best practices by including labels in an optional clause and uses the appropriate property (wdt:P102) for party membership. No improvements are necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?productOrService ?productOrServiceLabel WHERE {
  wd:Q95 wdt:P1056 ?productOrService .
  OPTIONAL {
    ?productOrService rdfs:label ?productOrServiceLabel FILTER ( LANG( ?productOrServiceLabel ) = "en" )
  }
}

Got 8 rows and 2 columns:
| productOrService               | productOrServiceLabel |
| ------------------------------ | --------------------- |
| Software tools (wd:Q111897729) | Software tools (en)   |
| Google Maps (wd:Q12013)        | Google Maps (en)      |
| Google Pay (wd:Q19834616)      | Google Pay (en)       |
| Google Ads (wd:Q271982)        | Google Ads (en)       |
| search engine (wd:Q4182287)    | search engine (en)    |
| Google Voice (wd:Q51712)       | Google Voice (en)     |
| Gmail (wd:Q9334)               | Gmail (en)            |
| Google Search (wd:Q9366)       | Google Search (en)    |

Google offers various products and services including Software tools, Google Maps, Google Pay, Google Ads, search engine, Google Voice, Gmail, and Google Search.

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

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

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

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

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

[User] what products and\/or services does google offer customers?

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

[Tool]
Example 1:
Question:
who is the owner of the philadelphia eagles?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q219714 wdt:P127 ?x .
}

Using entities:
Philadelphia Eagles, also known as The Birds, Eagles (wd:Q219714): National Football League franchise in Philadelphia, Pennsylvania

Using properties:
owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as wdt): owner of the subject

Example 2:
Question:
what countries does the mississippi river run through?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1497 wdt:P17 ?x .
}

Using entities:
Mississippi River, also known as Mississippi, The Mississippi (wd:Q1497): primary river of the largest drainage basin in the United States

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

Example 3:
Question:
what kind of government does spain have now?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29 wdt:P122 ?x .
}

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

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as wdt): subject's government

[Assistant] The examples show how to query for properties of an entity. In this case, we want to find the products and/or services offered by Google. We should first identify the entity for Google and then find relevant properties that describe the products or services it offers. Let's start by searching for the entity "Google" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Google, also known as google.com, Google LLC, Google, Inc., Google Inc., Big G (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc.
2. Google, also known as Big G, google.com, Google Inc., Google LLC, Google, Inc. (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc.
3. Google Search, also known as BackRub, goo.gle, Google, google.com, Google homepage (wd:Q9366): search engine by Google LLC
4. Alphabet Inc., also known as Alphabet, Alphabet company, Alphabet Inc, Alphabet, Inc, Alphabet, Inc. (wd:Q20800404): American multinational technology conglomerate
5. Google+, also known as G+, Google Plus (wd:Q356): social networking service
6. .google, also known as dot google (wd:Q20573262): top-level Internet domain
7. google, also known as to google, googling (wd:Q1156923): transitive verb, meaning to search for something using the Google search engine
8. Google Google (wd:Q123412777): Tamil song from Thuppakki movie
9. Archaeology & Language, also known as Google (wd:Q23301814): 1998 Pimlico edition
10. Google Canada, also known as Google, Google Kitchener-Waterloo, Google Waterloo (wd:Q30338099)

[Assistant] The entity for Google as an American multinational technology company is wd:Q95. Now, I will search for properties of this entity that might relate to products or services offered by Google.

[Tool]
Top 10 property alternatives:
1. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as p/wdt): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
2. official shop URL, also known as online store, shop, shop URL, store, store URL (wd:P10225 as p/wdt): official URL where the agent sells products/merchandise, official website
3. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
4. official app, also known as app, mobile app, official application, official mobile application (wd:P4290 as p/wdt): official app for this organization or other entity (a downloadable application for Android, iOS, etc.)
5. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as p/wdt): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
6. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
7. uses, also known as uses trope, used, using, wielded, wields (wd:P2283 as p/wdt): item or concept used by the subject or in the operation (see also instrument [P1303] and armament [P520])
8. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
9. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as p/wdt): official name of the subject in its official language(s), name
10. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant] The property "product, material, or service produced or provided" (wdt:P1056) seems to be the most relevant for finding products or services offered by Google. I will now query for the values of this property for the entity Google (wd:Q95).

