PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?actor ?actorLabel WHERE {
  ?work wdt:P161 ?actor .
  ?work p:P161 ?statement .
  ?statement pq:P453 wd:Q694790 .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel .
    FILTER ( LANG( ?actorLabel ) = "en" )
  }
}

Got 183 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?actor                            | ?actorLabel         |
| --------------------------------- | ------------------- |
| Sara Sampaio (wd:Q10368401)       | Sara Sampaio        |
| Christian Clemenson (wd:Q1079204) | Christian Clemenson |
| Milly Alcock (wd:Q108816955)      | Milly Alcock        |
| Conrad Goode (wd:Q1126809)        | Conrad Goode        |
| Cress Williams (wd:Q1139717)      | Cress Williams      |
| ...                               | ...                 |
| Brian Doyle-Murray (wd:Q912103)   | Brian Doyle-Murray  |
| Eric Allan Kramer (wd:Q922264)    | Eric Allan Kramer   |
| Kirk Alyn (wd:Q935563)            | Kirk Alyn           |
| Ian Roberts (wd:Q942066)          | Ian Roberts         |
| Stephan Bender (wd:Q944747)       | Stephan Bender      |

The actors who have played Lex Luthor include Sara Sampaio, Christian Clemenson, Milly Alcock, Conrad Goode, Cress Williams, Brian Doyle-Murray, Eric Allan Kramer, Kirk Alyn, Ian Roberts, and Stephan Bender, among others.

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

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

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

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

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

[User] who has played lex luthor?

[Assistant] To answer the question "Who has played Lex Luthor?", we need to identify the character "Lex Luthor" and then find the actors who have portrayed this character. Let's start by searching for "Lex Luthor" in the knowledge graph to find the corresponding entity.

[Tool]
Top 10 entity alternatives:
1. Lex Luthor, also known as Alexander Joseph Luthor, Alexander Luthor, Alexander Joseph "Lex" Luthor (wd:Q694790): supervillain appearing in DC Comics publications and related media, chief executive officer, business executive, business magnate, drug trafficker, philanthropist, mass murderer, roboticist, crime boss, superhero, physicist, engineer, inventor, chemist
2. Lex Luthor, also known as Alexander Joseph "Lex" Luthor, Jr. (wd:Q110800327): DC Extended Universe character, chief executive officer, business executive, philanthropist, mass murderer, scientist, socialite, terrorist, engineer, criminal
3. Green Skull, also known as Alexander Luthor, Lex Luthor (wd:Q9300166): fictional character in Amalgam Comics
4. Lex Luthor, also known as Alexander Joseph Luthor (wd:Q91371653): fictional character from the television series Supergirl, time traveller, businessperson, politician, terrorist, criminal, inventor
5. Lex Luthor (wd:Q105123177): villain in the film Superman (1978), scientist, criminal, inventor
6. Lex Lutor, also known as Alexander Luthor, Lex Luthor (Smallville) (wd:Q735712): fictional character from the television series Smallville, businessperson, murderer
7. Lex Luthor, Jr. (wd:Q3831418): American investor, criminal, investor
8. Eve Teschmacher, also known as Eve, Lex Luthor's Girlfriend (wd:Q22266383): DC Comics character, secretary
9. Vitor Miranda, also known as Vitor "Lex Luthor" Miranda (wd:Q7937196): mixed martial arts fighter, Brazilian martial artist, Thai boxer, kickboxer
10. Lex Luthor's Presidency (wd:Q18280092)

No other items found

[Assistant]
The top result for "Lex Luthor" is the supervillain appearing in DC Comics publications and related media (wd:Q694790). This is the character we are interested in. Next, we need to find the actors who have played this character. We will search for the property that links actors to the characters they have played.

Let's search for the property that connects actors to the characters they have played.

[Tool]
Top 10 property alternatives:
1. character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
2. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as ps/wdt): owner of the subject
3. enemy, also known as opponent, rival, archvillain, archrival, archnemesis (wd:P7047 as ps/wdt): opponent character or group of this fictive character or group, significant person
4. based on, also known as modelled after, inspired by, iteration of, modeled after, fork of (wd:P144 as ps/wdt): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, references work, tradition or theory, inspired by
5. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as ps/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
6. developer, also known as written by, video game developer, video game dev, game developer, game dev (wd:P178 as ps/wdt): organization or person that developed the item, creator
7. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as ps/wdt): founder or co-founder of this organization, religion, place or entity, creator
8. said to be the same as, also known as may be, the same as, synonymous with, same as, same (wd:P460 as ps/wdt): this item is said to be the same as that item, though this may be uncertain or disputed
9. child, also known as has son, kids, mother of, kid, issue (wd:P40 as ps/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
10. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as ps/wdt): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person

No other items found

[Assistant]
The property that connects actors to the characters they have played is `character role` (wd:P453), but it is used as a qualifier for the property `cast member` (wd:P161). Therefore, we need to use `cast member` (wd:P161) and include `character role` (wd:P453) as a qualifier to find the actors who have played Lex Luthor.

