PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
SELECT ?voiceActor ?voiceActorLabel ?startTime WHERE {
  wd:Q908772 p:P725 ?statement .
  ?statement ps:P725 ?voiceActor .
  OPTIONAL {
    ?statement pq:P580 ?startTime
  }
  OPTIONAL {
    ?voiceActor rdfs:label ?voiceActorLabel FILTER ( LANG( ?voiceActorLabel ) = "en" )
  }
}
ORDER BY ?startTime
LIMIT 1

The original voice actor of Meg Griffin on Family Guy is Lacey Chabert, as she has the earliest start time qualifier among the voice actors listed.

[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 originally voiced meg on family guy?

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

[Tool]
Example 1:
Question:
who is chelsea kane?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q205794 wdt:P106 ?x .
}

Using entities:
Chelsea Kane, also known as Chelsea Kane Staub, Chelsea Staub (wd:Q205794): American actress and singer, television actor, voice actor, film actor, singer, actor

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

Example 2:
Question:
where did gary coleman live when he died?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q313367 wdt:P20 ?x .
}

Using entities:
Gary Coleman, also known as Gary Wayne Coleman (wd:Q313367): American actor (1968–2010), television director, television actor, film director, film producer, screenwriter, voice actor, comedian, actor

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

Example 3:
Question:
who played mason capwell?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q1965740 .
}

Using entities:
Mason Capwell (wd:Q1965740)

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

[Assistant]
The question is "Who originally voiced Meg on Family Guy?" We want to find the original voice actor for the character Meg Griffin from the TV show Family Guy.

Step 1: Identify the entity for "Meg Griffin" from Family Guy.
Step 2: Identify the property that links a character to their voice actor.
Step 3: Query for the original voice actor of Meg Griffin.

I will start by searching for the entity "Meg Griffin" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Meg Griffin, also known as Megan Griffin, Megatron "Meg" Harvey Oswald Griffin, Megatron Harvey Oswald Griffin, Megan "Meg" Griffin (wd:Q908772): fictional character from the Family Guy franchise, high school student
2. Meg Griffin (wd:Q6807983): American radio disc jockey, radio personality, disc jockey
3. Megan Kate Griffin-Pickering (wd:Q103292935): Ph.D. University of Cambridge 2019
4. griffin, also known as griffon, gryphon (wd:Q130223): legendary animal
5. Griffin, also known as Griffin, GA, Griffin, Georgia (wd:Q1012372): county seat of Spalding County, Georgia, United States
6. The Meg, also known as Meg, The Meg IMAX 2D, The Meg IMAX 3D (wd:Q27957869): 2018 film by Jon Turteltaub
7. (RS)-propylene glycol, also known as methylethylene glycol, methyl ethyl glycol, methylethyl glycol, HOCH2CH(OH)CH3, methyl glycol (wd:Q161495): pair of enantiomers
8. Heinkel He 177 Greif, also known as Luftwaffe's Lighter, Luftwaffenfeuerzeug, Griffin, Heinkel 177, Greif (wd:Q316321): 1939 heavy bomber family by Heinkel
9. Griffin, also known as Griffin, IN, Griffin, Indiana (wd:Q2096172): town in Indiana, USA
10. 4995 Griffin, also known as Griffin (wd:Q389857): asteroid

[Assistant] The entity "Meg Griffin" from the Family Guy franchise is wd:Q908772. Next, I need to find the property that links a fictional character to their voice actor. I will search for properties related to "voice actor" for the entity Meg Griffin (wd:Q908772).

[Tool]
Top 10 property alternatives:
1. voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as p/wdt): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member
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 p/wdt): date on which the subject was born, inception
4. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as p/wdt): full name of a person at birth, if different from their current, generally used name, name
5. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
6. media franchise, also known as franchise, mass media franchise, media mix, presented in media franchise (wd:P8345 as p/wdt): this creative work belongs to this media franchise
7. first appearance, also known as debut, present initially in, introduced in work, initial appearance, first film (wd:P4584 as p/wdt): work in which a fictional/mythical character or entity first appeared, present in work
8. from narrative universe, also known as from narrative, in continuity, from universe, in cycle, in world of (wd:P1080 as p/wdt): subject's fictional entity is in the object narrative. See also P1441 (present in work) and P1445 (fictional universe described in), part of
9. birthday, also known as b-day, bday, birth day (wd:P3150 as p/wdt): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
10. 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)

No other items found

[Assistant] The property "voice actor" (wdt:P725) is the correct property to link a fictional character to their voice actor. Now I will query for the voice actors of Meg Griffin (wd:Q908772). Since the question asks for the original voice actor, I will try to find the earliest voice actor if possible. I will start with a simple query to get all voice actors for Meg Griffin.

[Tool]
Got 2 rows and 2 columns:
| voiceActor                 | voiceActorLabel    |
| -------------------------- | ------------------ |
| Lacey Chabert (wd:Q232910) | Lacey Chabert (en) |
| Mila Kunis (wd:Q37628)     | Mila Kunis (en)    |

[Assistant] Meg Griffin has two voice actors listed: Lacey Chabert and Mila Kunis. To determine who originally voiced Meg, I will check if there is any qualifier or statement indicating the original or first voice actor. I will look for statements about the voice actor property for Meg Griffin.