[Tool]
Got 8 rows and 2 columns:
| productOrService               | productOrServiceLabel |
| ------------------------------ | --------------------- |
| Software tools (wd:Q111897729) | Software tools (en)   |
| Google Maps (wd:Q12013)        | Google Maps (en)      |
| Google Pay (wd:Q19834616)      | Google Pay (en)       |
| Google Ads (wd:Q271982)        | Google Ads (en)       |
| search engine (wd:Q4182287)    | search engine (en)    |
| Google Voice (wd:Q51712)       | Google Voice (en)     |
| Gmail (wd:Q9334)               | Gmail (en)            |
| Google Search (wd:Q9366)       | Google Search (en)    |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves products and services offered by Google using the property 'product, material, or service produced or provided' (wdt:P1056). The results include relevant and well-known Google products and services such as Google Maps, Google Pay, Google Ads, Gmail, and others. The query also includes English labels for readability, which is helpful. The answer is complete, accurate, and directly addresses the user's question. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?team ?teamLabel WHERE {
  wd:Q1374361 wdt:P54 ?team .
  OPTIONAL {
    ?team rdfs:label ?teamLabel FILTER ( LANG( ?teamLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| team                                   | teamLabel                     |
| -------------------------------------- | ----------------------------- |
| New York Giants (wd:Q190618)           | New York Giants (en)          |
| Texas Longhorns football (wd:Q7707821) | Texas Longhorns football (en) |

Tom Landry played for the New York Giants and the Texas Longhorns football team.

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

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

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

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

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

[User] who did tom landry play for?

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

[Tool]
Example 1:
Question:
what do most nigerians speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1033 wdt:P37 ?x .
}

Using entities:
Nigeria, also known as Federal Republic of Nigeria, FRN, Naija, NG, NGA (wd:Q1033): sovereign state in West Africa

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 2:
Question:
who is julia roberts married to 2012?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q40523 p:P26 ?p .
  ?p ps:P26 ?x ; pq:P580 ?y .
  FILTER ( ( ?y < "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?y >= "2012-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
Julia Roberts, also known as Julia Fiona Roberts (wd:Q40523): American actress (born 1967), television actor, film producer, voice actor, stage actor, film actor, actor, model

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/ps): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
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 3:
Question:
what did the scientist thomson discover?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P61 wd:Q47285 .
}

Using entities:
J. J. Thomson, also known as Sir Joseph Thomson, John Thompson, Sir Joseph John Thomson, Joseph John Thomson (wd:Q47285): British physicist (1856-1940), university teacher, mathematician, physicist

Using properties:
discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as wdt): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory

[Assistant]
The question is "Who did Tom Landry play for?" We want to find the sports teams or clubs for which Tom Landry played.

Step 1: Identify the entity "Tom Landry" in Wikidata.
Step 2: Identify the property that relates a person to the sports teams they played for. This could be something like "member of sports team" or "played for."

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

[Tool]
Top 10 entity alternatives:
1. Tom Landry, also known as Thomas Wade Landry (wd:Q1374361): American football coach and player (1924–2000), American football player, American football coach, aircraft pilot
2. Tom Landry (wd:Q108629583): statue in Arlington, United States of America - Robert Summers - 2001
3. Landry Tomb (wd:Q4856268): historic place
4. Tom Landry Strategy Football (wd:Q108536207)
5. Landry, Tom (1924-2000), football coach (wd:Q103866595): encyclopedia article
6. 75th US Colored Infantry: Landry, Tom (wd:Q107830161): file unit in the National Archives and Records Administration's holdings (NAID 170728667)
7. 84th US Colored Infantry: Landry, Tom (wd:Q107699626): file unit in the National Archives and Records Administration's holdings (NAID 107157520)
8. A personal tribute to Tom Landry (wd:Q93705732)
9. Art Garfunkel, also known as Arthur Ira Garfunkel, Arthur Ira "Art" Garfunkel, Tom, Arthur Garfunkel (wd:Q4039): American singer (born 1941), singer-songwriter, television actor, street artist, songwriter, teacher, singer, actor, poet
10. Tom, also known as Tom River (wd:Q216188): river in Khakassia, Kemerovo Oblast, and Tomsk Oblast, Russia