Let's construct a SPARQL query to find the actors who have played Lex Luthor.

```sparql
SELECT ?actor ?actorLabel
WHERE {
  ?work wdt:P161 ?actor .
  ?work p:P161 ?statement .
  ?statement pq:P453 wd:Q694790 .
  OPTIONAL { ?actor rdfs:label ?actorLabel . FILTER(LANG(?actorLabel) = "en") }
}
```

This query will find the works where Lex Luthor was a character and the actors who played him. Let's execute this query.

[Tool]
Got 183 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?actor                            | ?actorLabel         |
| --------------------------------- | ------------------- |
| Sara Sampaio (wd:Q10368401)       | Sara Sampaio        |
| Christian Clemenson (wd:Q1079204) | Christian Clemenson |
| Milly Alcock (wd:Q108816955)      | Milly Alcock        |
| Conrad Goode (wd:Q1126809)        | Conrad Goode        |
| Cress Williams (wd:Q1139717)      | Cress Williams      |
| ...                               | ...                 |
| Brian Doyle-Murray (wd:Q912103)   | Brian Doyle-Murray  |
| Eric Allan Kramer (wd:Q922264)    | Eric Allan Kramer   |
| Kirk Alyn (wd:Q935563)            | Kirk Alyn           |
| Ian Roberts (wd:Q942066)          | Ian Roberts         |
| Stephan Bender (wd:Q944747)       | Stephan Bender      |

[Assistant]
The SPARQL query returned a list of actors who have played Lex Luthor. Here are some of the actors:

- Sara Sampaio
- Christian Clemenson
- Milly Alcock
- Conrad Goode
- Cress Williams
- Brian Doyle-Murray
- Eric Allan Kramer
- Kirk Alyn
- Ian Roberts
- Stephan Bender

These are the actors who have portrayed Lex Luthor in various works.

Let's finalize the answer with the SPARQL query and the list of actors.

```sparql
SELECT ?actor ?actorLabel
WHERE {
  ?work wdt:P161 ?actor .
  ?work p:P161 ?statement .
  ?statement pq:P453 wd:Q694790 .
  OPTIONAL { ?actor rdfs:label ?actorLabel . FILTER(LANG(?actorLabel) = "en") }
}
```

Answer: The actors who have played Lex Luthor include Sara Sampaio, Christian Clemenson, Milly Alcock, Conrad Goode, Cress Williams, Brian Doyle-Murray, Eric Allan Kramer, Kirk Alyn, Ian Roberts, and Stephan Bender, among others.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?town ?townLabel WHERE {
  wd:Q8027 wdt:P20 ?town .
  OPTIONAL {
    ?town rdfs:label ?townLabel .
    FILTER ( LANG( ?townLabel ) = "en" )
  }
}

Memphis

[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 town was martin luther king assassinated in?

[Assistant] To answer the question about the town where Martin Luther King Jr. was assassinated, I need to identify the entity for Martin Luther King Jr. and the property that indicates the location of his assassination. Let's start by searching for Martin Luther King Jr. in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Martin Luther King Jr. (wd:Q8027): American Baptist minister and civil rights leader (1929–1968), human rights activist, civil rights advocate, opinion journalist, peace activist, politician, preacher, pacifist, writer, pastor
2. Martin Luther King Jr. (wd:Q16974341): station on the Crenshaw Line, currently under construction
3. Martin Luther King, Jr. (wd:Q6776048): sculpture by John Woodrow Wilson
4. Martin Luther King Jr. (wd:Q39073111): Outdoor bronze sculpture depicting the American civil rights leader  installed on the University of Texas at Austin campus.
5. Martin Luther King, Jr. (wd:Q111842410): sculpture by artist unknown
6. Martin Luther King, Jr. (wd:Q116445650): print at the Metropolitan Museum of Art (MET, 2022.102)
7. Martin Luther King, Jr. (wd:Q47509396): painting by Robert Vickrey
8. Martin Luther King, Jr. (wd:Q47511447): painting by Boris Chaliapin
9. Martin Luther King, Jr. (wd:Q63570975): technical material in the National Gallery of Art (NGA 59039)
10. Martin Luther King, Jr. (wd:Q65577725): print in the National Gallery of Art (NGA 59040)

No other items found

[Assistant] The top result for "Martin Luther King Jr." is `wd:Q8027`, which represents the American Baptist minister and civil rights leader. Next, I will search for the property that indicates the location of his assassination.