[Tool]
Got 2 rows and 3 columns:
| subject                  | property               | object                     |
| ------------------------ | ---------------------- | -------------------------- |
| Meg Griffin (wd:Q908772) | voice actor (wdt:P725) | Mila Kunis (wd:Q37628)     |
| Meg Griffin (wd:Q908772) | voice actor (wdt:P725) | Lacey Chabert (wd:Q232910) |

[Assistant] The direct property statements do not show qualifiers about which voice actor was the original. I will now check the detailed statements (not just direct properties) for the voice actor property of Meg Griffin to see if there are qualifiers indicating the original or first voice actor.

[Tool]
Got 2 rows and 3 columns:
| subject                  | property             | object                                         |
| ------------------------ | -------------------- | ---------------------------------------------- |
| Meg Griffin (wd:Q908772) | voice actor (p:P725) | s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d |
| Meg Griffin (wd:Q908772) | voice actor (p:P725) | s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba |

[Assistant] There are two statements for the voice actor property with statement nodes. I will now check the qualifiers of these statements to see if there is any indication of which voice actor was the original. I will look at the qualifiers of the statement nodes.

[Tool]
Got 6 rows and 3 columns:
| subject                                        | property              | object                              |
| ---------------------------------------------- | --------------------- | ----------------------------------- |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | start time (pq:P580)  | 1999-12-26T00:00:00Z (xsd:dateTime) |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | voice actor (ps:P725) | Mila Kunis (wd:Q37628)              |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | wikibase:rank         | wikibase:NormalRank                 |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | rdf:type              | wikibase:BestRank                   |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | start time (pqv:P580) | v:f3464911887585a185abfe9a3a6348d1  |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | rdf:type              | wikibase:Statement                  |

[Tool]
Got 18 rows and 3 columns, showing the first 10 rows below:
| subject                                        | property              | object                                |
| ---------------------------------------------- | --------------------- | ------------------------------------- |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | start time (pq:P580)  | 1999-01-31T00:00:00Z (xsd:dateTime)   |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | end time (pq:P582)    | 1999-09-30T00:00:00Z (xsd:dateTime)   |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | voice actor (ps:P725) | Lacey Chabert (wd:Q232910)            |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | pq:P10663             | Death Has a Shadow (wd:Q1191505)      |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | wikibase:rank         | wikibase:NormalRank                   |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | rdf:type              | wikibase:BestRank                     |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | start time (pqv:P580) | v:4d3b247501548c614f1e15774931d252    |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | end time (pqv:P582)   | v:82dcc86a69d08b486bc109e94c737a9d    |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | pq:P10663             | I Never Met the Dead Man (wd:Q253099) |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | pq:P10663             | Chitty Chitty Death Bang (wd:Q860840) |
| ...                                            | ...                   | ...                                   |

[Assistant]
The statement with voice actor Mila Kunis has a start time qualifier of 1999-12-26. The statement with voice actor Lacey Chabert has a start time qualifier of 1999-01-31 and an end time qualifier of 1999-09-30. This indicates that Lacey Chabert originally voiced Meg Griffin from January 31, 1999, to September 30, 1999, and Mila Kunis took over the role starting December 26, 1999.

I will now create a SPARQL query to return the original voice actor of Meg Griffin based on the earliest start time qualifier for the voice actor property.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query attempts to find the original voice actor of Meg Griffin by looking for the earliest start time qualifier on the voice actor property. However, the query returns no results, indicating that the data might be missing or the query logic is not correctly capturing the original voice actor. The property P725 (voice actor) is used correctly, but the qualifier P580 (start time) might not be present or used differently in Wikidata for this character. It is recommended to revise the query to check for voice actors without relying solely on the start time qualifier or to consider alternative properties or qualifiers that indicate the original voice actor. Additionally, ensure that the entity for Meg Griffin (wd:Q908772) is correct and that the voice actor data is available in Wikidata. The answer given (Lacey Chabert) is correct based on external knowledge, but the query does not confirm it. The system should retry with a refined query that can retrieve the original voice actor without depending on the start time qualifier or by using a different approach.

[Assistant]
Thank you for the feedback. I understand that the previous query did not return results because it relied solely on the start time qualifier, which might not be consistently present or used in Wikidata for this character.

I will revise the approach to retrieve all voice actors for Meg Griffin along with their start and end times if available, and then order by start time to get the earliest voice actor. This way, even if some statements lack qualifiers, we can still identify the original voice actor by sorting.

I will write a query that retrieves voice actors with optional start and end times and orders by start time ascending, limiting to 1 result to get the original voice actor.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the voice actors of Meg Griffin and orders them by the start time qualifier to identify the original voice actor. The answer that Lacey Chabert is the original voice actor is supported by the earliest start time in the query result. The query follows best practices by returning the actual identifiers and labels optionally, and it uses the appropriate properties. No further refinement is needed.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coordinate WHERE {
  wd:Q2118432 wdt:P625 ?coordinate .
}

Jenni Rivera's body was found at the crash site of the 2012 Mexico Learjet 25 crash. The precise location of the crash site is given by the coordinates POINT(-99.871667 24.763889).

[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 they find jenni rivera's body?

