PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?disease ?diseaseLabel WHERE {
  wd:Q1345645 wdt:P1050 ?disease .
  OPTIONAL {
    ?disease rdfs:label ?diseaseLabel FILTER ( LANG( ?diseaseLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| disease                       | diseaseLabel            |
| ----------------------------- | ----------------------- |
| multiple sclerosis (wd:Q8277) | multiple sclerosis (en) |

Montel Williams has the disease multiple sclerosis.

[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 kind of disease does montel williams have?

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

[Tool]
Example 1:
Question:
what disease has jack osbourne got?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q724791 wdt:P1050 ?x .
}

Using entities:
Jack Osbourne, also known as Jack Joseph Osbourne (wd:Q724791): television presenter, television actor, British actor, film actor, actor

Using properties:
medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt): any state relevant to the health of an organism, including diseases and positive conditions

Example 2:
Question:
what disease michael jackson?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2831 wdt:P1050 ?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:
medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt): any state relevant to the health of an organism, including diseases and positive conditions

Example 3:
Question:
what blood disease does robin roberts have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2041541 wdt:P1050 ?x .
  ?x wdt:P1995 wd:Q103824 ; wdt:P31 wd:Q12136 .
}

Using entities:
hematology, also known as haematology (wd:Q103824): study of blood, the blood-forming organs, and blood diseases
disease, also known as ailments, sickness, other disease, medical disorder, MedicalCondition (wd:Q12136): abnormal condition negatively affecting organisms
Robin Roberts, also known as Robin René Roberts (wd:Q2041541): American television broadcaster, sports commentator, basketball player, news presenter, journalist

Using properties:
medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt): any state relevant to the health of an organism, including diseases and positive conditions
health specialty, also known as medical field, medical speciality, medical specialty (wd:P1995 as wdt): main specialty that diagnoses, prevent human illness, injury and other physical and mental impairments
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] From the similar examples, the property "medical condition" (wdt:P1050) is used to find the disease or medical condition a person has. Montel Williams is the person of interest here. I will first search for the entity Montel Williams in Wikidata to get his identifier. Then I will query his medical condition using the property wdt:P1050.

[Tool]
Top 10 entity alternatives:
1. Montel Williams, also known as Montel Brian Anthony Williams (wd:Q1345645): American television host and actor, television presenter, television producer, radio personality, television actor, military officer, journalist, politician, actor
2. The Montel Williams Show (wd:Q2412902): television series
3. Montel Williams MS Foundation (wd:Q30289093): nonprofit organization in New York, United States
4. Williams Racing, also known as Williams, Williams Grand Prix Engineering Limited, Williams F1 (wd:Q171337): European Formula One motor racing team and constructor
5. Williams, also known as Williams, AZ, Williams, Arizona (wd:Q79864): city in Coconino County, Arizona, United States
6. Williams, also known as Williams, CA, Williams, California (wd:Q2685585): city in Colusa County, California, United States
7. Williams, also known as Williams, IA, Williams, Iowa (wd:Q1012283): city in Hamilton County, Iowa, United States
8. Williams, also known as Williams, MN, Williams, Minnesota (wd:Q963315): city in Lake of the Woods County, Minnesota, United States
9. Williams College, also known as Williams (wd:Q49166): liberal arts college in Massachusetts
10. Williams, also known as Williams, SC, Williams, South Carolina (wd:Q2562748): town in Collation County, South Carolina, United States

[Assistant] Montel Williams is identified as wd:Q1345645 in Wikidata. Now I will query the medical condition (wdt:P1050) of Montel Williams.

[Tool]
Got 1 row and 2 columns:
| disease                       | diseaseLabel            |
| ----------------------------- | ----------------------- |
| multiple sclerosis (wd:Q8277) | multiple sclerosis (en) |

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?team ?startTime WHERE {
  wd:Q169452 p:P54 ?statement .
  ?statement ps:P54 ?team .
  ?team wdt:P118 wd:Q155223 .
  ?statement pq:P580 ?startTime .
}
ORDER BY ?startTime
LIMIT 1

Shaquille O'Neal came into the NBA in 1992, when he started playing for the Orlando Magic.

[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] when did shaq come into the nba?

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

[Tool]
Example 1:
Question:
what team did shaq play for first?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q169452 p:P54 ?p .
  ?p ps:P54 ?x ; pq:P580 ?y .
}
ORDER BY ?y
LIMIT 1

Using entities:
Shaquille O'Neal, also known as Shaquille O’Neal, Shaquille Rashaun O'Neal, Shaq O'Neal, Shaquille Rashaun O’Neal, Shaq (wd:Q169452): American basketball player, real estate entrepreneur, television producer, sports commentator, basketball player, businessperson, film producer, screenwriter, film actor, Thai boxer, podcaster, singer, rapper, actor

Using properties:
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 year lebron james came to the nba?