[Tool]
Top 10 property alternatives:
1. killed by, also known as slaughtered by, slain by, shot dead by, murderer, murdered by (wd:P157 as p/wdt): person or organization who killed the subject, significant person
2. 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
3. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt/p): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
4. place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as p/wdt): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
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. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as wdt/p): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
7. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as p/wdt): significant or notable events associated with the subject
8. image of grave, also known as headstone picture, image of gravestone, image of cenotaph, image of grave, image of shrine (wd:P1442 as p/wdt): picture of a person or animal's grave, gravestone or tomb, image
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. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The property that indicates the location of Martin Luther King Jr.'s assassination is `wdt:P20` (place of death). Now, I will construct a SPARQL query to retrieve the town where he was assassinated.

Let's execute the query:

```sparql
SELECT ?town ?townLabel
WHERE {
  wd:Q8027 wdt:P20 ?town .
  OPTIONAL { ?town rdfs:label ?townLabel . FILTER(LANG(?townLabel) = "en") }
}
```

This query will return the town where Martin Luther King Jr. was assassinated, along with its label in English.

[Tool]
Got 1 row and 2 columns:
| ?town               | ?townLabel |
| ------------------- | ---------- |
| Memphis (wd:Q16563) | Memphis    |

[Assistant]
The town where Martin Luther King Jr. was assassinated is Memphis.

Here is the final SPARQL query and answer:

```sparql
SELECT ?town ?townLabel
WHERE {
  wd:Q8027 wdt:P20 ?town .
  OPTIONAL { ?town rdfs:label ?townLabel . FILTER(LANG(?townLabel) = "en") }
}
```

Answer: Memphis

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?continent ?adminEntity WHERE {
  wd:Q6583 wdt:P30 ?continent .
  OPTIONAL {
    wd:Q6583 wdt:P131 ?adminEntity .
  }
}

Got 9 rows and 2 columns:
| ?continent      | ?adminEntity          |
| --------------- | --------------------- |
| Africa (wd:Q15) | Libya (wd:Q1016)      |
| Africa (wd:Q15) | Mauritania (wd:Q1025) |
| Africa (wd:Q15) | Morocco (wd:Q1028)    |
| Africa (wd:Q15) | Sudan (wd:Q1049)      |
| Africa (wd:Q15) | Algeria (wd:Q262)     |
| Africa (wd:Q15) | Chad (wd:Q657)        |
| Africa (wd:Q15) | Egypt (wd:Q79)        |
| Africa (wd:Q15) | Mali (wd:Q912)        |
| Africa (wd:Q15) | Tunisia (wd:Q948)     |

The Sahara Desert is located on the continent of Africa and covers the following countries: Libya, Mauritania, Morocco, Sudan, Algeria, Chad, Egypt, Mali, and Tunisia.

[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 are the sahara desert located?

[Assistant] To answer the question about the location of the Sahara Desert, I need to identify the entity for the Sahara Desert and then find the property that indicates its location. Let's start by searching for the Sahara Desert in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Sahara, also known as the Desart, Zara, Zahara, Zaara, The Sahara (wd:Q6583): desert on the African continent
2. Sahara Desert (wd:Q3889421): ecoregion
3. Sahara (Desert) (wd:Q104765650): painting by Jan Ciągliński (MNK MNK II-b-422)
4. Sahara (Desert) (wd:Q104765639): painting by Jan Ciągliński (MNK MNK II-b-419)
5. Sahara (Desert) (wd:Q104765619): painting by Jan Ciągliński (MNK MNK II-b-426)
6. Sahara (Desert) (wd:Q104765585): painting by Jan Ciągliński
7. Sahara desert (wd:L643007-S1)
8. Sahara desert (wd:L300591-S1)
9. Sahara Desert (wd:L1411251-S1)
10. Cataglyphis bicolor, also known as Sahara desert ant (wd:Q1717126): species of insect

No other items found

[Assistant] The top result for the Sahara Desert is `wd:Q6583`. Now, I will look for the property that indicates the location of the Sahara Desert. Typically, this would be something like "located in" or "continent". Let's search for the relevant property.

[Tool]
Top 10 property alternatives:
1. 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 p/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
2. 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
3. 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
4. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
5. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/p): area occupied by an object
6. 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)
7. continent (wd:P30 as wdt/p): continent of which the subject is a part, located in/on physical feature
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant]
The most relevant properties for the location of the Sahara Desert are `wdt:P131` (located in the administrative territorial entity) and `wdt:P30` (continent). Let's use these properties to construct a SPARQL query to find the location of the Sahara Desert.

I will start with a simple query to get the continent and then add the administrative territorial entity if needed.

[Tool]
Got 1 row and 1 column:
| ?continent      |
| --------------- |
| Africa (wd:Q15) |

[Assistant] The Sahara Desert is located on the continent of Africa. To provide a more detailed location, I will now include the administrative territorial entity (`wdt:P131`) in the query to see if it provides more specific regions or countries where the Sahara Desert is located.