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

[Tool]
Example 1:
Question:
what is phoebe halliwell's real name?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q1639574 .
}

Using entities:
Phoebe Halliwell (wd:Q1639574): fictional character from the television series Charmed, witch in a work of fiction, demonologist, columnist, reporter, writer

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

Example 2:
Question:
what is jill wagner on wipeout?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q52497 p:P161 ?p .
  ?p ps:P161 wd:Q432993 ; pq:P453 ?x .
}

Using entities:
Jill Wagner, also known as Jill Suzanne Wagner (wd:Q432993): television personality, American actress, actor
Wipeout, also known as Wipeout USA (wd:Q52497): American reality game show

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

Example 3:
Question:
who was johnny cash's first wife?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q42775 p:P26 ?p .
  ?p ps:P26 ?x ; pq:P580 ?y .
}
ORDER BY ?y
LIMIT 1

Using entities:
Johnny Cash, also known as The Man in Black, John R. Cash, J. R. Cash (wd:Q42775): American country singer (1932–2003), singer-songwriter, guitarist, actor

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/ps): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time

[Assistant] The examples found are not directly related to the question about where Jenni Rivera's body was found. Next, I will search for the entity "Jenni Rivera" in Wikidata to identify her Wikidata entity ID. Then, I will look for properties related to the location of her body being found.

[Tool]
Top 10 entity alternatives:
1. Jenni Rivera, also known as Jenny Rivera, Dolores Janney Rivera Saavedra (wd:Q714185): American singer (1969–2012), television producer, singer-songwriter, recording artist, record producer, businessperson, film actor, composer, singer, actor
2. Jennifer Rivera (wd:Q22088654): American opera singer, opera singer
3. Jennifer Rivera (wd:Q99230893): rhythmic gymnast
4. Jenni Rivera Fashion (wd:Q18359270): web-based fashion boutique
5. Jenni Rivera: Mariposa de Barrio, also known as Mariposa de Barrio (wd:Q29267690): television series
6. Jenniffer López, also known as Jenniffer Katherine Lopez Rivera (wd:Q26131407): weightlifter
7. Jenni Rivera, Mexican-American Singer, Dies at 43 (wd:Q123654230): The New York Times article (December 10, 2012)
8. Rivera (wd:Q646498): city in Uruguay
9. Rivera (wd:Q1526269): Colombian municipality of the department of Huila
10. Rivera, also known as Rivera, Switzerland, Rivera TI (wd:Q663061): village and former municipality in Mendrisio in the canton of Ticino, Switzerland

[Assistant] The entity for Jenni Rivera is wd:Q714185. Now I will search for properties related to "body" or "found" for this entity to find relevant information about where her body was found.

[Tool]
Top 10 property alternatives:
1. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as p/wdt): 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 p/wdt): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
3. 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 p/wdt): identifier of an individual's burial place in the Find a Grave database
4. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as p/wdt): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
5. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as p/wdt): dissolved, abolished or demolished date, date on which the subject died, end time
6. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. 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. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
9. 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
10. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

No other items found

[Assistant] The properties place of death (wdt:P20) and place of burial (wdt:P119) seem relevant to the question about where Jenni Rivera's body was found. I will now query these properties for Jenni Rivera to see if the location where her body was found is mentioned.

[Tool]
Got 1 row and 4 columns:
| placeOfDeath             | placeOfDeathLabel | placeOfBurial                   | placeOfBurialLabel      |
| ------------------------ | ----------------- | ------------------------------- | ----------------------- |
| Iturbide (wd:Q116918876) | Iturbide (en)     | Los Angeles County (wd:Q104994) | Los Angeles County (en) |

[Assistant] Jenni Rivera's place of death is Iturbide, and her place of burial is Los Angeles County. However, the specific location where her body was found is not explicitly stated in these properties. I will now check if there is any significant event related to her death that might mention the location where her body was found.

[Tool]
Got 1 row and 2 columns:
| event                                      | eventLabel                        |
| ------------------------------------------ | --------------------------------- |
| 2012 Mexico Learjet 25 crash (wd:Q2118432) | 2012 Mexico Learjet 25 crash (en) |

[Assistant] There is a significant event related to Jenni Rivera's death called the "2012 Mexico Learjet 25 crash." This event likely relates to where her body was found. I will now query the location of this event to provide a more precise answer.

[Tool] Got no rows and 2 columns

[Assistant] The significant event "2012 Mexico Learjet 25 crash" does not have a direct location property (wdt:P276) specified in Wikidata. I will try to find other location-related properties for this event to identify where it happened and thus where Jenni Rivera's body was found.

[Tool]
Got 12 rows and 4 columns, showing the first 5 and last 5 rows below:
| property                                        | propertyLabel | value                                        | valueLabel             |
| ----------------------------------------------- | ------------- | -------------------------------------------- | ---------------------- |
| number of injured (wdt:P1339)                   |               | 0 (xsd:decimal)                              |                        |
| number of deaths (wdt:P1120)                    |               | 7 (xsd:decimal)                              |                        |
| Aviation Safety Network accident ID (wdt:P1755) |               | 20121209-0                                   |                        |
| Freebase ID (wdt:P646)                          |               | /m/0pcvld6                                   |                        |
| vessel (wdt:P1876)                              |               | Learjet 25 (wd:Q1340723)                     | Learjet 25 (en)        |
| ...                                             | ...           | ...                                          | ...                    |
| instance of (wdt:P31)                           |               | aviation accident (wd:Q744913)               | aviation accident (en) |
| wdt:P31279                                      |               | aviation accident (wd:Q744913)               | aviation accident (en) |
| country (wdt:P17)                               |               | Mexico (wd:Q96)                              | Mexico (en)            |
| point in time (wdt:P585)                        |               | 2012-12-09T00:00:00Z (xsd:dateTime)          |                        |
| coordinate location (wdt:P625)                  |               | POINT(-99.871667 24.763889) (geo:wktLiteral) |                        |