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

Example 3:
Question:
what year did dwayne wade came to the nba?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q31683 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
Dwyane Wade, also known as WOW (Way of Wade), Pookie, Dwyane Tyrone Wade, Jr., Flash, Father Prime (wd:Q31683): American basketball player, sports commentator, basketball player

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]
From the examples, it seems that the property "member of sports team" (wdt:P54) with qualifier "start time" (pq:P580) can be used to find when a player started playing for a team. Also, the team should be in the NBA (wd:Q155223).

I will now search for the entity Shaquille O'Neal to confirm his Wikidata ID.

[Tool]
Top 10 entity alternatives:
1. Shaquille O'Neal, also known as Shaquille O’Neal, Shaquille Rashaun O'Neal, Shaq O'Neal, Shaquille Rashaun O’Neal, Shaq (wd:Q169452): American basketball player, real estate entrepreneur, television producer, sports commentator, basketball player, businessperson, film producer, screenwriter, film actor, Thai boxer, podcaster, singer, rapper, actor
2. Shaquille O'Neal (wd:Q125446160): episode of All That (S5 E3)
3. Shaquille Cleare, also known as Shaquille O'Neal Cleare (wd:Q61953486): college basketball player (2013–2017) Maryland; Texas, basketball player
4. Shaquille O'Neal Motors (wd:Q114535400): episode of Fresh Off the Boat (S2 E3)
5. Shaq Belson, also known as Shaquille Belson, Shaquille O'Neal Belson (wd:Q106725566): American American football player, American football player
6. Shaquille Allen, also known as Shaquille O'Neal Allen (wd:Q106725550): American football player
7. Upload with Shaquille O'Neal (wd:Q7898386): American comedy television series
8. Statue of Shaquille O'Neal (wd:Q114363921): sculpture in Los Angeles, California, U.S
9. The Best of Shaquille O'Neal (wd:Q7717219): album by Shaquille O'Neal
10. A Message from Shaquille O'Neal (wd:Q110058550): sketch from Saturday Night Live

[Assistant] The entity for Shaquille O'Neal is wd:Q169452. Now I will search for the property related to the start time or joining time for sports teams for this entity.

[Tool]
Top 10 property alternatives:
1. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as p/wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
2. work period (end), also known as floruit end, floruit (end of work), flourished (end), retirement, work ends (wd:P2032 as p/wdt): end of period during which a person or group flourished (fl. = "floruit") in their professional activity, end time, floruit
3. 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
4. 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
5. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as p/wdt): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
6. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as p/wdt): league or competition in which team or player has played, or in which an event occurs, participant in
7. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as p/wdt): the place where the person is or has been, resident, location
8. 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
9. Last.fm ID, also known as Lastfm ID, Last FM ID, LastFM music ID (wd:P3192 as p/wdt): identifier for an artist, group or work, on Last.fm
10. 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

No other items found

[Assistant] The property "start time" (wdt:P580) is not directly listed here, but from the examples, it is used as a qualifier for the property "member of sports team" (wdt:P54). I will now check the statements for Shaquille O'Neal with the property "member of sports team" to see if there is a start time qualifier.

[Tool]
Got 7 rows and 3 columns:
| subject                       | property                        | object                                    |
| ----------------------------- | ------------------------------- | ----------------------------------------- |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Los Angeles Lakers (wd:Q121783)           |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Boston Celtics (wd:Q131371)               |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Cleveland Cavaliers (wd:Q162990)          |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Phoenix Suns (wd:Q164177)                 |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Orlando Magic (wd:Q161337)                |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Miami Heat (wd:Q169138)                   |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | LSU Tigers men's basketball (wd:Q6460027) |

[Assistant] Shaquille O'Neal was a member of several sports teams. To find when he came into the NBA, I need to find the start time qualifier for the first NBA team he played for. I will now query the statements for the property "member of sports team" with qualifiers to get the start time for each team.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant] The SERVICE wikibase:label is not supported by the used endpoint. I will remove it and just return the team IRIs and start times.

[Tool]
Got 1 row and 2 columns:
| team                       | startTime                           |
| -------------------------- | ----------------------------------- |
| Orlando Magic (wd:Q161337) | 1992-06-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


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

Benjamin Franklin married Deborah Read Franklin.

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

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

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

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

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

[User] who did ben franklin marry?

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

[Tool]
Example 1:
Question:
where was ben franklin born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q34969 wdt:P19 ?x .
}

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

Using properties:
place of 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:
where did benjamin franklin died?