[Assistant] The entity "Tom Landry" is identified as wd:Q1374361, an American football coach and player. Now, I will search for properties related to the sports teams he played for. I will search for properties of this entity related to "play" or "team."

[Tool]
Top 10 property alternatives:
1. sport, also known as play, plays, sport played, sports (wd:P641 as p/wdt): sport that the subject participates or participated in or is associated with
2. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
3. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team
4. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
5. coach of sports team, also known as trainer of sports team, club manager of sports team, trainer of, team manager of sports team, team manager of (wd:P6087 as p/wdt): sports club or team for which this person is or was on-field manager or coach
6. Pro Football Reference player ID, also known as PFR player ID, Pro-Football-Reference.com player ID, Pro-Football-Reference.com player identifier, Pro Football Reference player identifier (wd:P3561 as p/wdt): identifier for American football players at Pro-Football-Reference.com
7. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as p/wdt): country a person or a team represents when playing a sport, country
8. SNAC ARK ID, also known as Ark ID, snac ark id, SNAC Ark ID, snaccooperative id, SNAC ID (misnomer) (wd:P3430 as p/wdt): identifier for items in the Social Networks and Archival Context system
9. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
10. NFL.com player ID (former scheme), also known as National Football League player ID, NFL.com ID (former scheme), NFL ID, NFL identifier (wd:P3539 as p): numeric identifier for American football players at NFL.com

No other items found

[Assistant]
The property "member of sports team" (wdt:P54) is the appropriate property for indicating the sports teams or clubs that Tom Landry played for.

Now I will write a SPARQL query to find the sports teams that Tom Landry (wd:Q1374361) played for using the property wdt:P54. I will also include the labels of the teams for better readability.

[Tool]
Got 2 rows and 2 columns:
| team                                   | teamLabel                     |
| -------------------------------------- | ----------------------------- |
| New York Giants (wd:Q190618)           | New York Giants (en)          |
| Texas Longhorns football (wd:Q7707821) | Texas Longhorns football (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the sports teams Tom Landry played for using the property 'member of sports team' (wdt:P54). The answer includes both the New York Giants and the Texas Longhorns football team, which matches the query results. The query also correctly includes English labels for readability. The output is accurate and complete for the user's question.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?currency ?currencyLabel WHERE {
  wd:Q1028 wdt:P38 ?currency .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

The currency you should take to Morocco is the Moroccan dirham.

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

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

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

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

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

[User] what currency should you take to morocco?

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

[Tool]
Example 1:
Question:
who did king tut married?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q12154 wdt:P26 ?x .
}

Using entities:
Tutankhamun, also known as Tutankhamen, Tutenkhamon, Tutenkhamen, Tutankhaten, King Tut (wd:Q12154): 14th century BCE (18th dynasty) Egyptian pharaoh, ruler

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

Example 2:
Question:
what does kenya moore do for a living?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q447710 wdt:P106 ?x .
}

Using entities:
Kenya Moore, also known as Kenya Summer Moore Daly, Kenya Moore Daly (wd:Q447710): American actress, model, author, and entrepreneur, beauty pageant contestant, television actor, film director, film producer, film actor, model

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

Example 3:
Question:
what was lebron james rookie year?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q36159 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
LeBron James, also known as LeBron Raymone James Sr., LeBron, The Chosen One, King James, LeBron Raymone James (wd:Q36159): American basketball player (born 1984), basketball player, television actor, screenwriter

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 p/ps): 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

[Assistant]
The question is about the currency used in Morocco. To answer this, I need to find the entity for Morocco and then find the property that relates to the currency used in that country.

