PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coach WHERE {
  wd:Q330120 p:P286 ?statement .
  ?statement ps:P286 ?coach .
  ?statement pq:P580 ?start .
  ?statement pq:P582 ?end .
  FILTER ( ?start <= '2013-12-31' ^^ xsd:date && ?end >= '2013-01-01' ^^ xsd:date )
}

Ron Rivera

[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 will coach carolina panthers in 2013?

[Assistant]
To answer the question about who coached the Carolina Panthers in 2013, we need to identify the following:
1. The entity for the Carolina Panthers.
2. The property for the coach of a team.
3. The specific coach for the Carolina Panthers in 2013.

Let's start by searching for the entity representing the Carolina Panthers.

[Tool]
Top 10 entity alternatives:
1. Carolina Panthers (wd:Q330120): American football team
2. history of the Carolina Panthers, also known as Carolina Panthers history, the Carolina Panthers history (wd:Q5869201): aspect of history
3. Carolina Panthers Cheerleaders (wd:Q130385213): cheerleading squad of the Carolina Panthers
4. 2021 Carolina Panthers season (wd:Q104869609): 27th season in franchise history
5. 2022 Carolina Panthers season (wd:Q110445399): 28th season in franchise history
6. 2020 Carolina Panthers season (wd:Q80995958): 26th season in franchise history
7. 2018 Carolina Panthers season (wd:Q48843395): 24th season in franchise history
8. 2015 Carolina Panthers season (wd:Q18701993): NFL team 21st season(lost Super Bowl)
9. 2019 Carolina Panthers season (wd:Q60525825): 25th season in franchise history
10. 2023 Carolina Panthers season (wd:Q116170055): 29th season in franchise history

[Assistant] The top result for "Carolina Panthers" is `wd:Q330120`, which represents the American football team. Next, we need to find the property that indicates the coach of a team. Let's search for properties related to "coach".

[Tool]
Top 10 property alternatives:
1. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): 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
2. coach of sports team, also known as trainer of sports team, club manager of sports team, trainer of, team manager of sports team, team manager of (wd:P6087 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): sports club or team for which this person is or was on-field manager or coach
3. PlaymakerStats.com coach ID, also known as PlaymakerStats.com manager ID, TheFinalBall coach ID (wd:P6316 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): identifier for an association football (soccer) coach at PlaymakerStats.com (formerly TheFinalBall.com)
4. LNB Coach id, also known as LNB Pro A coach ID (wd:P6743 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): identifier for a coach in the French basketball championship
5. trained by, also known as personal trainer, trainer (wd:P10449 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): personal trainer of the athlete, student of
6. LevskiSofia.info coach ID (wd:P6410 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): identifier for a coach at the LevskiSofia.info
7. TuttoCalciatori.net coach ID (wd:P7035 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): identifier of a football coach in the website TuttoCalciatori.net
8. Soccerdonna coach ID, also known as Soccerdonna trainer ID (wd:P8134 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): identifier for a coach at the Soccerdonna
9. LegaBasket.it coach ID (wd:P5612 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): identifier for a coach at legabasket.it
10. VBL people ID, also known as VBL coach ID, VBL player ID, VBL staff ID (wd:P4298 as psv/pqn/p/ps/pq/wdtn/prn/prv/wdt/psn/pr/pqv): identifier for a volleyball player on the website of the German Volleyball Federation

[Assistant]
The most relevant property for the coach of a sports team is `wd:P286` (head coach). Now, let's use this property to find the coach of the Carolina Panthers in 2013. We will also need to filter the results to ensure we get the correct year.

Let's execute a SPARQL query to find the coach of the Carolina Panthers in 2013.

[Tool]
Got 1 row and 1 column:
| coach                    |
| ------------------------ |
| Ron Rivera (wd:Q1991889) |

[Assistant]
The coach of the Carolina Panthers in 2013 was Ron Rivera.

Here is the final SPARQL query and answer:

```sparql
SELECT ?coach WHERE {
  wd:Q330120 p:P286 ?statement .
  ?statement ps:P286 ?coach .
  ?statement pq:P580 ?start .
  ?statement pq:P582 ?end .
  FILTER(?start <= '2013-12-31'^^xsd:date && ?end >= '2013-01-01'^^xsd:date)
}
```

The coach of the Carolina Panthers in 2013 was Ron Rivera.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is well-formed and correctly identifies the coach of the Carolina Panthers for the year 2013. The result matches the expected answer, and the query follows all the required rules.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?spouse WHERE {
  wd:Q42869 wdt:P26 ?spouse
}

Nicolas Cage is currently married to Riko Shibata.