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

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

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

Example 3:
Question:
what jobs did ben franklin do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q34969 wdt:P106 ?x .
}

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

Using properties:
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)

[Assistant]
From the examples, we see that Benjamin Franklin is represented by the entity wd:Q34969 in Wikidata. To find who he married, we need to find the property related to marriage or spouse. The common property for spouse in Wikidata is wdt:P26.

I will now write a SPARQL query to find the spouse of Benjamin Franklin (wd:Q34969).

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

[Tool] Stopped generation process


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

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) |

Chinese people write in Standard Chinese, which is one of the official languages of China.

[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 language do chinese people write in?

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

[Tool]
Example 1:
Question:
what language do chinese?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P37 ?x .
}

Using entities:
People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia

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

Example 2:
Question:
what kind of language do they speak in china?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P37 ?x .
}

Using entities:
People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia

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

Example 3:
Question:
what kind of language do china speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P37 ?x .
}

Using entities:
People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia

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

[Assistant]
The similar examples indicate that the property "official language" (wdt:P37) of the entity "People's Republic of China" (wd:Q148) is used to find the languages spoken or written by Chinese people. Since the question is about the language Chinese people write in, we can use the same approach to find the official languages of China, which would include the written languages used by Chinese people.

I will now write a SPARQL query to get the official languages of China.

[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) |

[Assistant]
Chinese people write in the language "Standard Chinese," which is an official language of China. The query also returned "Chinese" and "languages of China," but the most specific and relevant language for writing is "Standard Chinese."

I will now provide the final answer.

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT DISTINCT ?owner ?ownerLabel WHERE {
  wd:Q29610 p:P127 ?statement .
  ?statement ps:P127 ?owner .
  OPTIONAL {
    ?statement pq:P580 ?startTime .
  }
  OPTIONAL {
    ?statement pq:P582 ?endTime .
  }
  FILTER ( ( ! BOUND( ?startTime ) || ?startTime <= "2011-12-31T23:59:59Z" ^^ xsd:dateTime ) && ( ! BOUND( ?endTime ) || ?endTime >= "2011-01-01T00:00:00Z" ^^ xsd:dateTime ) ) OPTIONAL {
    ?owner rdfs:label ?ownerLabel FILTER ( LANG( ?ownerLabel ) = "en" )
  }
}

There is no direct ownership statement for Chrysler Corporation specifically for the year 2011 in Wikidata. However, Chrysler Corporation was owned by Fiat Chrysler Automobiles from 2014 to 2021, and Stellantis North America from 2021 onwards. Fiat Chrysler Automobiles was owned by several entities including Exor, UBS, The Vanguard Group, and Tiger Management. Stellantis North America is a subsidiary of Stellantis, which is owned by Exor, Bpifrance, and Peugeot Invest.

[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 chrysler corporation 2011?

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

[Tool]
Example 1:
Question:
who owns chrysler corporation 2012?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29610 wdt:P127 ?x .
}

Using entities:
Chrysler, also known as Chrysler brand (wd:Q29610): US automotive brand

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

Example 2:
Question:
who owns nissan car manufacturer?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q20165 wdt:P112 ?x .
}

Using entities:
Nissan Motor Co. Ltd., also known as Nissan Motors, Nissan Motor Company Ltd, Nissan Motor Company, Nissan Motor Co., Ltd., NISSAN (wd:Q20165): Japanese company

Using properties:
founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt): founder or co-founder of this organization, religion, place or entity, creator

Example 3:
Question:
what car companies does ford motor company own?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q44294 wdt:P1830 ?x .
  ?x wdt:P31 wd:Q10429667 .
}

Using entities:
car brand, also known as automobile brand, automobile marque, badge, car marque, make of car (wd:Q10429667): brand or make of a car
Ford Motor Company, also known as FoMoCo, Ford Motors, Ford Motor Corporation, Ford Motor Co., Ford Motor (wd:Q44294): American multinational automotive company

Using properties:
owner of, also known as owns, owns property, shareholder of (wd:P1830 as wdt): entities owned by the subject
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
From the similar examples, we see that Chrysler Corporation is represented by wd:Q29610 in Wikidata. The property for ownership is "owned by" (wdt:P127). We want to find the owner of Chrysler Corporation in the year 2011.

Since ownership can change over time, we need to check if there is a qualifier for the point in time (P585) to specify the year 2011.

I will now construct a SPARQL query to find the owner of Chrysler Corporation with a qualifier for the year 2011.

[Tool] Got no rows and 2 columns

[Assistant]
The query returned no results, which means there might not be a direct ownership statement for Chrysler Corporation specifically qualified with the year 2011. Ownership might be represented differently or the year might not be directly qualified.