[Assistant] The "2012 Mexico Learjet 25 crash" event has a coordinate location (wdt:P625) with the value POINT(-99.871667 24.763889) and is located in Mexico (wdt:P17). This is likely the location where Jenni Rivera's body was found after the crash. I will now finalize the answer with this information.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query retrieves the country and coordinates of the 2012 Mexico Learjet 25 crash, which is related to Jenni Rivera's death. However, it does not explicitly state the exact location where Jenni Rivera's body was found. The query uses the property 'country' (wdt:P17) on the crash event, which returns the country Mexico, but this is too broad. It would be better to use the coordinate location (wdt:P625) directly on the crash event to get the precise location, and also clarify in the answer that the body was found at the crash site. Additionally, the query should not use the 'country' property on the crash event as it is not the most precise location. The answer should explicitly mention that the body was found at the crash site, not just in Mexico. Therefore, the query and answer need refinement to better reflect the exact location of the body.

[Assistant] Thank you for the feedback. I will refine the SPARQL query to directly retrieve the coordinate location of the 2012 Mexico Learjet 25 crash event without using the country property. I will also clarify in the answer that Jenni Rivera's body was found at the crash site.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the coordinates of the crash site where Jenni Rivera's body was found, using the entity for the 2012 Mexico Learjet 25 crash and the coordinate location property. The answer is accurate and complete, providing the precise location as requested. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?currency ?currencyLabel WHERE {
  wd:Q29 wdt:P38 ?currency .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| currency        | currencyLabel |
| --------------- | ------------- |
| Euro (wd:Q4916) | euro (en)     |

The currency used by Spain is the Euro (wd:Q4916).

[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 money does spain use?

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

[Tool]
Example 1:
Question:
what are the 5 countries in the united kingdom?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q145 wdt:P150 ?x .
}
LIMIT 5

Using entities:
United Kingdom, also known as U.K., UK, U. K., U K, United Kingdom of Great Britain and Northern Ireland (wd:Q145): country in north-west Europe

Using properties:
contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as wdt): (list of) direct subdivisions of an administrative territorial entity, has part(s)

Example 2:
Question:
what movies has billy burke been in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q325020 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Billy Burke, also known as William Albert "Billy" Burke, William Albert Burke (wd:Q325020): American actor, musician, television actor, film producer, screenwriter, film actor, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
what condition does michael j fox have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q395274 wdt:P1050 ?x .
}

Using entities:
Michael J. Fox, also known as Michael Fox, Michael J Fox, Michael Andrew Fox (wd:Q395274): Canadian-American actor, comedian, author, film producer, and activist with a film and television career, television producer, television actor, autobiographer, voice actor, film actor, blogger, actor

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

[Assistant]
The question is "what money does Spain use?" which means we want to find the currency used by Spain.

Step 1: Identify the entity for Spain.
Step 2: Identify the property that relates a country to its currency.
Step 3: Query the currency used by Spain.

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

[Tool]
Top 10 entity alternatives:
1. Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa
2. Spain men's national football team, also known as La Furia, The Spanish Fury, The Red One, The Red Fury, The Fury (wd:Q42267): men's national association football team representing Spain
3. Second Spanish Republic, also known as Spain (wd:Q178038): political regime established in Spain between April 14, 1931 and April 1, 1939
4. New Spain, also known as Colonial Central America, Central America under Spain, Viceroyalty of New Spain, Spanish Mexico, Spanish Central America (wd:Q170603): viceroyalty of the Spanish Empire (1535-1821)
5. Spain under the Restoration, also known as Bourbon Restoration, Spain, Second Bourbon Restoration, Restoration, Restoration (Spain) (wd:Q1044536): name given to a period between 1874 (end of First Spanish Republ...econd Spanish Republic), and the state of Spain during that time
6. Kingdom of Spain (1820-1823), also known as Kingdom of Spain, Spain, Trienio Liberal (wd:Q238809): 1820–1823 Spanish political period
7. Spain under Joseph Bonaparte, also known as Kingdom of Spain, Napoleonic Spain, Spain (wd:Q1709185): Napoleonic client state (1808–1813)
8. Sexenio Democrático, also known as Kingdom of Spain, Spain (wd:Q12411956): 1868–1874 period of fu under a provisional government
9. Ominous Decade, also known as Kingdom of Spain, second restoration of absolutism, Spain (wd:Q2378204): period in the history of Spain, corresponding to the second rest...reign of Fernando VII from August 31, 1823 to September 29, 1833
10. Hispanic Monarchy, also known as Spains, Hispanic Crown, Spain, Kingdom of Spains, Crown of Spain (wd:Q766543): (1479-1716) set of territories distributed throughout the world,...monarch and corresponding to the period of the House of Habsburg

[Assistant]
The entity for Spain is wd:Q29 (Kingdom of Spain).

Next, I will search for the property that relates a country to its currency. I will search for properties related to "currency" or "money" for the entity Spain.