[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 is nicolas cage married too?

[Assistant] To answer the question "Who is Nicolas Cage married to?", we need to identify the entity for Nicolas Cage and then find the property that indicates his current spouse. Let's start by searching for Nicolas Cage in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Nicolas Cage, also known as Nicolas Coppola, Nicolas Kim Coppola, Nic Cage (wd:Q42869): television presenter, television producer, executive producer, character actor, American actor, film director, film producer, screenwriter, voice actor, film actor, director, writer, actor
2. Nicolas Cage/Bobby Brown, also known as Saturday Night Live S18E1, Saturday Night Live, season 18 episode 1 (wd:Q110035758): episode of Saturday Night Live (S18 E1)
3. Weekend Update: Nicolas Cage (wd:Q110060114): sketch from Saturday Night Live
4. Cage's Kiss: The Nicolas Cage Podcast (wd:Q110580467): podcast
5. Cage Rage - A Nicolas Cage Podcast (wd:Q110575223): podcast
6. Weekend Update: Nicolas Cage and Bradley Cooper (wd:Q110060014): sketch from Saturday Night Live
7. cage (wd:Q129211): enclosure used to confine, contain or protect something or someone
8. China Zorrilla, also known as Nicolás (wd:Q458175): Uruguayan actress (1922–2014), stage actor, film actor, actor
9. Frida Kalho, also known as Nicolás (wd:Q458175): Uruguayan actress (1922–2014), stage actor, film actor, actor
10. The Cage, also known as Cage, Cage, The, Pilot: The Cage (wd:Q20909): 1986 episode of Star Trek: The Original Series directed by Robert Butler

[Assistant] The top result for Nicolas Cage is `wd:Q42869`. Now, let's find the property that indicates his current spouse. We can search for properties related to marriage or spouse for this entity.

[Tool]
Top 10 property alternatives:
1. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt/p): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
2. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as wdt/p): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
3. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt/p): full name of a person at birth, if different from their current, generally used name, name
4. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
5. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
6. child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt/p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
7. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt/p): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
8. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as wdt/p): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
9. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
10. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as wdt/p): female parent of the subject. For stepmother, use "stepparent" (P3448), parent

No other items found

[Assistant] The property `wd:P26` (spouse) is the most relevant for finding out who Nicolas Cage is married to. Let's execute a SPARQL query to find the current spouse of Nicolas Cage.

[Tool]
Got 1 row and 1 column:
| spouse                       |
| ---------------------------- |
| Riko Shibata (wd:Q109355504) |

[Assistant]
The SPARQL query returned that Nicolas Cage is currently married to Riko Shibata.

Let's finalize the answer with the SPARQL query and the result.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query successfully retrieves the current spouse of Nicolas Cage, which is Riko Shibata. The query follows all the rules and returns the IRI of the item as required.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q206939 wdt:P19 ?birthPlace .
  OPTIONAL {
    ?birthPlace rdfs:label ?birthPlaceLabel .
    FILTER ( LANG( ?birthPlaceLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| birthPlace      | birthPlaceLabel |
| --------------- | --------------- |
| London (wd:Q84) | London (en)     |

Elvis Costello was born in London.

[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 was elvis costello born?

[Assistant]
To answer the question "Where was Elvis Costello born?", we need to identify the entity for Elvis Costello and the property for place of birth. Let's start by searching for Elvis Costello in the knowledge graph.

I will use the `search_entity` function to find the entity for Elvis Costello.

[Tool]
Top 10 entity alternatives:
1. Elvis Costello, also known as Declan MacManus, Declan Patrick MacManus (wd:Q206939): English singer-songwriter (born 1954), record producer, songwriter, guitarist, singer
2. Elvis Costello (wd:Q107119978): lithograph at the Museum of Modern Art; unknown designer
3. Elvis Costello (wd:Q125462686): written work by Eduardo Margaretto Kohrmann
4. Elvis Costello (wd:Q125462696): 1993 edition of written work by Eduardo Margaretto Kohrmann
5. Elvis Costello (wd:Q28052324): painting by Adam Birtwistle
6. Spectacle: Elvis Costello with... (wd:Q7575075): television series
7. Elvis Costello Band concert (wd:Q99322922): Elvis Costello Band concert performed during Montreux Jazz Festival the 1989-07-11
8. Elvis Costello Solo concert (wd:Q99429372): Elvis Costello Solo concert performed during Montreux Jazz Festival the 1989-07-11
9. Elvis Costello & the Attractions, also known as Elvis Costello and the Attractions, Nick Lowe And His Sound (wd:Q7714866): UK musical group
10. Elvis Costello with Steve Nieve (wd:Q105091759): print by Jenny Gill