I will try a simpler query to just find the current or known owners of Chrysler Corporation without the time constraint to see if we get any results. Then we can investigate how to filter by year.

[Tool]
Got 1 row and 2 columns:
| owner                                 | ownerLabel                    |
| ------------------------------------- | ----------------------------- |
| Stellantis North America (wd:Q181114) | Stellantis North America (en) |

[Assistant]
The current owner of Chrysler Corporation is Stellantis North America (wd:Q181114). However, this is the current owner and may not reflect the ownership in 2011.

I will now check the statements about Chrysler Corporation's ownership (P127) with qualifiers to see if there is any statement with a time qualifier around 2011. This will help us identify how ownership was represented in that year.

[Tool]
Got 1 row and 3 columns:
| subject              | property            | object                                |
| -------------------- | ------------------- | ------------------------------------- |
| Chrysler (wd:Q29610) | owned by (wdt:P127) | Stellantis North America (wd:Q181114) |

[Tool]
Got 2 rows and 3 columns:
| subject              | property          | object                                        |
| -------------------- | ----------------- | --------------------------------------------- |
| Chrysler (wd:Q29610) | owned by (p:P127) | s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b |
| Chrysler (wd:Q29610) | owned by (p:P127) | s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 |

[Tool]
Got 7 rows and 3 columns:
| subject                                       | property              | object                                   |
| --------------------------------------------- | --------------------- | ---------------------------------------- |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | owned by (ps:P127)    | Fiat Chrysler Automobiles (wd:Q15678788) |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | start time (pq:P580)  | 2014-01-01T00:00:00Z (xsd:dateTime)      |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | end time (pq:P582)    | 2021-01-01T00:00:00Z (xsd:dateTime)      |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | wikibase:rank         | wikibase:NormalRank                      |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | rdf:type              | wikibase:Statement                       |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | start time (pqv:P580) | v:4755748741739c53456596b64165b84b       |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | end time (pqv:P582)   | v:068defc300d06ed22eb72f44c2fe8914       |

[Tool]
Got 7 rows and 3 columns:
| subject                                       | property              | object                                       |
| --------------------------------------------- | --------------------- | -------------------------------------------- |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | owned by (ps:P127)    | Stellantis North America (wd:Q181114)        |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | start time (pq:P580)  | 2021-01-01T00:00:00Z (xsd:dateTime)          |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | wikibase:rank         | wikibase:PreferredRank                       |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | rdf:type              | wikibase:BestRank                            |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | prov:wasDerivedFrom   | ref:ed0016ffcbc832c857c8124f34111ba7d4e9336d |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | start time (pqv:P580) | v:068defc300d06ed22eb72f44c2fe8914           |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | rdf:type              | wikibase:Statement                           |

[Assistant]
The ownership statements for Chrysler Corporation show two owners with time qualifiers:
- Fiat Chrysler Automobiles (wd:Q15678788) owned it from 2014 to 2021.
- Stellantis North America (wd:Q181114) owned it starting from 2021.

There is no direct ownership statement for the year 2011. I will now check if there is an owner before 2014 by querying ownership statements with start time before 2011 and end time after or no end time. This might give us the owner in 2011.

[Tool] Got no rows and 4 columns

[Assistant]
There are no ownership statements for Chrysler Corporation that cover the year 2011 directly in the data.

I will now try to find the owner of Chrysler Corporation in 2011 by searching for the owner of the predecessor company or the company that existed before Fiat Chrysler Automobiles took ownership in 2014.

I will search for the predecessor or earlier owners of Chrysler Corporation.

[Tool]
Got 1 row and 2 columns:
| owner                                 | ownerLabel                    |
| ------------------------------------- | ----------------------------- |
| Stellantis North America (wd:Q181114) | Stellantis North America (en) |

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool]
Top 10 entity alternatives:
1. Stellantis North America, also known as Chrysler Corporation, Chrysler LLC, FCA US (wd:Q181114): American automotive manufacturer
2. Chrysler Corporation v. United States (wd:Q19037103)
3. 2011 Chandigarh Municipal Corporation election (wd:Q110281392): local body election in India
4. Corporations (Fees) Amendment Act 2011 (wd:Q56757982): Act of the Parliament of Australia, currently registered as C2011A00144
5. Damodar Valley Corporation (Amendment) Act, 2011 (wd:Q92122081): Act of the Parliament of India
6. Chrysler Corporation's super-lite; an evaluation (wd:Q44500476): scientific article published in November 1969
7. Life Insurance Corporation (Amendment) Act, 2011 (wd:Q92118085): Act of the Parliament of India
8. Chrysler Corporation Loan Guarantee Act of 1979 (wd:Q131378741): United States federal statute
9. Corporations (Investigation and Management) Order 2011 (wd:Q101081466): New Zealand Statutory Regulation SR 2011/407
10. EVOLUTION in Chrysler Corporation's medical department (wd:Q78476671): scientific article published on 01 January 1959

[Assistant]
The entity Stellantis North America (wd:Q181114) is also known as Chrysler Corporation, Chrysler LLC, FCA US. This suggests that the entity representing Chrysler Corporation in Wikidata is updated to the current company name.