[Tool]
Got 9 rows and 2 columns:
| ?continent      | ?adminEntity          |
| --------------- | --------------------- |
| Africa (wd:Q15) | Libya (wd:Q1016)      |
| Africa (wd:Q15) | Mauritania (wd:Q1025) |
| Africa (wd:Q15) | Morocco (wd:Q1028)    |
| Africa (wd:Q15) | Sudan (wd:Q1049)      |
| Africa (wd:Q15) | Algeria (wd:Q262)     |
| Africa (wd:Q15) | Chad (wd:Q657)        |
| Africa (wd:Q15) | Egypt (wd:Q79)        |
| Africa (wd:Q15) | Mali (wd:Q912)        |
| Africa (wd:Q15) | Tunisia (wd:Q948)     |

[Assistant]
The Sahara Desert is located on the continent of Africa and spans several countries, including Libya, Mauritania, Morocco, Sudan, Algeria, Chad, Egypt, Mali, and Tunisia.

Here is the final SPARQL query and answer:

```sparql
SELECT ?continent ?adminEntity WHERE {
  wd:Q6583 wdt:P30 ?continent .
  OPTIONAL { wd:Q6583 wdt:P131 ?adminEntity . }
}
```

The Sahara Desert is located on the continent of Africa and covers the following countries: Libya, Mauritania, Morocco, Sudan, Algeria, Chad, Egypt, Mali, and Tunisia.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?currency ?currencyLabel WHERE {
  wd:Q766 wdt:P38 ?currency .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel .
    FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| ?currency                    | ?currencyLabel  |
| ---------------------------- | --------------- |
| Jamaican dollar (wd:Q209792) | Jamaican dollar |

The Jamaican money is called the Jamaican dollar.

[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 jamaican money called?

[Assistant] To answer the question about what Jamaican money is called, we need to identify the currency of Jamaica. Let's start by searching for the entity representing Jamaica and then find the property that links to its currency.

[Tool]
Top 10 entity alternatives:
1. Jamaica, also known as JA, JM, JAM, Commonwealth of Jamaica (wd:Q766): island state in the Caribbean Sea
2. Jamaica men's national association football team, also known as Jamaica, Reggae Boyz, Jamaica national soccer team, Jamaica national football team, Jamaica national association football team (wd:Q235399): men's national association football team representing Jamaica
3. Jamaica, also known as Jamaica, Iowa, Jamaica, IA (wd:Q1913470): city in Iowa, United States
4. Jamaica, also known as Jamaica, Vermont, Jamaica, VT (wd:Q3450853): town in Vermont, United States
5. Jamaica, also known as Jamaica, New York City, Jamaica, Queens (wd:Q1320403): neighborhood of Queens, New York City, United States
6. Colony of Jamaica, also known as Jamaica and Dependencies, Jamaica Colony, Jamaica (wd:Q2526023): British colony on the island of Jamaica, 1655–1962
7. Jamaica (wd:Q11310077): Long Island Rail Road train station in Queens, New York
8. Jamaica, also known as Island of Jamaica, Jamaica island, main island of Jamaica, mainland Jamaica (wd:Q27119301): largest island of Jamaica, comprising most of its territory
9. Jamaica, also known as Jamaica metro station, Jamaica station (wd:Q3377006): metro station in Mexico City
10. Jamaica, also known as Poney Poney (wd:Q943535): French band

No other items found

[Assistant] The top result for "Jamaica" is the island state in the Caribbean Sea, which is the correct entity we are looking for. Now, let's find the property that links to the currency of Jamaica.

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as wdt/p): currency used by item, uses
2. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as wdt/p): market value of all officially recognized final goods and services produced within a country in a given period of time
3. central bank (wd:P1304 as wdt/p): country's central bank
4. flag, also known as flag description (wd:P163 as wdt/p): subject's flag
5. 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
6. VAT rate, also known as goods and services tax rate, GST, sales tax, taxation rate for sales, tax rate for sales (wd:P2855 as p/wdt): percentage value-added tax in this country or region. Do not use for sales tax. For specialised rates, use qualifiers
7. 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)
8. continent (wd:P30 as wdt/p): continent of which the subject is a part, located in/on physical feature
9. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity
10. located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt/p): time zone for this item

No other items found

[Assistant]
The property `currency` (P38) is the correct property that links to the currency used by a country. Now, let's construct a SPARQL query to find the currency of Jamaica.

We will use the IRI `wd:Q766` for Jamaica and the property `wdt:P38` to find the currency.

Let's execute the query:

```sparql
SELECT ?currency
WHERE {
  wd:Q766 wdt:P38 ?currency .
}
```

This query will return the IRI of the currency used in Jamaica. We can also optionally include the label of the currency for better readability.