[Assistant] The top result for Elvis Costello is `wd:Q206939`, which represents the English singer-songwriter. Now, we need to find the property for the place of birth. I will use the `search_property` function to find the property for place of birth.

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

[Assistant]
The top result for the place of birth property is `wd:P19`. Now, we can construct a simple SPARQL query to find the place of birth for Elvis Costello.

Let's execute the following SPARQL query:

```sparql
SELECT ?birthPlace WHERE {
  wd:Q206939 wdt:P19 ?birthPlace .
}
```

This query will return the identifier of the place where Elvis Costello was born.

[Tool]
Got 1 row and 1 column:
| birthPlace      |
| --------------- |
| London (wd:Q84) |

[Assistant]
The SPARQL query returned the identifier `wd:Q84` for the place of birth of Elvis Costello. To provide a more human-readable answer, let's also fetch the label for this place.

We can modify the query to include the label of the birthplace:

```sparql
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q206939 wdt:P19 ?birthPlace .
  OPTIONAL { ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = "en") }
}
```

This query will return both the identifier and the English label of the place where Elvis Costello was born.

[Tool]
Got 1 row and 2 columns:
| birthPlace      | birthPlaceLabel |
| --------------- | --------------- |
| London (wd:Q84) | London (en)     |

[Assistant]
The SPARQL query has returned the identifier `wd:Q84` and the label "London" for the place of birth of Elvis Costello.

Therefore, the answer to the question "Where was Elvis Costello born?" is:

Elvis Costello was born in London.

Here is the final SPARQL query and answer:

```sparql
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q206939 wdt:P19 ?birthPlace .
  OPTIONAL { ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = "en") }
}
```

Answer: Elvis Costello was born in London.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the birthplace of Elvis Costello and returns the IRI along with the label in English.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?movie ?movieLabel WHERE {
  ?movie wdt:P161 wd:Q187038 .
  OPTIONAL {
    ?movie rdfs:label ?movieLabel FILTER ( LANG( ?movieLabel ) = 'en' )
  }
}

Got 118 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                             | movieLabel               |
| --------------------------------- | ------------------------ |
| Think Big (wd:Q1031705)           | Think Big (en)           |
| Death Race (wd:Q1033191)          | Death Race (en)          |
| The Misfit Brigade (wd:Q10478647) | The Misfit Brigade (en)  |
| Deathsport (wd:Q1134750)          | Deathsport (en)          |
| Crank: High Voltage (wd:Q1138916) | Crank: High Voltage (en) |
| ...                               | ...                      |
| Mean Streets (wd:Q841335)         | Mean Streets (en)        |
| True Legend (wd:Q910896)          | True Legend (en)         |
| Kill Bill: Volume 2 (wd:Q928019)  | Kill Bill: Volume 2 (en) |
| Big Stan (wd:Q939728)             | Big Stan (en)            |
| Behind Enemy Lines (wd:Q946863)   | Behind Enemy Lines (en)  |

David Carradine played in the following movies: Think Big, Death Race, The Misfit Brigade, Deathsport, Crank: High Voltage, Mean Streets, True Legend, Kill Bill: Volume 2, Big Stan, Behind Enemy Lines, and many more.

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

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

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

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

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

[User] what movies did david carradine play in?

[Assistant] To answer the question about the movies David Carradine played in, we need to identify the entity for David Carradine and then find the movies he acted in. Let's start by searching for the entity for David Carradine.