Since there is no direct ownership statement for 2011, it is likely that Chrysler Corporation was an independent or differently structured company at that time.

I will now check the history or predecessor of Stellantis North America to find the owner or structure of Chrysler Corporation in 2011.

[Tool]
Got 1 row and 3 columns:
| subject                               | property                       | object                    |
| ------------------------------------- | ------------------------------ | ------------------------- |
| Stellantis North America (wd:Q181114) | parent organization (wdt:P749) | Stellantis (wd:Q97439162) |

[Tool]
Got 1 row and 3 columns:
| subject                               | property              | object                                 |
| ------------------------------------- | --------------------- | -------------------------------------- |
| Stellantis North America (wd:Q181114) | founded by (wdt:P112) | Walter Percy Chrysler Sr. (wd:Q318044) |

[Tool]
Got 1 row and 3 columns:
| subject                               | property                       | object                    |
| ------------------------------------- | ------------------------------ | ------------------------- |
| Stellantis North America (wd:Q181114) | parent organization (wdt:P749) | Stellantis (wd:Q97439162) |

[Tool] Got no rows and 3 columns

[Tool]
Got 3 rows and 3 columns:
| subject                   | property            | object                       |
| ------------------------- | ------------------- | ---------------------------- |
| Stellantis (wd:Q97439162) | owned by (wdt:P127) | Exor (wd:Q1384140)           |
| Stellantis (wd:Q97439162) | owned by (wdt:P127) | Bpifrance (wd:Q2362964)      |
| Stellantis (wd:Q97439162) | owned by (wdt:P127) | Peugeot Invest (wd:Q3488278) |

[Assistant]
Stellantis North America, which is also known as Chrysler Corporation, is a subsidiary of Stellantis (wd:Q97439162). Stellantis is owned by Exor (wd:Q1384140), Bpifrance (wd:Q2362964), and Peugeot Invest (wd:Q3488278).

Since Stellantis was formed in 2021, I will now check the owner of Chrysler Corporation before 2014, which was Fiat Chrysler Automobiles (wd:Q15678788). I will check the owner of Fiat Chrysler Automobiles in 2011.

[Tool]
Got 4 rows and 3 columns:
| subject                                  | property            | object                          |
| ---------------------------------------- | ------------------- | ------------------------------- |
| Fiat Chrysler Automobiles (wd:Q15678788) | owned by (wdt:P127) | UBS (wd:Q193199)                |
| Fiat Chrysler Automobiles (wd:Q15678788) | owned by (wdt:P127) | The Vanguard Group (wd:Q849363) |
| Fiat Chrysler Automobiles (wd:Q15678788) | owned by (wdt:P127) | Exor (wd:Q1384140)              |
| Fiat Chrysler Automobiles (wd:Q15678788) | owned by (wdt:P127) | Tiger Management (wd:Q7801440)  |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?occupation ?occupationLabel WHERE {
  wd:Q302 wdt:P106 ?occupation .
  OPTIONAL {
    ?occupation rdfs:label ?occupationLabel FILTER ( LANG( ?occupationLabel ) = "en" )
  }
}

Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| occupation                      | occupationLabel       |
| ------------------------------- | --------------------- |
| rabbi (wd:Q133485)              | rabbi (en)            |
| thaumaturge (wd:Q1349880)       | thaumaturge (en)      |
| carpenter (wd:Q154549)          | carpenter (en)        |
| religious leader (wd:Q15995642) | religious leader (en) |
| father of faith (wd:Q2142783)   | father of faith (en)  |
| ...                             | ...                   |
| teacher (wd:Q37226)             | teacher (en)          |
| prophet (wd:Q42857)             | prophet (en)          |
| preacher (wd:Q432386)           | preacher (en)         |
| Messiah (wd:Q51626)             | Messiah (en)          |
| tektōn (wd:Q7695510)            | tektōn (en)           |

Jesus had multiple occupations including rabbi, thaumaturge, carpenter, religious leader, father of faith, teacher, prophet, preacher, Messiah, and tektōn.

[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 did jesus do for living?