Let's execute the query:

```sparql
SELECT ?currency ?currencyLabel
WHERE {
  wd:Q766 wdt:P38 ?currency .
  OPTIONAL { ?currency rdfs:label ?currencyLabel . FILTER(LANG(?currencyLabel) = "en") }
}
```

Now, let's run this query.

[Tool]
Got 1 row and 2 columns:
| ?currency                    | ?currencyLabel  |
| ---------------------------- | --------------- |
| Jamaican dollar (wd:Q209792) | Jamaican dollar |

[Assistant]
The currency used in Jamaica is the Jamaican dollar.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?currency ?currencyLabel
WHERE {
  wd:Q766 wdt:P38 ?currency .
  OPTIONAL { ?currency rdfs:label ?currencyLabel . FILTER(LANG(?currencyLabel) = "en") }
}
```

The Jamaican money is called the **Jamaican dollar**.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?country WHERE {
  wd:Q9441 wdt:P19 ?placeOfBirth .
  ?placeOfBirth wdt:P17 ?country .
}

Nepal

[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 country did buddha come from?

[Assistant]
To answer the question about the country Buddha came from, I need to identify the entity for Buddha and then find the country associated with his place of birth or origin. Let's start by searching for Buddha in the knowledge graph.

I will search for the subject "Buddha" in the Wikidata knowledge graph.

[Tool]
Top 10 entity alternatives:
1. The Buddha, also known as Trigyesh, Shakyamuni, Sakyasinha, Shakyasimha, Siddhartha Gautama (wd:Q9441): Indian philosopher and the founder of Buddhism (623 or 563 BCE – 543 or 483 BCE), spiritual teacher, religious leader, social reformer, father of faith, psychologist, psychiatrist, philosopher, preacher, bhikkhu, writer
2. The Buddha, also known as Lord Buddha, Mahatma Buddha, Siddhartha Gautama, Munish, Shakyasimha (wd:Q9441): Indian philosopher and the founder of Buddhism (623 or 563 BCE – 543 or 483 BCE), spiritual teacher, religious leader, father of faith, social reformer, psychologist, psychiatrist, philosopher, preacher, bhikkhu, writer
3. Buddha, also known as Arhat, Vijjācaraṇasampanna, Vidyācaraṇasaṃpanna, Tathārāja, Sugata (wd:Q7055): being who attains perfect enlightenment
4. buddhahood, also known as Buddha, fóguǒ, Chengfo, bukkai, buddhatta (wd:Q56247062): condition or rank of fully awakened enlightenment
5. Buddharupa, also known as Buddha, Buddharūpa (wd:Q1000809): statues of beings who have obtained Buddhahood
6. Buddha (wd:Q945140): manga series
7. Ulf Ekberg, also known as Ulf Buddha Ekberg, Ulf Gunnar Ekberg, Buddha (wd:Q2656667): television producer, Swedish musician, record producer, businessperson, film producer, songwriter, composer, musician, singer
8. Buddha (wd:Q851370): 1994 demo album by Blink-182
9. Buddha, also known as Buddhaa-Rajaon Ka Raja, Buddhaa - The King of Kings (wd:Q16954312): TV series
10. Huberht Taylor Hudson, also known as Buddha, Hubert Hudson (wd:Q3787383): British sailor who took part in Shackleton's Imperial Trans-Antarctic Expedition, navigator, sailor

No other items found

[Assistant]
The top result for "Buddha" is the entity representing Siddhartha Gautama, the founder of Buddhism (wd:Q9441). Now, I will find the country where Buddha was born or originated from. I will look for the property related to the place of birth or origin and then find the country associated with that place.

First, let's list the properties related to the place of birth or origin for Buddha.

[Tool]
Got 1 row and 3 columns:
| subject               | property                 | object             |
| --------------------- | ------------------------ | ------------------ |
| The Buddha (wd:Q9441) | place of birth (wdt:P19) | Lumbini (wd:Q9213) |

[Assistant]
The place of birth for Buddha is Lumbini (wd:Q9213). Now, I need to find the country where Lumbini is located. I will search for the property that indicates the country of a place and then find the country associated with Lumbini.

Let's list the properties related to the country for Lumbini.

[Tool]
Got 1 row and 3 columns:
| subject            | property          | object          |
| ------------------ | ----------------- | --------------- |
| Lumbini (wd:Q9213) | country (wdt:P17) | Nepal (wd:Q837) |

[Assistant]
The country where Lumbini is located is Nepal (wd:Q837). Therefore, Buddha came from Nepal.

Now, I will construct the final SPARQL query to confirm this information and provide the answer.

Here is the SPARQL query:

```sparql
SELECT ?country
WHERE {
  wd:Q9441 wdt:P19 ?placeOfBirth .
  ?placeOfBirth wdt:P17 ?country .
}
```

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

[Tool]
Got 1 row and 1 column:
| ?country        |
| --------------- |
| Nepal (wd:Q837) |

[Assistant]
The SPARQL query confirms that Buddha came from Nepal (wd:Q837).

Therefore, the answer to the question "What country did Buddha come from?" is Nepal.

Here is the final SPARQL query and answer:

```sparql
SELECT ?country
WHERE {
  wd:Q9441 wdt:P19 ?placeOfBirth .
  ?placeOfBirth wdt:P17 ?country .
}
```

Answer: Nepal

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?county WHERE {
  wd:Q486472 wdt:P131 ?county .
}

Wyandotte County

[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 county is kansas city kansas?

[Assistant] To determine the county of Kansas City, Kansas, we need to identify the entity representing Kansas City, Kansas, and then find the property that links it to its county. Let's start by searching for the entity representing Kansas City, Kansas.

[Tool]
Top 10 entity alternatives:
1. Kansas City, also known as Kansas City, Missouri, Kansas City, MO, K.C., KC, KCMO (wd:Q41819): city in Missouri, United States
2. Kansas City, also known as Kansas City, Kansas, KCK, Kansas, Kansas, Kansas City, KS (wd:Q486472): city and county seat of Wyandotte County, State of Kansas, United States
3. Kansas City, also known as Kansas City, Kansas, KCK, Kansas City, KS, Kansas, Kansas (wd:Q486472): city and county seat of Wyandotte County, State of Kansas, United States
4. Kansas City (wd:Q977996): 1996 film by Robert Altman
5. Kansas City, also known as K. C. Loving (wd:Q1723915): original song written and composed by Jerry Leiber and Mike Stoller
6. Kansas City, also known as Kansas City, Oregon, Kansas City, OR (wd:Q3709254): unincorporated community in Washington County, Oregon, United States
7. Kansas City/Hey, Hey, Hey, Hey, also known as Kansas City (wd:Q10543339): vocal track by The Beatles
8. Kansas City (wd:Q6364626): US basketball team
9. Kansas City (wd:Q6364628): 2008 single by Sneaky Sound System
10. Kansas City, also known as Kansas City (Oklahoma!) (wd:Q6364632): original song written and composed by Richard Rodgers (music) and Oscar Hammerstein II; from the musical Oklahoma!

No other items found

[Assistant] From the search results, the entity representing Kansas City, Kansas is `wd:Q486472`. Now, let's find the property that links this entity to its county. We can use the `list` function to explore the triples associated with this entity and look for a property that indicates the county.

[Tool]
Got 611 rows and 3 columns, showing the first 10 rows below:
| subject                  | property                                                    | object                                                               |
| ------------------------ | ----------------------------------------------------------- | -------------------------------------------------------------------- |
| Kansas City (wd:Q486472) | instance of (wdt:P31)                                       | county seat (wd:Q62049)                                              |
| Kansas City (wd:Q486472) | country (wdt:P17)                                           | United States (wd:Q30)                                               |
| Kansas City (wd:Q486472) | located in the administrative territorial entity (wdt:P131) | Wyandotte County (wd:Q375652)                                        |
| Kansas City (wd:Q486472) | coordinate location (wdt:P625)                              | POINT(-94.676389 39.106667)                                          |
| Kansas City (wd:Q486472) | Commons category (wdt:P373)                                 | Kansas City, Kansas                                                  |
| Kansas City (wd:Q486472) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Quality-i70.jpg> |
| Kansas City (wd:Q486472) | population (wdt:P1082)                                      | 156607                                                               |
| Kansas City (wd:Q486472) | inception (wdt:P571)                                        | 1868-01-01T00:00:00Z                                                 |
| Kansas City (wd:Q486472) | described by source (wdt:P1343)                             | Encyclopædia Britannica 11th edition (wd:Q867541)                    |
| Kansas City (wd:Q486472) | official name (wdt:P1448)                                   | Kansas City                                                          |
| ...                      | ...                                                         | ...                                                                  |

[Assistant]
From the list of triples, we can see that the property `located in the administrative territorial entity (wdt:P131)` links Kansas City, Kansas (`wd:Q486472`) to Wyandotte County (`wd:Q375652`).

Now, let's construct a SPARQL query to confirm this relationship and return the county.

```sparql
SELECT ?county
WHERE {
  wd:Q486472 wdt:P131 ?county .
}
```

Let's execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| ?county                       |
| ----------------------------- |
| Wyandotte County (wd:Q375652) |

[Assistant]
The SPARQL query confirms that Kansas City, Kansas is located in Wyandotte County.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?county
WHERE {
  wd:Q486472 wdt:P131 ?county .
}
```

Answer: Wyandotte County

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?voiceActor WHERE {
  wd:Q25097 wdt:P175 ?voiceActor .
}

Brad Dourif

[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 does the voice for chucky in child's play?