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as p/wdt): currency used by item, uses
2. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as p/wdt): market value of all officially recognized final goods and services produced within a country in a given period of time
3. flag, also known as flag description (wd:P163 as p/wdt): subject's flag
4. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. 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
6. The New Yorker topic ID, also known as TNY ID, The NewYorker topic ID, New Yorker topic ID, NewYorker topic ID, newyorker.com (wd:P13317 as p/wdt): identifier of a topic on The New Yorker website
7. 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)
8. continent (wd:P30 as p/wdt): 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 p/wdt): time zone for this item

No other items found

[Assistant]
The property "currency" (wdt:P38) is the one that relates a country to its currency.

Now I will write a SPARQL query to get the currency used by Spain (wd:Q29) using the property wdt:P38. I will also include the label of the currency for better readability.

[Tool]
Got 1 row and 2 columns:
| currency        | currencyLabel |
| --------------- | ------------- |
| Euro (wd:Q4916) | euro (en)     |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the currency used by Spain (wd:Q29) using the property wdt:P38 (currency). The query also optionally fetches the English label of the currency. The result correctly identifies the Euro (wd:Q4916) as the currency used by Spain. The answer is accurate and complete, and the query follows the rules for returning identifiers and labels. No further refinement is needed.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?language ?languageLabel WHERE {
  wd:Q34 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| Swedish (wd:Q9027) | Swedish (en)  |

The official language spoken in Sweden is Swedish.

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

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

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

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

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

[User] what language do they speak in sweden yahoo?

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

[Tool]
Example 1:
Question:
where are brembo brakes from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q907265 wdt:P159 ?x .
}

Using entities:
Brembo, also known as Brembo S.p.A., Freni Brembo S.p.A. (wd:Q907265): Italian automotive brake systems manufacturer

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

Example 2:
Question:
who plays mary jane in spiderman 3?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q182212 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q63729056 .
}

Using entities:
Spider-Man 3 (wd:Q182212): 2007 American film directed by Sam Raimi
Mary Jane Watson (wd:Q63729056): 2002-2007 Spider-Man film series character, high school student, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

Example 3:
Question:
who played eowyn in the lord of the rings movies?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q716565 .
}

Using entities:
Éowyn, also known as Dernhelm (wd:Q716565): fictional character from J.R.R. Tolkien's legendarium

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

[Assistant]
The question is about the language spoken in Sweden. The entity to focus on is "Sweden." We want to find the language spoken in Sweden. The property we are interested in is likely "official language" or "language spoken."

Next, I will search for the entity "Sweden" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Sweden, also known as Swedish Kingdom, Konungariket Sverige, SWE, se, Kingdom of Sweden (wd:Q34): country in Northern Europe
2. Sweden, also known as Kingdom of Sweden, Konungariket Sverige, se, Swedish Kingdom, Sverige (wd:Q34): country in Northern Europe
3. Sweden, also known as Sweden, Maine, Sweden, ME (wd:Q3450805): town in Oxford County, Maine, USA
4. Sweden, also known as Sweden, NY, Sweden, New York (wd:Q3709888): town in New York, USA
5. Sweden (wd:Q7654287): constituency of the European Parliament
6. Sweden, also known as Sweden, AR, Sweden, Arkansas (wd:Q7654280): unincorporated community in Jefferson County, Arkansas
7. Sweden, also known as Sweden, Missouri, Sweden, MO (wd:Q27985021): unincorporated community in Missouri
8. Sweden, also known as Sweden, Georgia (wd:Q65049788)
9. Curators of Sweden, also known as @sweden, twitter.com/sweden (wd:Q5194619): Swedish social media campaign, Twitter account
10. Sweden (wd:Q12004480): musical group from Oslo, Norway

[Assistant] The entity for the country Sweden is wd:Q34. Now I will search for properties related to language for this entity. Likely properties are "official language" or "language spoken." I will search for properties of Sweden related to language.

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as p/wdt): language designated as official by this item, language used
2. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as p/wdt): language widely used (spoken or written) in this place or at this event or organisation
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
5. culture, also known as archaeological culture, civilisation, civilization (wd:P2596 as p/wdt): human culture or people (or several cultures) associated with this item, part of
6. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
7. 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
8. Libraries Australia ID, also known as CNLKIN, NLA Kinetica Service identifier, NLA (Australia) identifier, NLA (Australia) ID, Libraries Australia identifier (wd:P409 as p/wdt): identifier issued by the National Library of Australia (see also...F component. Format: 1-12 digits, removing leading zero-padding.
9. Unicode character, also known as emoji, emote, pictograph, Unicode symbol (wd:P487 as p/wdt): Unicode character representing the item (only if this is not a c...acter or a compatiblity character: in that case, use only P4213)
10. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category

No other items found

[Assistant] The property "official language" (wdt:P37) is the most relevant for the question about the language spoken in Sweden. I will now write a SPARQL query to get the official language(s) of Sweden (wd:Q34).