[Tool]
Top 10 entity alternatives:
1. David Carradine, also known as John Arthur Carradine (wd:Q187038): American actor (1936–2009), television producer, television actor, character actor, film director, film producer, screenwriter, voice actor, film actor, director, actor
2. David Carradine, also known as David M. Carradine, D. Carradine (wd:Q123597734): structural engineer at BRANZ in New Zealand, structural engineer
3. David Carradine, Actor, Is Dead at 72 (wd:Q123708760): The New York Times article (June 5, 2009)
4. David, also known as David, King of Israel, King David, Dawud re d'Israele, Nabi Dawud King of Israel, sweet singer of Israel (wd:Q41370): king of Israel and Judah, instrumentalist, monarch, warlord, herder, ruler, poet
5. Jacques-Louis David, also known as J.-L. David, Louis David, L. David, J.L. David, J. L. David (wd:Q83155): architectural draftsperson, French painter (1748–1825), politician, painter
6. David, also known as David by Michelangelo, Michelangelo's David, David of Michelangelo, Michaelangelo's David (wd:Q179900): sculpture by Michelangelo
7. Saint David, also known as St. David, St David, David of Wales, Dewi, David (wd:Q331697): patron saint of Wales, Catholic bishop, Catholic priest
8. David, also known as David, Chiriquí, San José de David (wd:Q279009): capital of the province of Chiriquí, Panama
9. Gerard David, also known as Gheeraert Davidt, Gheeraedt David, Gheeraert David, Gheeraedt Davit, Gheeraedt Davidt (wd:Q333380): Early Netherlandish painter, (c. 1460–1523), draftsperson, illuminator, painter, artist
10. Armand David, also known as Pere David, Jean-Pierre-Armand David, David, Père David, Jean Pierre Armand David (wd:Q346939): French Catholic priest, zoologist, and botanist (1826–1900), Catholic priest, ornithologist, missionary, zoologist, botanist, explorer

[Assistant]
The top result for David Carradine is the correct one (wd:Q187038). Now, let's find the movies he acted in. We need to look for the property that indicates the movies an actor has been in. A common property for this is `P161` (cast member of).

Let's check if this property is used for David Carradine.

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
3. filmography, also known as list of films with the person, list of films the person contributed to, list of films about the person (wd:P1283 as wdt/p): item for the list of films a person has contributed to. Don't us...mber" (P161) on items for films, directors with "director" (P57), list of works
4. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
5. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt/p): educational institution attended by subject, affiliation
6. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
7. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
8. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt/p): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
9. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as wdt/p): dissolved, abolished or demolished date, date on which the subject died, end time
10. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as wdt/p): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit

No other items found

[Assistant]
It seems that the property `P161` (cast member of) is not directly used for David Carradine. However, the property `P1283` (filmography) might be relevant. Let's check if this property is used for David Carradine and what it returns.

I will execute a SPARQL query to find the movies listed in David Carradine's filmography.

[Tool]
Got 1 row and 1 column:
| movie        |
| ------------ |
| wd:Q17086354 |

[Assistant]
The query returned a single movie (wd:Q17086354) from David Carradine's filmography. To get more context, let's find the label of this movie and see if there are more movies associated with David Carradine through other properties.

First, let's get the label of the movie.

[Tool]
Got 1 row and 2 columns:
| movie        | movieLabel                       |
| ------------ | -------------------------------- |
| wd:Q17086354 | David Carradine filmography (en) |

[Assistant]
The result shows that the movie (wd:Q17086354) is actually a list or collection of David Carradine's filmography, rather than a specific movie. This suggests that we need to look for individual movies he acted in using a different approach.

Let's try using the property `P161` (cast member of) to find the movies where David Carradine is listed as a cast member.

[Tool]
Got 118 rows and 1 column, showing the first 5 and last 5 rows below:
| movie                             |
| --------------------------------- |
| Think Big (wd:Q1031705)           |
| Death Race (wd:Q1033191)          |
| The Misfit Brigade (wd:Q10478647) |
| Deathsport (wd:Q1134750)          |
| Crank: High Voltage (wd:Q1138916) |
| ...                               |
| Mean Streets (wd:Q841335)         |
| True Legend (wd:Q910896)          |
| Kill Bill: Volume 2 (wd:Q928019)  |
| Big Stan (wd:Q939728)             |
| Behind Enemy Lines (wd:Q946863)   |

[Assistant]
The query returned a list of 118 movies where David Carradine is listed as a cast member. To provide a more complete and readable answer, let's include the labels of these movies in the result.

I will execute a SPARQL query to get both the IRIs and the labels of the movies.