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

[Tool]
Example 1:
Question:
what did st. matthew do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q43600 wdt:P106 ?x .
}

Using entities:
Matthew the Apostle, also known as Saint Matthew, Matthew the Evangelist, Matthew (wd:Q43600): Christian evangelist and apostle, tax collector, presbyter, publican

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 2:
Question:
what did martin luther do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9554 wdt:P106 ?x .
}

Using entities:
Martin Luther (wd:Q9554): German priest and theologian (1483–1546), Protestant reformer, Bible translator, Catholic priest, philosopher, translator, hymnwriter, reformator, theologian, professor, preacher, composer, scribe, lawyer, writer, pastor

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:
where was jesus born and raised?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q302 wdt:P19 ?x .
}

Using entities:
Jesus, also known as The Messiah, Son of Man, The Saviour, Lord of Lords, Saviour of the world (wd:Q302): central figure of Christianity (6 or 4 BC – AD 30 or 33), religious leader, father of faith, thaumaturge, carpenter, preacher, Messiah, teacher, prophet, pastor, healer, tektōn, rabbi

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] From the examples, it is clear that the property to find what someone did for a living is the occupation property (wdt:P106). The entity for Jesus is wd:Q302. I will now write a SPARQL query to find the occupations of Jesus.

[Tool]
Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| occupation                      | occupationLabel       |
| ------------------------------- | --------------------- |
| rabbi (wd:Q133485)              | rabbi (en)            |
| thaumaturge (wd:Q1349880)       | thaumaturge (en)      |
| carpenter (wd:Q154549)          | carpenter (en)        |
| religious leader (wd:Q15995642) | religious leader (en) |
| father of faith (wd:Q2142783)   | father of faith (en)  |
| ...                             | ...                   |
| teacher (wd:Q37226)             | teacher (en)          |
| prophet (wd:Q42857)             | prophet (en)          |
| preacher (wd:Q432386)           | preacher (en)         |
| Messiah (wd:Q51626)             | Messiah (en)          |
| tektōn (wd:Q7695510)            | tektōn (en)           |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?venue ?venueLabel WHERE {
  wd:Q599903 wdt:P115 ?venue .
  OPTIONAL {
    ?venue rdfs:label ?venueLabel FILTER ( LANG( ?venueLabel ) = "en" )
  }
}

Ireland plays rugby union at the Aviva Stadium.

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

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

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

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

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

[User] where do ireland play rugby union?

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

[Tool]
Example 1:
Question:
where is ellis park rugby stadium?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q182081 wdt:P276 ?x .
}

Using entities:
Ellis Park Stadium, also known as Emirates Airline Park, Ellis Park, Coca-Cola Park (wd:Q182081): stadium in Johannesburg, South Africa

Using properties:
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as 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

Example 2:
Question:
where does the shannon river flow?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q7488940 wdt:P131 ?x .
}

Using entities:
Shannon River (wd:Q7488940): river in Western Australia, Australia

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of

Example 3:
Question:
who does northern ireland belong to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q26 wdt:P131 ?x .
}

Using entities:
Northern Ireland, also known as UKN, Tuaisceart Éireann, The Six Counties, The North, N. Ireland (wd:Q26): part of the United Kingdom situated on the island of Ireland

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 "where do Ireland play rugby union?" is asking about the location or stadium where the Ireland national rugby union team plays their home games.

From the similar examples, it seems that the property "location" (wdt:P276) is used to indicate the location of a stadium or venue. We need to find the entity for the Ireland national rugby union team and then find the location or stadium where they play.

Step 1: Search for the entity "Ireland national rugby union team" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Ireland rugby union team, also known as Ireland national rugby team, Ireland national rugby union team (wd:Q599903): Men’s rugby union team representing the island of Ireland
2. Ireland women's national rugby union team (wd:Q3589823): women’s rugby union team representing the island of Ireland
3. Ireland national rugby union sevens team, also known as Ireland national rugby sevens team, Ireland sevens rugby team (wd:Q7902223): national sevens rugby team
4. Ireland national under-20 rugby union team (wd:Q6068684): rugby team
5. Ireland national schoolboy rugby union team (wd:Q6068681): sports team
6. Ireland women's national rugby union sevens team, also known as Ireland women's national sevens team (wd:Q6068719): sevens national rugby team
7. History of the Ireland national rugby union team (wd:Q23808242)
8. national rugby union team (wd:Q58840819): rugby union team that represents a country in international competitions
9. England national rugby union team, also known as England rugby union team, England rugby team, England national rugby team, England Rugby (wd:Q378628): Men’s rugby union team representing England
10. France national rugby union team, also known as France national rugby team, France rugby team, France rugby union team (wd:Q518116): Men’s rugby union team representing France

[Assistant]
The entity "Ireland rugby union team" (wd:Q599903) corresponds to the Ireland national rugby union team.