[Tool]
Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| Swedish (wd:Q9027) | Swedish (en)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the official language spoken in Sweden using the property 'official language' (wdt:P37). It returns the language identifier and its English label, which is Swedish. The answer provided is accurate and complete. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?genre ?genreLabel WHERE {
  wd:Q1203 wdt:P136 ?genre .
  ?genre rdfs:label ?genreLabel .
  FILTER ( LANG( ?genreLabel ) = "en" )
}

Got 11 rows and 2 columns, showing the first 5 and last 5 rows below:
| genre                            | genreLabel              |
| -------------------------------- | ----------------------- |
| rock music (wd:Q11399)           | rock music (en)         |
| experimental music (wd:Q1640319) | experimental music (en) |
| experimental rock (wd:Q1641839)  | experimental rock (en)  |
| blues rock (wd:Q193355)          | blues rock (en)         |
| psychedelic rock (wd:Q206159)    | psychedelic rock (en)   |
| ...                              | ...                     |
| pop music (wd:Q37073)            | pop music (en)          |
| pop rock (wd:Q484641)            | pop rock (en)           |
| beat music (wd:Q546264)          | beat music (en)         |
| rock and roll (wd:Q7749)         | rock and roll (en)      |
| hard rock (wd:Q83270)            | hard rock (en)          |

John Lennon sang various types of music including rock music, experimental music, experimental rock, blues rock, psychedelic rock, pop music, pop rock, beat music, rock and roll, and hard rock.

[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 music did john lennon sing?

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

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

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

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

Using properties:
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

Example 2:
Question:
what influenced langston hughes to write?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q188093 wdt:P737 ?x .
}

Using entities:
Langston Hughes, also known as James Langston Hughes, James Mercer Langston Hughes (wd:Q188093): (1901-1967) American writer and social activist, opinion journalist, children's writer, biographer, journalist, playwright, novelist, essayist, writer, poet

Using properties:
influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as wdt): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”

Example 3:
Question:
who miley cyrus engaged to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q4235 wdt:P26 ?x .
}

Using entities:
Miley Cyrus, also known as Miley Ray Hemsworth, Miley Ray Cyrus, Miley Cyrus Love, Smiley Miley, Miley R. Cyrus (wd:Q4235): American singer, actress, and television personality (born 1992), television producer, singer-songwriter, television actor, voice actor, film actor, composer, singer, actor

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

[Assistant]
The question is about the type of music John Lennon sang. This relates to John Lennon as an entity and the type or genre of music as a property.

Step 1: Identify John Lennon entity in Wikidata.
Step 2: Identify properties related to music genre or type of music for John Lennon.
Step 3: Query the type of music John Lennon sang.

I will start by searching for the entity "John Lennon" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. John Lennon, also known as John Winston Ono Lennon, John Ono Lennon (wd:Q1203): British musician (1940–1980), political activist, singer-songwriter, recording artist, record producer, peace activist, public figure, film director, film producer, prose writer, film actor, guitarist, composer, painter, pianist, singer, writer, actor, poet
2. Liverpool John Lennon Airport, also known as John Lennon, John Lennon airport, Liverpool Airport, Liverpool (John Lennon), LPL (wd:Q8727): airport in Liverpool, England
3. John Lennon Silva Santos, also known as John Lennon (wd:Q6244563): association football player, Brazilian footballer
4. John Brown Lennon, also known as John B. Lennon, John Lennon (wd:Q6223555): American labor leader (1850–1923), trade unionist
5. John Lennon, also known as J. John Lennon, Justin John Lennon (wd:Q11979004): Scottish tourism researcher, university teacher, tourism scholar
6. John Lennon (wd:Q65548791): Irish hurler born 1996
7. John Lennon (wd:Q6244553): British naval captain, military personnel
8. John Lennon (wd:Q12871620): 1855 - 3 Aug 1921
9. John Lennon (wd:Q125643070): 2005 edition of written work by Jordi Sierra i Fabra
10. John Lennon (wd:Q106781630): 2015 song by SCH

[Assistant] The entity for John Lennon as the British musician and singer-songwriter is wd:Q1203. Next, I will search for properties related to the type or genre of music for this entity. I will search for properties related to "music genre" or "type of music" for John Lennon (wd:Q1203).

[Tool]
Top 10 property alternatives:
1. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
2. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as p/wdt): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
3. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as p/wdt): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
4. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as p/wdt): musical instrument that a person plays or teaches or used in a music occupation, uses
5. record label, also known as label, labels (wd:P264 as p/wdt): brand and trademark associated with the marketing of subject music recordings and music videos
6. Apple Music artist ID (U.S. version), also known as iTunes author ID, music.apple.com/artist/, iTunes artist ID (American version), https://music.apple.com/artist/, Apple Music artist ID (American version) (wd:P2850 as p/wdt): identifier for a musical artist or author in the U.S. version of Apple Music
7. voice type, also known as range of voice, register, tessitura, type of voice, vocal type (wd:P412 as p/wdt): person's voice type. expected values: soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass (and derivatives)
8. MusicBrainz artist ID, also known as MB artist ID, MBID artist (wd:P434 as wdt/p/wdtn): identifier for an artist in the MusicBrainz open music encyclopedia
9. Songfacts artist ID (wd:P5287 as p/wdt): identifier for an artist on the Songfacts website
10. discography, also known as discography link, recording catalog (wd:P358 as p/wdt): item for list pages with discography of artist or band, list of works

No other items found

[Assistant] The property "genre" (wdt:P136) is the relevant property for the type or genre of music. Now I will query the genres of music associated with John Lennon (wd:Q1203) using this property.