Step 1: Search for the entity "Morocco" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Morocco, also known as ⵎⵓⵔⴰⴽⵓⵛ, Marocco, MAR, ma, Lmaġrib (wd:Q1028): sovereign state in North Africa
2. Morocco, also known as al-Maġrib, Kingdom of Morocco, ⵎⵓⵔⴰⴽⵓⵛ, Lmaġrib, ma (wd:Q1028): sovereign state in North Africa
3. Morocco (wd:Q577754): 1930 film by Josef von Sternberg and Henry Hathaway
4. Morocco, also known as Morocco, IN, Morocco, Indiana (wd:Q2374422): town in Indiana, United States
5. Morocco leather, also known as Levant, Morocco (wd:Q2118555): soft, pliable leather used for bookbinding, wallets, linings for luggage, gloves and shoes
6. Morocco at the 1960 Summer Olympics, also known as 1960 Summer Olympics, Morocco (wd:Q2149869): sporting event delegation
7. Exit Marrakech, also known as Morocco (wd:Q14949869): 2013 film by Caroline Link
8. Sharifian Empire, also known as Morocco (wd:Q12183875): historical name given to Morocco
9. blouza, also known as Morocco (wd:Q2907091): traditional dress of Morocco and Algeria, traditional dress of Algeria
10. Morocco titular see, also known as Marocco, Marruecos titular see, Morocco, Titular see of Marocco (wd:Q3708053): titular see

[Assistant] The entity for Morocco is wd:Q1028. Now I will search for the property related to currency for this entity.

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as p/wdt): currency used by item, uses
2. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as p/wdt): market value of all officially recognized final goods and services produced within a country in a given period of time
3. central bank (wd:P1304 as p/wdt): country's central bank
4. flag, also known as flag description (wd:P163 as p/wdt): subject's flag
5. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
6. VAT rate, also known as goods and services tax rate, GST, sales tax, taxation rate for sales, tax rate for sales (wd:P2855 as p/wdt): percentage value-added tax in this country or region. Do not use for sales tax. For specialised rates, use qualifiers
7. The New Yorker topic ID, also known as TNY ID, The NewYorker topic ID, New Yorker topic ID, NewYorker topic ID, newyorker.com (wd:P13317 as p/wdt): identifier of a topic on The New Yorker website
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
9. continent (wd:P30 as p/wdt): continent of which the subject is a part, located in/on physical feature
10. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity

No other items found

[Assistant] The property for currency used by a country is wdt:P38. Now I will write a SPARQL query to get the currency used in Morocco (wd:Q1028).

[Tool]
Got 1 row and 2 columns:
| currency                     | currencyLabel        |
| ---------------------------- | -------------------- |
| Moroccan dirham (wd:Q200192) | Moroccan dirham (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the currency used by Morocco (wd:Q1028) using the property wdt:P38. The query also optionally retrieves the English label of the currency. The result is accurate and matches the answer provided: Moroccan dirham. The query follows the rules by returning the identifier and label, and the answer is complete and correct. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?language ?languageLabel WHERE {
  wd:Q148 wdt:P37 ?language .
  FILTER ( ?language != wd:Q835866 ) OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| language                      | languageLabel         |
| ----------------------------- | --------------------- |
| Standard Chinese (wd:Q727694) | Standard Chinese (en) |
| Chinese (wd:Q7850)            | Chinese (en)          |

The primary official language of China is Standard Chinese. Chinese is also an official language, but Standard Chinese is the main one used.

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

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

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

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

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

[User] what is the primary language of china?

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

[Tool]
Example 1:
Question:
what year was michael jordan rookie year?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q41421 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
Michael Jordan, also known as His Airness, Air Jordan (wd:Q41421): American basketball player and businessman (born 1963), basketball player, baseball player, autobiographer, spokesperson, entrepreneur

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 p/ps): 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 kind of paintings did frida kahlo do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5588 wdt:P135 ?x .
}

Using entities:
Frida Kahlo, also known as Mrs. Diego Rivera, Magdalena Carmen Frieda Kahlo y Calderon, Magdalena Carmen Frida Kahlo y Calderón, Frida Kahlo Calderón, Magdalena Carmen Frida Kahlo y Calderon (wd:Q5588): Mexican painter (1907–1954), painter

Using properties:
movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as wdt): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.