Step 2: Now, let's find the property that indicates the stadium or location where this team plays. I will search for properties related to "play" or "home stadium" for this entity.

[Tool]
Top 10 property alternatives:
1. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as p/wdt): home stadium or venue of a sports team or applicable performing arts organization, location
2. 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
3. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as p/wdt): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
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. 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. ranking, also known as peak position, place, placing, position, rank (wd:P1352 as p/wdt): subject's ordinal position as qualitatively evaluated relative to other members of a group
7. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as p/wdt): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person
8. 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
9. nickname, also known as informal name, moniker, other name, othername, other_names (wd:P1449 as p/wdt): informal name (for a pseudonym use P742), name
10. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time

No other items found

[Assistant]
The property "home venue" (wdt:P115) is the most relevant property indicating the home stadium or venue of a sports team.

Step 3: Now, I will construct a SPARQL query to find the home venue of the Ireland rugby union team (wd:Q599903) using the property "home venue" (wdt:P115).

[Tool]
Got 1 row and 2 columns:
| venue                      | venueLabel         |
| -------------------------- | ------------------ |
| Aviva Stadium (wd:Q244402) | Aviva Stadium (en) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?team WHERE {
  wd:Q119562 wdt:P54 ?team .
}

Got 8 rows and 1 column:
| team                                                           |
| -------------------------------------------------------------- |
| Argentina national under-20 football team (wd:Q1187790)        |
| Club Atlético Independiente (wd:Q214978)                       |
| Argentina national under-23 football team (wd:Q2462207)        |
| Argentina national under-17 football team (wd:Q2902690)        |
| Manchester City F.C. (wd:Q50602)                               |
| FC Barcelona (wd:Q7156)                                        |
| Argentina men's national association football team (wd:Q79800) |
| Atlético de Madrid (wd:Q8701)                                  |

Sergio Agüero played for several teams including Club Atlético Independiente, Atlético de Madrid, Manchester City F.C., FC Barcelona, and various Argentina national teams.

[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 team did aguero play for?

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

[Tool]
Example 1:
Question:
what team does sergio aguero play for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q119562 wdt:P54 ?x .
}

Using entities:
Sergio Agüero, also known as Sergio Leonel Agüero del Castillo (wd:Q119562): Argentine association football player, association football player, online streamer, businessperson

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

Example 2:
Question:
what club did aguero play for before man city?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q119562 p:P54 ?p .
  ?p ps:P54 ?x ; pq:P582 ?y .
  ?x wdt:P31 wd:Q476028 .
  wd:Q1920 p:P54 ?q .
  ?q ps:P54 wd:Q50602 ; pq:P580 ?z .
  FILTER ( ?y <= ?z )
}

Using entities:
Sergio Agüero, also known as Sergio Leonel Agüero del Castillo (wd:Q119562): Argentine association football player, association football player, online streamer, businessperson
Samir Nasri (wd:Q1920): French footballer (born 1987), association football player
association football club, also known as association soccer club, F.C., FC, football club, soccer club (wd:Q476028): sports club devoted to association football (soccer)
Manchester City F.C., also known as The Sky Blues, City, The Citizens, The Blues, Sky Blues (wd:Q50602): association football club in Manchester, England

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
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
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 3:
Question:
what team did kaka play for in 2009?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q531814 p:P54 ?p .
  ?p ps:P54 ?x ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2010-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2009-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
Kaká, also known as Ricardo Kaká (wd:Q531814): Brazilian association football player, born 1982, association football player, diplomat, writer

Using properties:
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
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

[Assistant] From the examples, I see that "Sergio Agüero" is represented by the entity wd:Q119562 in Wikidata. The property for the team a player played for is "member of sports team" (wdt:P54). I will now query for the teams that Sergio Agüero played for using this property.

[Tool]
Got 8 rows and 2 columns:
| team                                                           | teamLabel                                               |
| -------------------------------------------------------------- | ------------------------------------------------------- |
| Argentina national under-20 football team (wd:Q1187790)        | Argentina national under-20 football team (en)          |
| Club Atlético Independiente (wd:Q214978)                       | Club Atlético Independiente (en)                        |
| Argentina national under-23 football team (wd:Q2462207)        | Argentina national under-23 football team (en)          |
| Argentina national under-17 football team (wd:Q2902690)        | Argentina national under-17 football team (en)          |
| Manchester City F.C. (wd:Q50602)                               | Manchester City F.C. (en)                               |
| FC Barcelona (wd:Q7156)                                        | FC Barcelona (en)                                       |
| Argentina men's national association football team (wd:Q79800) | Argentina men's national association football team (en) |
| Atlético de Madrid (wd:Q8701)                                  | Atlético de Madrid (en)                                 |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?language WHERE {
  wd:Q155 wdt:P37 ?language .
}

The official language of Brazil now is Portuguese.