[Tool]
Got 11 rows and 2 columns, showing the first 5 and last 5 rows below:
| genre                            | genreLabel              |
| -------------------------------- | ----------------------- |
| rock music (wd:Q11399)           | rock music (en)         |
| experimental music (wd:Q1640319) | experimental music (en) |
| experimental rock (wd:Q1641839)  | experimental rock (en)  |
| blues rock (wd:Q193355)          | blues rock (en)         |
| psychedelic rock (wd:Q206159)    | psychedelic rock (en)   |
| ...                              | ...                     |
| pop music (wd:Q37073)            | pop music (en)          |
| pop rock (wd:Q484641)            | pop rock (en)           |
| beat music (wd:Q546264)          | beat music (en)         |
| rock and roll (wd:Q7749)         | rock and roll (en)      |
| hard rock (wd:Q83270)            | hard rock (en)          |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the music genres associated with John Lennon using the property wdt:P136 (genre). The query returns the genres' identifiers and their English labels, which directly answer the user's question about the types of music John Lennon sang. The answer is comprehensive and includes a variety of relevant music genres. The query follows the rules by returning identifiers and labels, filtering labels by English language, and does not perform any post-processing outside SPARQL. Overall, the output is correct and complete.


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:Q39607 wdt:P20 ?placeOfDeath .
  OPTIONAL {
    ?placeOfDeath rdfs:label ?placeOfDeathLabel FILTER ( LANG( ?placeOfDeathLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| placeOfDeath                      | placeOfDeathLabel         |
| --------------------------------- | ------------------------- |
| place de la Concorde (wd:Q189503) | place de la Concorde (en) |

Antoine Lavoisier died at Place de la Concorde.

[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 antoine lavoisier die?

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

[Tool]
Example 1:
Question:
where did sergio romo go to college?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q3041597 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q38723 .
}

Using entities:
Sergio Romo, also known as Sergio Francisco Romo (wd:Q3041597): American baseball pitcher, baseball player
higher education institution, also known as HEI, Higher Education school, institution of higher education, Superior Institute (wd:Q38723): institution that provides higher education (e.g., universities, ...es, liberal arts colleges, institutes of technology, and others)

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

Example 2:
Question:
where did roger moore live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q134333 wdt:P551 ?x .
}

Using entities:
Roger Moore, also known as Sir Roger Moore, Sir Roger George Moore (wd:Q134333): English actor (1927–2017), television producer, television director, military personnel, television actor, autobiographer, film producer, voice actor, stage actor, film actor, actor

Using properties:
residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as wdt): the place where the person is or has been, resident, location

Example 3:
Question:
where does frida kahlo live now?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5588 wdt:P551 ?x .
}

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

Using properties:
residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as wdt): the place where the person is or has been, resident, location

[Assistant] The examples show that to find the place where a person died, we need to find the entity for Antoine Lavoisier and then find the property related to the place of death. Let's first search for the entity "Antoine Lavoisier" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Antoine Lavoisier, also known as Lavoisier, Antoine Laurent Lavoisier, Antoine Laurent de Lavoisier, Antoine-Laurent de Lavoisier (wd:Q39607): French chemist, administrator, astronomer, biologist, physicist, economist, academic, chemist, lawyer, writer
2. Antoine Lavoisier (wd:Q59073688): scientific article published in Nature
3. Antoine Lavoisier (wd:Q18147111): sculpture by Jacques-Léonard Maillet
4. Antoine-Laurent Lavoisier (wd:Q21685186): encyclopedic article
5. résidence Antoine Lavoisier (wd:Q113413611): street in Pierrefitte-sur-Seine, France
6. Antoine de Lavoisier (wd:Q108838701)
7. Antoine Laurent Lavoisier (wd:Q74018917): scientific article published on 01 May 1956
8. Antoine Laurent Lavoisier (wd:Q69311401): scientific article published on 01 July 1973
9. Antoine Laurent Lavoisier (wd:Q41051602): scientific article
10. rue Antoine de Lavoisier (wd:Q112065256): street in Rungis, France

[Assistant] The entity for Antoine Lavoisier is wd:Q39607. Now, I will search for properties related to 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 p/wdt): 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 p/wdt): 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 p/wdt): dissolved, abolished or demolished date, date on which the subject died, end time
4. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as p/wdt): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
5. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as p/wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
6. 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
7. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
8. 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 p/wdt): identifier of an individual's burial place in the Find a Grave database
9. 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
10. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception

No other items found

[Assistant] The property for place of death is wd:P20. Now I will write a SPARQL query to find the place where Antoine Lavoisier (wd:Q39607) died using the property wd:P20.

[Tool]
Got 1 row and 2 columns:
| placeOfDeath                      | placeOfDeathLabel         |
| --------------------------------- | ------------------------- |
| place de la Concorde (wd:Q189503) | place de la Concorde (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the place of death for Antoine Lavoisier using the property wdt:P20. The result is accurate and matches the human-readable answer given, which is Place de la Concorde. The query also optionally retrieves the English label for the place, which is appropriate. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?college ?collegeLabel WHERE {
  wd:Q117425 wdt:P69 ?college .
  ?college wdt:P31 ?type .
  FILTER ( ?type IN ( wd:Q3918 , wd:Q16917 ) ) OPTIONAL {
    ?college rdfs:label ?collegeLabel FILTER ( LANG( ?collegeLabel ) = "en" )
  }
}

S. E. Hinton attended the University of Tulsa as her college-level education institution.

[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 college did se hinton go?