[Assistant] To answer the question about who provides the voice for Chucky in the "Child's Play" series, we need to identify the character "Chucky" and then find out who voices him. Let's start by searching for "Chucky" in the knowledge graph to find the relevant entity.

[Tool]
Top 10 entity alternatives:
1. Seed of Chucky, also known as Child's Play 5: Seed of Chucky (wd:Q925421): 2004 film directed by Don Mancini
2. Child's Play (wd:Q935945): 1988 film by Tom Holland
3. Child's Play, also known as Childs Play (wd:Q56697304): 2019 film directed by Lars Klevberg
4. Child's Play, also known as Chucky (franchise) (wd:Q2265493): horror film franchise focusing on Chucky, a killer doll
5. Child's Play (wd:Q3966802): 1972 film by Sidney Lumet
6. Child's Play (wd:Q5097661): children's charity
7. Child's Play (wd:Q5097656): episode of Star Trek: Voyager (S6 E19)
8. Child's Play (wd:Q1463844): 1992 film directed by Wolfgang Becker
9. Child's Play (wd:Q5097664): 1994 Marvel Comics storyline
10. Child's Play (wd:Q5097667): 1980s US game show

No other items found

[Assistant] From the search results, it seems that the most relevant entity for "Chucky" in the context of "Child's Play" is the horror film franchise (wd:Q2265493). However, we need to ensure that we are looking at the correct character and not just the franchise. Let's search for "Chucky" as a character to find the specific entity.

[Tool]
Top 10 entity alternatives:
1. character, also known as fictional character (wd:Q95074): fictional human or non-human character in a narrative work of art
2. character (wd:Q366773): relatively permanent traits of an individual relates to various kinds of stimuli, and to the environment
3. Hirving Lozano, also known as Chucky, Hirving Rodrigo Lozano Bahena, Hirving Lozano Bahena, Chucky Lozano (wd:Q17633812): Mexican association football player, association football player
4. character, also known as char, Char, rune (wd:Q32483): primitive data type
5. Character (wd:Q928545): 1997 film directed by Mike van Diem
6. Chucky, also known as The Lakeshore Strangler, Lakeshore Strangler, Good Guy doll, Chucky the murderdoll, Charles Ray (wd:Q25097): horror film villain, serial killer
7. disposition, also known as nature, personage, natural inclination, character (wd:Q1149305): tendency of a person to act in a specified way
8. Chucky (wd:Q106824359): American horror television series
9. character, also known as computer character, computer symbol, sign, symbol, typographical mark (wd:Q3241972): symbol or sign
10. Character (wd:Q1062911): album by Dark Tranquillity

No other items found

[Assistant] The most relevant entity for "Chucky" as a character in the "Child's Play" series is wd:Q25097. Now that we have identified the character, let's find out who provides the voice for Chucky. We will look for properties related to voice actors or performers.

[Tool]
Top 10 property alternatives:
1. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as p/wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
2. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as p/wdt): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
3. 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
4. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
5. 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)
6. 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
7. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as p/wdt): maker of this creative work or other object (where no more specific property exists)
8. 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)
9. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
10. enemy, also known as opponent, rival, archvillain, archrival, archnemesis (wd:P7047 as wdt/p): opponent character or group of this fictive character or group, significant person

No other items found

[Assistant] The property "performer" (wd:P175) seems to be the most relevant for finding the voice actor of Chucky. Let's construct a SPARQL query to find the voice actor for the character Chucky (wd:Q25097).

[Tool]
Got 1 row and 1 column:
| ?voiceActor              |
| ------------------------ |
| Brad Dourif (wd:Q329734) |

[Assistant] The voice actor for Chucky in the "Child's Play" series is Brad Dourif.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?timeZone ?timeZoneLabel WHERE {
  wd:Q84 wdt:P421 ?timeZone .
  OPTIONAL {
    ?timeZone rdfs:label ?timeZoneLabel .
    FILTER ( LANG( ?timeZoneLabel ) = "en" )
  }
}

The time zone of London, UK, is Europe/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] what is london uk time zone?

[Assistant] To determine the time zone of London, UK, I will first search for the entity representing London, UK, and then look for the property that represents the time zone. Let's start by searching for London, UK.