[Tool]
Got 118 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                             | movieLabel               |
| --------------------------------- | ------------------------ |
| Think Big (wd:Q1031705)           | Think Big (en)           |
| Death Race (wd:Q1033191)          | Death Race (en)          |
| The Misfit Brigade (wd:Q10478647) | The Misfit Brigade (en)  |
| Deathsport (wd:Q1134750)          | Deathsport (en)          |
| Crank: High Voltage (wd:Q1138916) | Crank: High Voltage (en) |
| ...                               | ...                      |
| Mean Streets (wd:Q841335)         | Mean Streets (en)        |
| True Legend (wd:Q910896)          | True Legend (en)         |
| Kill Bill: Volume 2 (wd:Q928019)  | Kill Bill: Volume 2 (en) |
| Big Stan (wd:Q939728)             | Big Stan (en)            |
| Behind Enemy Lines (wd:Q946863)   | Behind Enemy Lines (en)  |

[Assistant]
The query successfully returned the IRIs and labels of the movies in which David Carradine played a role. Here are some of the movies:

- **Think Big** (wd:Q1031705)
- **Death Race** (wd:Q1033191)
- **The Misfit Brigade** (wd:Q10478647)
- **Deathsport** (wd:Q1134750)
- **Crank: High Voltage** (wd:Q1138916)
- **Mean Streets** (wd:Q841335)
- **True Legend** (wd:Q910896)
- **Kill Bill: Volume 2** (wd:Q928019)
- **Big Stan** (wd:Q939728)
- **Behind Enemy Lines** (wd:Q946863)

Here is the final SPARQL query and the answer to the user's question:

```sparql
SELECT ?movie ?movieLabel
WHERE {
  ?movie wdt:P161 wd:Q187038 .
  OPTIONAL { ?movie rdfs:label ?movieLabel FILTER(LANG(?movieLabel) = 'en') }
}
```

David Carradine played in the following movies:

- **Think Big**
- **Death Race**
- **The Misfit Brigade**
- **Deathsport**
- **Crank: High Voltage**
- **Mean Streets**
- **True Legend**
- **Kill Bill: Volume 2**
- **Big Stan**
- **Behind Enemy Lines**

And many more.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected results. It retrieves the movies David Carradine played in along with their labels. The answer provided is accurate and comprehensive.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?governmentType WHERE {
  wd:Q155 wdt:P122 ?governmentType .
}

Got 3 rows and 1 column:
| governmentType                        |
| ------------------------------------- |
| representative democracy (wd:Q188759) |
| presidential system (wd:Q49892)       |
| federal republic (wd:Q512187)         |

Brazil has a representative democracy, a presidential system, and is a federal republic.

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

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

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

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

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

[User] what type of political system is brazil?

[Assistant] To determine the type of political system in Brazil, we need to identify the relevant entity for Brazil and then look for properties that describe its government or political system. Let's start by searching for the entity representing Brazil.

[Tool]
Top 10 entity alternatives:
1. Brazil, also known as Federative Republic of Brazil, Brasil, br (wd:Q155): country in South America
2. Brazil, also known as br, Brasil, Federative Republic of Brazil (wd:Q155): country in South America
3. Brazil (wd:Q25057): 1985 dystopian film by Terry Gilliam
4. Brazil, also known as Brazil, Indiana, Brazil, IN (wd:Q1998364): city in Clay County, Indiana, United States
5. State of Brazil, also known as Brazil, Colonial Brazil, Portuguese Brazil (wd:Q11876909): state of the Portuguese Empire
6. Brazil, also known as Stars and Guitars (wd:Q4958616): 1944 film by Joseph Santley
7. Brazil, also known as Brazil, IA (wd:Q17511873): human settlement in Appanoose County, Iowa, United States
8. Viceroyalty of Brazil, also known as Brasil, Brazil (wd:Q2920081): Portuguese viceroyalty in Brazil 1763-1815
9. Brazil (wd:Q13581616): 1991 song by Bebi Dol
10. Brazil (wd:Q4095706): 1994 novel by John Updike

[Assistant] The top result for "Brazil" is the country in South America, which is the entity we are looking for. The IRI for Brazil is `wd:Q155`. Next, we need to find properties that describe the political system or government of Brazil. We can search for properties related to "government" or "political system" for this entity.