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

[Tool]
Example 1:
Question:
what voice does hank azaria do on the simpsons?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q886 p:P725 ?p .
  ?p ps:P725 wd:Q202056 ; pq:P453 ?x .
}

Using entities:
Hank Azaria, also known as Henry Albert "Hank" Azaria, Henry Albert Azaria (wd:Q202056): television producer, television actor, American actor, film director, screenwriter, voice actor, stage actor, film actor, dub actor, actor
The Simpsons (wd:Q886): American animated sitcom created by Matt Groening

Using properties:
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)
voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as p/ps): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member

Example 2:
Question:
where john tyler was born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q11881 wdt:P19 ?x .
}

Using entities:
John Tyler, also known as John Tyler, Jr., J. Tyler, President Tyler, John Tyler Jr, John Tyler, Jr (wd:Q11881): president of the United States from 1841 to 1845, statesperson, politician, lawyer

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

Example 3:
Question:
what language do iraqi people speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q796 wdt:P37 ?x .
}

Using entities:
Iraq, also known as iq, IRQ, Republic of Iraq (wd:Q796): sovereign state in Western Asia

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

[Assistant]
The question is about the college that SE Hinton attended. SE Hinton is a person, so I need to find the entity for SE Hinton first. Then I need to find the property related to the college or educational institution attended by this person. Common properties for education in Wikidata are "educated at" (wdt:P69).

I will start by searching for the entity SE Hinton in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Sebastian Hinton (wd:Q55532855): lawyer, inventor of the Jungle gym, lawyer
2. Sean Hinton (wd:Q115735561): Founder and Chief Executive Officer - SkyHive
3. Sedum hintonii (wd:Q15128167): species of plant
4. Sechium hintonii (wd:Q15537806): species of plant
5. Sebastiania hintonii (wd:Q15381122): species of plant
6. Sedum hintoniorum (wd:Q17773683): species of plant
7. Senecio hintonii (wd:Q15596264): species of plant
8. Senecio hintoniorum (wd:Q15596465): species of plant
9. Hinton Sewage Pond Dam (wd:Q34836139): dam in Caddo County, Oklahoma, United States of America
10. Salvia sect. Hintoniana (wd:Q129574204)

[Assistant]
The search did not return an entity explicitly named "SE Hinton," but SE Hinton is a well-known author, so it might be under a slightly different name or spelling. The closest match is "Sebastian Hinton" (wd:Q55532855), but that is a different person (lawyer, inventor of the Jungle gym).

I will try searching for "S. E. Hinton" to see if the author is listed under that name.

[Tool]
Top 10 entity alternatives:
1. S. E. Hinton, also known as Susan Eloise Hinton (wd:Q117425): children's writer, American writer, autobiographer, screenwriter, film actor, novelist, writer
2. S. E. Hinton bibliography (wd:Q7387461)
3. Scott, Edward Hinton (wd:Q96779104): entry in the Royal Naval Biography
4. Eric Hinton Stewart (wd:Q75742435): (born 1899)
5. Edward Hinton Scott (wd:Q108103196): British Royal Navy officer, captain in 1838 (1789-?), naval officer
6. Scott, Edward Hinton (NBD) (wd:Q24022213): entry in the Naval Biographical Dictionary
7. High Stakes with Ed Hinton (wd:Q114502643): episode of The Roy Rogers Show (S6 E11)
8. Hinton Ampner C Of E Primary School (wd:Q26448924): school building in Hinton Ampner, Hampshire, England, UK
9. Hinton St George Church of England School (wd:Q66163957): school in Somerset, UK
10. Broad Hinton Church of England Primary School (wd:Q66164603): school in Wiltshire, UK

[Assistant] I found the entity for S. E. Hinton, the author, with the Wikidata ID wd:Q117425. Now I will look for the property related to the college or educational institution attended by S. E. Hinton. The common property for education is "educated at" (wdt:P69). I will check if this property exists for S. E. Hinton.

[Tool]
Got 2 rows and 3 columns:
| subject                   | property              | object                                |
| ------------------------- | --------------------- | ------------------------------------- |
| S. E. Hinton (wd:Q117425) | educated at (wdt:P69) | University of Tulsa (wd:Q1848657)     |
| S. E. Hinton (wd:Q117425) | educated at (wdt:P69) | Will Rogers High School (wd:Q8003051) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the educational institutions attended by S. E. Hinton, including both the University of Tulsa and Will Rogers High School. However, the user specifically asked for the college she attended, so the answer should focus on the college-level institution only. The query could be refined to filter out high schools or non-college institutions, for example by checking the instance type of the educational institution to ensure it is a college or university. This would make the answer more precise and relevant to the user's question.

[Assistant] Thank you for the feedback. I will refine the SPARQL query to return only the college-level institution attended by S. E. Hinton. To do this, I will filter the educational institutions to include only those that are instances of a university or college. I will check for instance of (wdt:P31) university (wd:Q3918) or college (wd:Q16917).

[Tool]
Got 1 row and 2 columns:
| college                           | collegeLabel             |
| --------------------------------- | ------------------------ |
| University of Tulsa (wd:Q1848657) | University of Tulsa (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified the college that S. E. Hinton attended by querying the 'educated at' (P69) property and filtering for educational institutions of type university or hospital. The result is accurate and matches known information that S. E. Hinton attended the University of Tulsa. The SPARQL query is well-formed, returns the correct entity and label, and follows the rules for SPARQL queries. No further refinement is necessary.