Example 3:
Question:
what countries are in the andean region?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5456 wdt:P17 ?x .
}

Using entities:
Andes, also known as Andes mountain range, Andes mountains, Ecuadorian Andes (wd:Q5456): mountain range running along the western side of South America

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

[Assistant] The question is about the primary language of China. We need to identify the entity for China and the property that indicates the primary language spoken in a country. Let's first search for the entity "China" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia
2. porcelain, also known as china, fine china (wd:Q130693): ceramic material
3. China, also known as All under Heaven, Zhonghua, Cathay, Zhongguo, Tianxia (wd:Q29520): cultural region, ancient civilization, and nation in East Asia, ...in political situation and rarely refer to the Republic of China
4. China, also known as Sinae, Zhonghua, Zhongguo, Tianxia, Middle Kingdom (wd:Q29520): cultural region, ancient civilization, and nation in East Asia, ...in political situation and rarely refer to the Republic of China
5. 1125 China, also known as (1125) China, China (wd:Q136211): asteroid
6. China, also known as China, TX, China, Texas (wd:Q288864): city in Jefferson County, Texas, United States
7. China, also known as China, Maine, China, ME (wd:Q3447500): town in Kennebec County, Maine, United States
8. China (wd:Q932423): town in Ōshima district, Kagoshima prefecture, Japan
9. Tianxia, also known as All under Heaven, Tien Hsia, T'ien Hsia, Tien-hsia, T'ien-hsia (wd:Q955223): Chinese cultural, philosophical, and political concept
10. China (wd:Q942154): municipality in the Nuevo León, Mexico

[Assistant] The entity for the country China is wd:Q148 (People's Republic of China). Now, I will search for properties related to "primary language" or "official language" for this entity.

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as p/wdt): language designated as official by this item, language used
2. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as p/wdt): language widely used (spoken or written) in this place or at this event or organisation
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
5. culture, also known as archaeological culture, civilisation, civilization (wd:P2596 as p/wdt): human culture or people (or several cultures) associated with this item, part of
6. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as p/wdt): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
7. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
9. Libraries Australia ID, also known as CNLKIN, NLA Kinetica Service identifier, NLA (Australia) identifier, NLA (Australia) ID, Libraries Australia identifier (wd:P409 as p/wdt): identifier issued by the National Library of Australia (see also...F component. Format: 1-12 digits, removing leading zero-padding.
10. Unicode character, also known as emoji, emote, pictograph, Unicode symbol (wd:P487 as p/wdt): Unicode character representing the item (only if this is not a c...acter or a compatiblity character: in that case, use only P4213)

No other items found

[Assistant] The property "official language" (wdt:P37) is the most relevant property for the primary language of a country. I will now write a SPARQL query to get the official language of China (wd:Q148).

[Tool]
Got 3 rows and 2 columns:
| language                        | languageLabel           |
| ------------------------------- | ----------------------- |
| Standard Chinese (wd:Q727694)   | Standard Chinese (en)   |
| Chinese (wd:Q7850)              | Chinese (en)            |
| languages of China (wd:Q835866) | languages of China (en) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the official languages of China, including Standard Chinese and Chinese. However, the query also returns 'languages of China,' which is a broader category and not a specific language. The answer should clarify that Standard Chinese is the primary official language. To improve, the query could be refined to exclude broader categories and focus on the primary official language, or the answer should explicitly state that Standard Chinese is the primary language among the official languages returned.

[Assistant] Thank you for the feedback. To improve the answer, I will refine the query to exclude broader categories like "languages of China" and focus on the primary official language, which is Standard Chinese. I will filter out entities that represent broader categories and only keep specific languages.