[Tool]
Top 10 property alternatives:
1. basic form of government, also known as form of government, government, type of government (wd:P122 as wdt/p): subject's government
2. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt/p): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
3. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt/p): seat of government of a country, province, state or other type of administrative territorial entity
4. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as wdt/p): political office that is fulfilled by the head of the government of this item
5. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as wdt/p): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
6. executive body, also known as executive branch (wd:P208 as wdt/p): branch of government for the daily administration of the territorial entity
7. main regulatory text, also known as regulated by, statutory authorization, statutory authority, legally established by, legal basis (wd:P92 as wdt/p): text setting the main rules by which the subject is regulated
8. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
9. has cabinet, also known as cabinet (wd:P12443 as wdt/p): value is the advisory committee to the item's head of state
10. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as wdt/p): political office that is fulfilled by the head of state of this item

No other items found

[Assistant]
From the search results, the property `wdt:P122` (basic form of government) seems to be the most relevant for determining the type of political system in Brazil. Let's use this property in a SPARQL query to find out the type of government in Brazil.

I will now construct and execute a SPARQL query to retrieve the type of government for Brazil.

[Tool]
Got 3 rows and 1 column:
| governmentType                        |
| ------------------------------------- |
| representative democracy (wd:Q188759) |
| presidential system (wd:Q49892)       |
| federal republic (wd:Q512187)         |

[Assistant]
The SPARQL query returned three types of government for Brazil:
1. Representative democracy (wd:Q188759)
2. Presidential system (wd:Q49892)
3. Federal republic (wd:Q512187)

These results indicate that Brazil has a representative democracy, a presidential system, and is a federal republic. To provide a clear and concise answer, we can combine these into a single statement.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?governmentType WHERE {
  wd:Q155 wdt:P122 ?governmentType .
}
```

Answer: Brazil has a representative democracy, a presidential system, and is a federal republic.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query returns the appropriate government types for Brazil, and the human-readable answer accurately reflects the results.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?date WHERE {
  wd:Q211386 wdt:P585 ?date .
}

The big earthquake hit San Francisco on April 18, 1906.

[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 the big earthquake hit san francisco?

[Assistant]
To answer the question about when the big earthquake hit San Francisco, we need to identify the specific earthquake event and then find the date it occurred. Let's start by searching for the entity representing the 1906 San Francisco earthquake in Wikidata.

I will use the `search_entity` function to find the entity for the 1906 San Francisco earthquake.

[Tool]
Top 10 entity alternatives:
1. 1906 San Francisco earthquake, also known as Great San Francisco Earthquake and Fire, San Francisco earthquake of 1906, San Francisco earthquake and fire, 1906, Great 1906 San Francisco Earthquake, earthquake of 1906 (wd:Q211386): major earthquake that struck San Francisco and the coast of Northern California
2. 1906 San Francisco earthquake, also known as 1906 San Francisco earthquake and fire, earthquake of 1906, San Francisco earthquake of 1906, Great 1906 San Francisco Earthquake, Great San Francisco Earthquake and Fire (wd:Q211386): major earthquake that struck San Francisco and the coast of Northern California
3. The San Francisco earthquake of 1906 (wd:Q58176314): scholarly article by Dennis R. Dean published November 1993 in Annals of Science
4. Simulations of the 1906 San Francisco Earthquake (wd:Q57871965): scholarly article published 16 December 2005
5. The 1906 San Francisco Earthquake and Fire (wd:Q133012217): online exhibition from National Archives and Records Administration (United States)
6. San Francisco Earthquake & Fire: April 18, 1906, also known as San Francisco Earthquake and Fire, April 18, 1906 (wd:Q19599178): 1906 film
7. Postseismic deformation following the 1906 San Francisco earthquake (wd:Q97865309): scientific article published on 10 June 2000
8. Source mechanism of the 1906 San Francisco earthquake (wd:Q98594973): scientific article published in September 1978
9. The 1906 San Francisco earthquake: a centennial contemplation. (wd:Q45948972): scientific article published in May 2006
10. Strain release mechanism of the 1906 san francisco earthquake (wd:Q57140054): scientific article

[Assistant]
The top result is the 1906 San Francisco earthquake, which is the entity we are looking for. The IRI for this entity is `wd:Q211386`.

Next, we need to find the date when this earthquake occurred. We can use the `search_property_of_entity` function to find the property that represents the date of the earthquake.

Let's search for the property related to the date of the earthquake for the entity `wd:Q211386`.

[Tool]
Top 10 property alternatives:
1. point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt/p): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
2. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt/p): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt/p): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
5. video, also known as gif, animation, trailer, media (wd:P10 as wdt/p): relevant video. For images, use the property P18. For film trailers, qualify with "object has role" (P3831)="trailer" (Q622550)
6. has cause, also known as implied by, originated due to, initial cause, outcome of, reason (wd:P828 as wdt/p): underlying cause, entity that ultimately resulted in this effect, follows
7. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
8. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
9. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
10. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

No other items found

[Assistant]
The top result for the property related to the date of the earthquake is "point in time" (`wdt:P585`). This property is used to specify the date when an event occurred.

Now, let's construct a SPARQL query to retrieve the date of the 1906 San Francisco earthquake using the identified entity and property.

Here is the SPARQL query:

```sparql
SELECT ?date
WHERE {
  wd:Q211386 wdt:P585 ?date .
}
```

I will execute this query to get the date of the earthquake.

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 1906-04-18T00:00:00Z (xsd:dateTime) |

[Assistant]
The SPARQL query returned the date of the 1906 San Francisco earthquake as `1906-04-18T00:00:00Z`, which corresponds to April 18, 1906.

Therefore, the big earthquake hit San Francisco on April 18, 1906.

Here is the final SPARQL query and answer:

```sparql
SELECT ?date
WHERE {
  wd:Q211386 wdt:P585 ?date .
}
```

Answer: The big earthquake hit San Francisco on April 18, 1906.

I will now provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the date of the 1906 San Francisco earthquake using the appropriate entity and property. The result is accurate and matches the historical record.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?laos ?laosLabel ?coordinates WHERE {
  wd:Q819 rdfs:label ?laosLabel .
  FILTER ( LANG( ?laosLabel ) = "en" ) wd:Q819 wdt:P625 ?coordinates .
  BIND( wd:Q819 AS ?laos )
}

Laos is located at the coordinates POINT(104.100000 18.200000).

[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 is laos in world map?

[Assistant]
To answer the question "Where is Laos in the world map?", we need to find the geographic location of Laos. We can start by searching for the entity representing Laos in the knowledge graph.

Let's search for the entity "Laos" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Laos, also known as LAO, Lao PDR, Lao People's Democratic Republic, la (wd:Q819): country in Southeast Asia
2. Tai peoples, also known as Laos, Shans (wd:Q703353): ethnic group
3. Laotians, also known as Lao, Laos (wd:Q11346642): citizens or residents of Laos
4. Laos (wd:Q28322504): family name
5. Laos (wd:Q3217694): German hard rock band
6. Laos (wd:Q103947900): encyclopedia article
7. Laos. (wd:Q47411910): scientific article published in May 1986
8. Laos (wd:Q59597671): Congressional Research Service report
9. Laos (wd:Q58675659): scholarly article
10. Laos (wd:Q130900075): scientific article published in January 2003

[Assistant]
The top result for "Laos" is the country in Southeast Asia, which is represented by the entity `wd:Q819`.

Next, we need to find the geographic coordinates of Laos. We can use the property `wdt:P625` which represents the geographic coordinates of a place.

Let's retrieve the geographic coordinates of Laos.

[Tool]
Got 1 row and 1 column:
| coordinates                                  |
| -------------------------------------------- |
| POINT(104.100000 18.200000) (geo:wktLiteral) |

[Assistant]
The geographic coordinates of Laos are `POINT(104.100000 18.200000)`.

To provide a more user-friendly answer, we can include the label of Laos and its coordinates. Let's construct a final SPARQL query to retrieve both the IRI and the label of Laos, along with its coordinates.

Here is the final SPARQL query:

```sparql
SELECT ?laos ?laosLabel ?coordinates
WHERE {
  wd:Q819 rdfs:label ?laosLabel .
  FILTER(LANG(?laosLabel) = "en")
  wd:Q819 wdt:P625 ?coordinates .
  BIND(wd:Q819 AS ?laos)
}
```

Let's execute this query to get the final result.

[Tool]
Got 1 row and 3 columns:
| laos           | laosLabel | coordinates                                  |
| -------------- | --------- | -------------------------------------------- |
| Laos (wd:Q819) | Laos (en) | POINT(104.100000 18.200000) (geo:wktLiteral) |

[Assistant]
The final result shows that Laos is located at the coordinates `POINT(104.100000 18.200000)`.

Here is the final SPARQL query and the answer to the user's question:

```sparql
SELECT ?laos ?laosLabel ?coordinates
WHERE {
  wd:Q819 rdfs:label ?laosLabel .
  FILTER(LANG(?laosLabel) = "en")
  wd:Q819 wdt:P625 ?coordinates .
  BIND(wd:Q819 AS ?laos)
}
```

Answer: Laos is located at the coordinates `POINT(104.100000 18.200000)`.

Now, let's provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query returns the IRI of Laos, its label, and its coordinates, which accurately represent its location on the world map.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?placeOfDeath ?placeOfDeathLabel WHERE {
  wd:Q1035 wdt:P20 ?placeOfDeath .
  OPTIONAL {
    ?placeOfDeath rdfs:label ?placeOfDeathLabel .
    FILTER ( LANG( ?placeOfDeathLabel ) = 'en' )
  }
}

Got 1 row and 2 columns:
| placeOfDeath             | placeOfDeathLabel |
| ------------------------ | ----------------- |
| Down House (wd:Q3038318) | Down House (en)   |

Charles Darwin died at Down House.

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

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

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

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

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

[User] where did charles darwin die?

[Assistant] To answer the question "Where did Charles Darwin die?", we need to identify the entity for Charles Darwin and then find the property that indicates his place of death. Let's start by searching for the entity representing Charles Darwin in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Charles Darwin (wd:Q1035): English naturalist and biologist (1809–1882), travel writer, philosopher, ethologist, naturalist, geologist, botanist, explorer, writer
2. Charles Galton Darwin, also known as Sir Charles Galton Darwin, Charles Darwin (wd:Q1064506): British physicist (1887–1962), university teacher, physicist
3. Charles Darwin (wd:Q5076724): oldest son of Erasmus Darwin and uncle of the naturalist Charles Darwin, physician, writer
4. Darwin, Charles (wd:Q107131027): entry in Alumni Oxonienses: the Members of the University of Oxford, 1715-1886
5. Charles Darwin (wd:Q5076728): British flying ace, military personnel
6. Charles Darwin, also known as Charles Darwin, Northern Territory, Charles Darwin, Northern Territory, Australia (wd:Q5076727): location in Northern Territory, Australia
7. Charles Darwin (wd:Q15873833): album by XII Alfonso
8. Charles Darwin (wd:Q19153034): German article in Die Gartenlaube, 1882, no. 19
9. Charles Darwin (wd:Q52450322): scientific article published in June 1972
10. Charles Darwin (wd:Q49071987): scientific article published in January 1990

[Assistant] The top result, `wd:Q1035`, represents Charles Darwin, the English naturalist and biologist. Now, let's find the property that indicates the place of death for this entity.

[Tool]
Top 10 property alternatives:
1. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt/p): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
2. place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as wdt/p): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
3. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as wdt/p): dissolved, abolished or demolished date, date on which the subject died, end time
4. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
5. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
6. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as wdt/p): the place where the person is or has been, resident, location
7. Find a Grave memorial ID, also known as FaG ID, FaGID, Find A Grave grave ID, Findagrave ID, Find A Grave memorial ID (wd:P535 as wdt/p): identifier of an individual's burial place in the Find a Grave database
8. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
9. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
10. significant person, also known as significant people, sigper, sign. person, relevant person, relevant people (wd:P3342 as wdt/p): person linked to the item in any possible way

No other items found

[Assistant] The property `wdt:P20` (place of death) is the most relevant for our query. Let's construct a SPARQL query to find the place of death for Charles Darwin (`wd:Q1035`).

[Tool]
Got 1 row and 1 column:
| placeOfDeath             |
| ------------------------ |
| Down House (wd:Q3038318) |

[Assistant] The place of death for Charles Darwin is Down House, represented by the IRI `wd:Q3038318`. To provide a more complete answer, let's include the label of the place of death in the query.

[Tool]
Got 1 row and 2 columns:
| placeOfDeath             | placeOfDeathLabel |
| ------------------------ | ----------------- |
| Down House (wd:Q3038318) | Down House (en)   |

[Assistant]
The place of death for Charles Darwin is Down House, located in England. Here is the final SPARQL query and answer:

```sparql
SELECT ?placeOfDeath ?placeOfDeathLabel
WHERE {
  wd:Q1035 wdt:P20 ?placeOfDeath .
  OPTIONAL { ?placeOfDeath rdfs:label ?placeOfDeathLabel . FILTER(LANG(?placeOfDeathLabel) = 'en') }
}
```

Answer: Charles Darwin died at Down House.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query returns the IRI and label of the place where Charles Darwin died, which is Down House. The query follows all the rules and guidelines provided.