[Tool]
Top 10 entity alternatives:
1. London, also known as Loniniensi, Trinovantum, the Big Smoke, Lundenwic, Lundenburh (wd:Q84): capital and largest city of England and the United Kingdom
2. Transport UK London Bus (wd:Q4666716): bus company operating services in Greater London
3. Case-Based Reasoning Research an...ondon, UK, September 12-15, 2011, also known as ICCBR 2011: London, UK (wd:Q106067800): academic conference
4. Biomedical Simulation, 4th Inter...2008, London, UK, July 7-8, 2008, also known as ISBMS 2008: London, UK (wd:Q106245166): academic conference
5. ACM SIGCOMM '94 Conference on Co...K, August 31 - September 2, 1994, also known as SIGCOMM 1994: London, UK (wd:Q106304259): academic conference
6. 2014 International Conference on...ed Kingdom, September 8-12, 2014, also known as ICCAC 2014: London, UK (wd:Q106335891): academic conference
7. 2017 International Conference On...United Kingdom, June 19-20, 2017, also known as CyberSA 2017: London, UK (wd:Q106336151): academic conference
8. 21st ACM SIGPLAN/SIGBED Internat... 2020, London, UK, June 16, 2020, also known as LCTES 2020: London, UK (wd:Q106303884): academic conference
9. 7th 2016 International Conferenc..., London, UK, July 11 - 13, 2016, also known as SMSociety 2016: London, UK (wd:Q106337600): academic conference
10. 5th International Conference on ...ondon, UK, September 29-30, 2008, also known as iPRES 2008: London, UK (wd:Q106336198): academic conference

No other items found

[Assistant] The top result for "London, UK" is `wd:Q84`, which represents the capital and largest city of England and the United Kingdom. Now, I will search for the property that represents the time zone and see if it is associated with `wd:Q84`.

[Tool]
Top 10 property alternatives:
1. located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt/p): time zone for this item
2. 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
3. continent (wd:P30 as wdt/p): continent of which the subject is a part, located in/on physical feature
4. 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
5. 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
6. local dialing code, also known as area code, dialling code, local calling code, local dialling code, STD code (wd:P473 as p/wdt): identifier dedicated to subject city by the area communication network
7. postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt/p): identifier assigned by postal authorities for the subject area or building
8. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as wdt/p): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
9. 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
10. detail map, also known as map (wd:P1621 as wdt/p): map containing details about the entire location, locator map image

No other items found

[Assistant]
The top result for the property "time zone" is `wdt:P421`. This property seems to represent the time zone for the entity. Now, I will construct a SPARQL query to retrieve the time zone of London, UK (`wd:Q84`).

Let's execute the query:

```sparql
SELECT ?timeZone
WHERE {
  wd:Q84 wdt:P421 ?timeZone .
}
```

This query will return the time zone of London, UK.

[Tool]
Got 4 rows and 1 column:
| ?timeZone                       |
| ------------------------------- |
| Europe/London (wd:Q16894228)    |
| Greenwich Mean Time (wd:Q30192) |
| UTC±00:00 (wd:Q6574)            |
| UTC+01:00 (wd:Q6655)            |

[Assistant]
The query returned multiple time zones associated with London, UK. These include:

- `Europe/London` (wd:Q16894228)
- `Greenwich Mean Time` (wd:Q30192)
- `UTC±00:00` (wd:Q6574)
- `UTC+01:00` (wd:Q6655)

To provide a more precise answer, I will check the labels of these time zones to understand their context better. However, the most commonly recognized time zone for London, UK, is `Europe/London`.

Let's confirm this by fetching the labels of these time zones.

```sparql
SELECT ?timeZone ?timeZoneLabel
WHERE {
  wd:Q84 wdt:P421 ?timeZone .
  OPTIONAL { ?timeZone rdfs:label ?timeZoneLabel . FILTER(LANG(?timeZoneLabel) = "en") }
}
```

This query will return the time zones along with their English labels.

[Tool]
Got 4 rows and 2 columns:
| ?timeZone                       | ?timeZoneLabel      |
| ------------------------------- | ------------------- |
| Europe/London (wd:Q16894228)    | Europe/London       |
| Greenwich Mean Time (wd:Q30192) | Greenwich Mean Time |
| UTC±00:00 (wd:Q6574)            | UTC±00:00           |
| UTC+01:00 (wd:Q6655)            | UTC+01:00           |

[Assistant]
The query returned the time zones along with their English labels:

- `Europe/London` (wd:Q16894228)
- `Greenwich Mean Time` (wd:Q30192)
- `UTC±00:00` (wd:Q6574)
- `UTC+01:00` (wd:Q6655)

The most commonly recognized time zone for London, UK, is `Europe/London`. This time zone encompasses both GMT (Greenwich Mean Time) and BST (British Summer Time), which is UTC+01:00 during daylight saving time.

Therefore, the time zone of London, UK, is `Europe/London`.

Here is the final SPARQL query and answer:

```sparql
SELECT ?timeZone ?timeZoneLabel
WHERE {
  wd:Q84 wdt:P421 ?timeZone .
  OPTIONAL { ?timeZone rdfs:label ?timeZoneLabel . FILTER(LANG(?timeZoneLabel) = "en") }
}
```

The time zone of London, UK, is `Europe/London`.

[Tool] Stopped generation process