[Tool]
Got 2 rows and 2 columns:
| language                      | languageLabel         |
| ----------------------------- | --------------------- |
| Standard Chinese (wd:Q727694) | Standard Chinese (en) |
| Chinese (wd:Q7850)            | Chinese (en)          |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the official languages of China (wd:Q148) using the property wdt:P37. It excludes the general item 'languages of China' (wd:Q835866) to avoid irrelevant results. The query returns both Standard Chinese and Chinese, which aligns with the answer that Standard Chinese is the primary official language. The answer clearly explains the distinction and is accurate. The query and answer follow the rules and provide a complete and correct response to the user's question.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?owner ?ownerLabel WHERE {
  wd:Q156578 wdt:P127 ?owner .
  OPTIONAL {
    ?owner rdfs:label ?ownerLabel FILTER ( LANG( ?ownerLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| owner                                               | ownerLabel                                 |
| --------------------------------------------------- | ------------------------------------------ |
| Hannoversche Beteiligungsgesellschaft (wd:Q1529289) | Hannoversche Beteiligungsgesellschaft (en) |
| Qatar Investment Authority (wd:Q1571175)            | Qatar Investment Authority (en)            |
| Porsche Automobil Holding SE (wd:Q2104551)          | Porsche Automobil Holding SE (en)          |

The owners of the Volkswagen car company (Volkswagen Group) are Hannoversche Beteiligungsgesellschaft, Qatar Investment Authority, and Porsche Automobil Holding SE.

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

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

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

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

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

[User] who owns volkswagen car company?

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

[Tool]
Example 1:
Question:
what county is plainfield il in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1012017 wdt:P131 ?x .
}

Using entities:
Plainfield, also known as Plainfield, IL, Plainfield, Illinois (wd:Q1012017): village in Illinois, 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 2:
Question:
what was the cause of death of michael jackson?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2831 wdt:P509 ?x .
}

Using entities:
Michael Jackson, also known as M.J., MJ, M. J., The King of Pop, King of Pop (wd:Q2831): American singer, songwriter, and dancer (1958–2009), singer-songwriter, recording artist, record producer, businessperson, philanthropist, music arranger, autobiographer, film director, choreographer, art collector, entrepreneur, screenwriter, voice actor, songwriter, film actor, composer, dancer, singer, actor, model, poet

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

Example 3:
Question:
what kind of government does italy have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q38 wdt:P122 ?x .
}

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

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as wdt): subject's government

[Assistant]
The question is about the ownership of the Volkswagen car company. We need to identify the entity for Volkswagen car company and then find the property related to ownership.

Step 1: Search for the entity "Volkswagen car company" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Volkswagen, also known as VW (wd:Q246): German automotive brand; manufacturing subsidiary of Volkswagen Group
2. Volkswagen Group, also known as Volkswagen, VOLKSWAGEN AG, Volkswagen Aktiengesellschaft, VOLKSWAGEN AKTIENGESELLSCHAFT, VW (wd:Q156578): German automotive manufacturing conglomerate
3. .volkswagen (wd:Q24033243): top-level domain
4. Volkswagen (wd:Q30256185): company in Verona, Italy
5. Volkswagen (wd:Q98823874): postcard by Louise Lawler (MET, 2014.679.3)
6. Volkswagen Beetle, also known as VW Bug, VW Beetle, Volkswagen Bug, Volkswagen Type 1 (wd:Q152946): compact car selling
7. Volkswagen Golf, also known as Volkswagen Caribe, Volkswagen Rabbit (wd:Q247): small family car manufactured by Volkswagen
8. Volkswagen Passat, also known as VW Passat (wd:Q216754): Car model series
9. Volkswagen Polo, also known as Volkswagen Derby (wd:Q247819): Series of automobiles manufactured by Volkswagen
10. Volkswagen Arena (wd:Q155603): football stadium in Wolfsburg, Germany

[Assistant]
There are two main relevant entities: "Volkswagen" (wd:Q246) which is a German automotive brand and a manufacturing subsidiary of Volkswagen Group, and "Volkswagen Group" (wd:Q156578) which is a German automotive manufacturing conglomerate. The question likely refers to the Volkswagen Group as the car company.