[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 official language of brazil now?

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

[Tool]
Example 1:
Question:
what is the language spoken in brazil?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q155 wdt:P37 ?x .
}

Using entities:
Brazil, also known as br, Brasil, Federative Republic of Brazil (wd:Q155): country in South 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:
what language brazil use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q155 wdt:P37 ?x .
}

Using entities:
Brazil, also known as br, Brasil, Federative Republic of Brazil (wd:Q155): country in South 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 3:
Question:
what main language do they speak in brazil?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q155 wdt:P37 ?x .
}

Using entities:
Brazil, also known as br, Brasil, Federative Republic of Brazil (wd:Q155): country in South 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

[Assistant]
From the similar examples, the entity for Brazil is wd:Q155 and the property for official language is wdt:P37. The query to find the official language of Brazil is straightforward:

SELECT DISTINCT ?language WHERE {
  wd:Q155 wdt:P37 ?language .
}

I will now execute this query to get the official language of Brazil.

[Tool]
Got 1 row and 1 column:
| language              |
| --------------------- |
| Portuguese (wd:Q5146) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?postalCode WHERE {
  wd:Q653636 wdt:P281 ?postalCode .
}

The zip codes for Morgantown, WV are 26501, 26501–26508, 26504, and 26506.

[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 zip code for morgantown wv?

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

[Tool]
Example 1:
Question:
what is the zip code for clarksville tn?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q328941 wdt:P281 ?x .
}

Using entities:
Clarksville, also known as Clarksville, TN, Clarksville, Tennessee (wd:Q328941): city in Tennessee, United States

Using properties:
postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt): identifier assigned by postal authorities for the subject area or building

Example 2:
Question:
what is zip code for chicago illinois?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1297 wdt:P281 ?x .
}

Using entities:
Chicago, also known as The Second City, The Queen of the West, The Windy City, City of Broad Shoulders, City by the Lake (wd:Q1297): city and county seat of Cook County, Illinois, United States of America

Using properties:
postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt): identifier assigned by postal authorities for the subject area or building

Example 3:
Question:
what is the zip code for cordova tn?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5170040 wdt:P281 ?x .
}

Using entities:
Cordova, also known as Cordova, Tennessee (wd:Q5170040): unincorporated community in Shelby County, Tennessee

Using properties:
postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt): identifier assigned by postal authorities for the subject area or building

[Assistant]
From the examples, the pattern to find the zip code for a city is to find the entity for the city and then query the postal code property (wdt:P281) for that entity.

Step 1: Find the entity for Morgantown, WV.
Step 2: Query the postal code (wdt:P281) for that entity.

I will first search for the entity Morgantown, WV.

[Tool]
Top 10 entity alternatives:
1. Morgantown, also known as Morgantown, West Virginia, Morgantown, WV (wd:Q653636): city in and county seat of Monongalia County, West Virginia, United States
2. Morgantown urban area, also known as Morgantown, WV, Morgantown, WV Urban Area (wd:Q125805682): urban area in West Virginia
3. Morgantown metropolitan area, also known as Morgantown, WV Metropolitan Statistical Area, Morgantown, WV MSA, Morgantown, WV metropolitan area, Morgantown MSA, Morgantown metropolitan statistical area (wd:Q17081833): metropolitan area in West Virginia, United States
4. Morgantown, also known as Morgantown, Kentucky, Morgantown, KY (wd:Q2555567): county seat in Kentucky
5. Morgantown, also known as Morgantown, Indiana (wd:Q644950): human settlement in Morgan County, Indiana, United States of America
6. Morgantown, also known as Morgantown, PA, Morgantown, Pennsylvania (wd:Q3960025): census-designated place in Berks and Lancaster counties in Pennsylvania, United States
7. Morgantown, also known as Morgantown, Adams County, Mississippi, Morgantown, MS (wd:Q13580455): census-designated place in Adams County, Mississippi
8. Morgantown, also known as Morgantown, MS (wd:Q3612521): unincorporated community in Marion County, Mississippi
9. Morgantown, also known as Morgantown, Maryland, Morgantown, MD (wd:Q6911981): unincorporated community in Charles County, Maryland
10. Morgantown, also known as Morgantown, MS (wd:Q20658077): human settlement in Oktibbeha County, Mississippi, United States

[Assistant]
The entity for Morgantown, West Virginia is wd:Q653636.

Next, I will query the postal code (wdt:P281) for this entity.

[Tool]
Got 4 rows and 1 column:
| postalCode  |
| ----------- |
| 26501       |
| 26501–26508 |
| 26504       |
| 26506       |

[Tool] Stopped generation process