Step 2: Search for properties related to ownership for the entity "Volkswagen Group" (wd:Q156578).

[Tool]
Top 10 property alternatives:
1. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as p/wdt): owner of the subject
2. owner of, also known as owns, owns property, shareholder of (wd:P1830 as p/wdt): entities owned by the subject
3. has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as p/wdt): subsidiary of a company or organization; generally a fully owned...siness division" (P199). Opposite of parent organization (P749)., has part(s), owner of
4. parent organization, also known as parent company, parent institution, parent organisation, parent unit, part of (wd:P749 as p/wdt): parent organization of an organization, opposite of subsidiaries (P355), owned by, part of
5. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as p/wdt): founder or co-founder of this organization, religion, place or entity, creator
6. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
7. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
8. significant person, also known as significant people, sigper, sign. person, relevant person, relevant people (wd:P3342 as p/wdt): person linked to the item in any possible way
9. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
10. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as p/wdt): presiding member of an organization, group or body, director / manager, significant person

No other items found

[Assistant]
The property "owned by" (wdt:P127) is the relevant property to find the owner of the Volkswagen Group.

Step 3: Construct a SPARQL query to find the owner(s) of Volkswagen Group (wd:Q156578) using the property "owned by" (wdt:P127).

[Tool]
Got 3 rows and 2 columns:
| owner                                               | ownerLabel                                 |
| --------------------------------------------------- | ------------------------------------------ |
| Hannoversche Beteiligungsgesellschaft (wd:Q1529289) | Hannoversche Beteiligungsgesellschaft (en) |
| Qatar Investment Authority (wd:Q1571175)            | Qatar Investment Authority (en)            |
| Porsche Automobil Holding SE (wd:Q2104551)          | Porsche Automobil Holding SE (en)          |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the owners of the Volkswagen car company using the property 'owned by' (wdt:P127). The query returns the identifiers and English labels of the owners, which are Hannoversche Beteiligungsgesellschaft, Qatar Investment Authority, and Porsche Automobil Holding SE. The answer is accurate and complete based on the data from Wikidata. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?team ?teamLabel WHERE {
  wd:Q706908 wdt:P54 ?team .
  OPTIONAL {
    ?team rdfs:label ?teamLabel FILTER ( LANG( ?teamLabel ) = "en" )
  }
}

Got 5 rows and 2 columns:
| team                              | teamLabel                 |
| --------------------------------- | ------------------------- |
| New York Yankees (wd:Q213417)     | New York Yankees (en)     |
| Texas Rangers (wd:Q329816)        | Texas Rangers (en)        |
| Detroit Tigers (wd:Q650855)       | Detroit Tigers (en)       |
| Washington Nationals (wd:Q825838) | Washington Nationals (en) |
| Houston Astros (wd:Q848117)       | Houston Astros (en)       |

Iván Rodríguez, also known as Pudge Rodriguez, has played for the following teams: New York Yankees, Texas Rangers, Detroit Tigers, Washington Nationals, and Houston Astros.

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

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

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

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

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

[User] who has pudge rodriguez played for?

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

[Tool]
Example 1:
Question:
where is portuguese language spoken?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q5146 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
Portuguese, also known as Portuguese language, pt (wd:Q5146): Western Romance language of the Indo-European language family
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:
who did juan ponce de leon married?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q185974 wdt:P26 ?x .
}

Using entities:
Juan Ponce de León, also known as Ponce de Leon, Juan Ponce de Leon, Don Juan Ponce de León, Don Juan Ponce de Leon (wd:Q185974): Spanish explorer and conquistador, military personnel, conquistador, explorer

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

Example 3:
Question:
where is adam smith from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9381 wdt:P19 ?x .
}

Using entities:
Adam Smith (wd:Q9381): Scottish moral philosopher and political economist (1723–1790), university teacher, non-fiction writer, French moralist, philosopher, publisher, economist, writer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

[Assistant]
The question is "who has pudge rodriguez played for?" which refers to a person "Pudge Rodriguez" and the teams or organizations he has played for. This is likely related to a sports career, specifically baseball since Pudge Rodriguez is a well-known baseball player.

Step 1: Search for the entity "Pudge Rodriguez" in Wikidata to get the correct identifier.
Step 2: Identify the property that relates a player to the teams they have played for. This could be something like "member of sports team" or "team played for".
Step 3: Construct a SPARQL query to find the teams Pudge Rodriguez has played for.

I will start by searching for the entity "Pudge Rodriguez".

[Tool]
Top 10 entity alternatives:
1. Iván Rodríguez, also known as Pudge Rodríguez, Pudge Rodriguez, Pudge, Iván Rodríguez Torres, Ivan Rodriguez Torres (wd:Q706908): Puerto Rican Hall of Fame baseball player, baseball player
2. Ivan ‘Pudge' Rodríguez Field (wd:Q115284691): baseball field in Annandale, Virginia
3. Rodrigues, also known as Rodrigues Islands, Rodriguez, Rodriguez Island (wd:Q208668): Mauritian island
4. Sixto Rodriguez, also known as Rodriguez, Sixto Diaz Rodriguez, Sixto Díaz Rodríguez, Sixto Rodriquez, Sugar Man (wd:Q1894125): American musician (1942–2023), singer-songwriter, guitarist, musician
5. Rodriguez, also known as Municipality of Rodriguez, Montalban (wd:Q106825): municipality of the Philippines in the province of Rizal
6. David Valdes, also known as Rodríguez, Samuel Róbinson (wd:Q1358685): Venezuelan educator, philosopher and politician, philosopher, pedagogue, writer
7. Simón Rodríguez, also known as Samuel Róbinson, Rodríguez (wd:Q1358685): Venezuelan educator, philosopher and politician, philosopher, pedagogue, writer
8. 13760 Rodriguez, also known as (13760) Rodriguez, Rodriguez (wd:Q1090306): asteroid
9. Rodríguez (wd:Q1654058): family name
10. Rodríguez, also known as Rodriguez (wd:Q32453): small town in the San José Department of southern Uruguay

[Assistant]
The entity "Pudge Rodriguez" corresponds to Iván Rodríguez (wd:Q706908), a Puerto Rican Hall of Fame baseball player.

Next, I will search for properties related to teams or sports teams that Iván Rodríguez has played for. I will search for properties of the entity wd:Q706908 with a query related to "team" or "played for".

[Tool]
Top 10 property alternatives:
1. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
2. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team
3. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as p/wdt): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
4. sport, also known as play, plays, sport played, sports (wd:P641 as p/wdt): sport that the subject participates or participated in or is associated with
5. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
6. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
8. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
9. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
10. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country

No other items found

[Assistant]
The property "member of sports team" (wdt:P54) is the relevant property that indicates the sports teams or clubs that Iván Rodríguez has represented or played for.

Now I will construct a SPARQL query to find the teams Iván Rodríguez (wd:Q706908) has played for using the property wdt:P54. I will also include the labels of the teams for better readability.

[Tool]
Got 5 rows and 2 columns:
| team                              | teamLabel                 |
| --------------------------------- | ------------------------- |
| New York Yankees (wd:Q213417)     | New York Yankees (en)     |
| Texas Rangers (wd:Q329816)        | Texas Rangers (en)        |
| Detroit Tigers (wd:Q650855)       | Detroit Tigers (en)       |
| Washington Nationals (wd:Q825838) | Washington Nationals (en) |
| Houston Astros (wd:Q848117)       | Houston Astros (en)       |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all the sports teams that Iván Rodríguez (Pudge Rodriguez) has played for using the property wdt:P54 (member of sports team). The query also optionally retrieves the English labels of the teams, which is helpful for readability. The execution result matches the answer provided, listing the New York Yankees, Texas Rangers, Detroit Tigers, Washington Nationals, and Houston Astros. The query follows the rules by returning the actual identifiers and labels in an optional clause. Overall, the answer is accurate, complete, and well-supported by the query and results.