PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?timeZone ?timeZoneLabel WHERE {
  wd:Q201026 wdt:P421 ?timeZone .
  OPTIONAL {
    ?timeZone rdfs:label ?timeZoneLabel FILTER ( LANG( ?timeZoneLabel ) = "en" )
  }
}

The current time in Kauai, Hawaii, corresponds to the time zone UTC−10:00. Kauai is in the UTC−10:00 time zone.

[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

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

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

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

[User] what is the current time in kauai hawaii?

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

[Tool]
Example 1:
Question:
what is time zone in hawaii?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q782 wdt:P421 ?x .
}

Using entities:
Hawaii, also known as Hawaii State, Hawaii, United States, Kaimana Hila, The Aloha State, State of Hawaii (wd:Q782): state of the United States of America

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

Example 2:
Question:
what is the hawaii time zone?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q782 wdt:P421 ?x .
}

Using entities:
Hawaii, also known as Hawaii State, Hawaii, United States, Kaimana Hila, The Aloha State, State of Hawaii (wd:Q782): state of the United States of America

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

Example 3:
Question:
what is the actual current local time now in uk?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q145 wdt:P421 ?x .
}

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:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

[Assistant]
The examples show that the property "located in time zone" (wdt:P421) is used to find the time zone of a place. To answer the question about the current time in Kauai, Hawaii, we first need to find the time zone of Kauai, Hawaii. Then we can provide the current time in that time zone.

Step 1: Find the entity for Kauai, Hawaii.
Step 2: Find the time zone of Kauai using the property "located in time zone" (wdt:P421).
Step 3: Return the time zone information, which can be used to determine the current time.

Let's start by searching for the entity Kauai.

[Tool]
Top 10 entity alternatives:
1. Kauai, also known as Kauaʻi (wd:Q201026): northernmost populated island of the Hawaiian archipelago
2. Kauai, also known as IMO 7802718 (wd:Q122788843): ship built in 1980
3. Kauai (wd:Q116498799): restaurant chain in South Africa
4. Kauai (wd:Q114490161): episode of Drinking Made Easy (S2 E2)
5. Kauai County, also known as Kauai County, Hawaii, Kauai County, HI (wd:Q111517): county in Hawaii, United States
6. Kauaʻi ʻŌʻō, also known as Kauai oo, Moho braccatus (wd:Q19555): extinct species of Moho songbird
7. Hyundai Kona, also known as Hyundai Encino, Hyundai Kauai (wd:Q30322680): subcompact crossover SUV
8. Kauai Akialoa, also known as Kauaʻi ʻakialoa, Akialoa stejnegeri (wd:Q27075764): species of bird
9. Astelia waialealae, also known as Kauai paiiniu, Kauai paíiniu (wd:Q2868379): species of plant
10. Kokia kauaiensis, also known as Kauai kokiio, Kauai kokiío (wd:Q5486498): species of plant

[Assistant] The entity for Kauai as the northernmost populated island of the Hawaiian archipelago is wd:Q201026. Now, let's find the time zone of Kauai using the property "located in time zone" (wdt:P421).

[Tool]
Got 1 row and 2 columns:
| timeZone             | timeZoneLabel  |
| -------------------- | -------------- |
| UTC−10:00 (wd:Q2163) | UTC−10:00 (en) |

[Assistant] Kauai is in the time zone UTC−10:00 (wd:Q2163). The current time in Kauai, Hawaii, corresponds to the current time in the UTC−10:00 time zone. Since the current time is dynamic and not stored in Wikidata, I can provide the time zone information for Kauai, Hawaii.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer correctly identifies the time zone of Kauai, Hawaii as UTC−10:00, which matches the information retrieved by the SPARQL query. The query properly uses the property 'located in time zone' (wdt:P421) for the entity Kauai (wd:Q201026) and retrieves the time zone and its English label. The answer is clear and complete given the question, which asks for the current time zone rather than the exact current time. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?language ?languageLabel WHERE {
  wd:Q79 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| Arabic (wd:Q13955) | Arabic (en)   |

Egyptians speak Arabic as the official language.

[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

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

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

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

[User] what kind of language do egyptian speak?

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

[Tool]
Example 1:
Question:
what language do they speak in egyptian?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q79 wdt:P37 ?x .
}

Using entities:
Egypt, also known as Republic of Egypt, Rep. Egypt, EGY, eg, Arab Republic of Egypt (wd:Q79): country in Northeast Africa and Southwest Asia

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

Example 2:
Question:
what language do egyptians use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q79 wdt:P37 ?x .
}

Using entities:
Egypt, also known as Republic of Egypt, Rep. Egypt, EGY, eg, Arab Republic of Egypt (wd:Q79): country in Northeast Africa and Southwest Asia

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

Example 3:
Question:
what language does egyptians use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q79 wdt:P37 ?x .
}

Using entities:
Egypt, also known as Republic of Egypt, Rep. Egypt, EGY, eg, Arab Republic of Egypt (wd:Q79): country in Northeast Africa and Southwest 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 examples suggest that the question "what kind of language do Egyptians speak?" can be answered by querying the official language(s) of Egypt (entity wd:Q79) using the property "official language" (wdt:P37). I will now write a SPARQL query to get the official languages of Egypt.

[Tool]
Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| Arabic (wd:Q13955) | Arabic (en)   |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the official language spoken in Egypt using the property for official language (wdt:P37). The result is accurate and matches the user's question about the language Egyptians speak. The query also optionally retrieves the English label for better readability. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?senator ?senatorLabel WHERE {
  ?senator p:P39 ?statement .
  ?statement ps:P39 wd:Q4416090 ; pq:P768 ?seat ; pq:P580 ?start ; pq:P582 ?end .
  ?seat wdt:P131 wd:Q1370 .
  FILTER ( ?start < "2014-01-01T00:00:00Z" ^^ xsd:dateTime && ?end >= "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) OPTIONAL {
    ?senator rdfs:label ?senatorLabel FILTER ( LANG( ?senatorLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| senator                  | senatorLabel     |
| ------------------------ | ---------------- |
| Tim Kaine (wd:Q359888)   | Tim Kaine (en)   |
| Mark Warner (wd:Q453893) | Mark Warner (en) |
| Jim Webb (wd:Q532279)    | Jim Webb (en)    |

The Virginia senators in 2013 were Tim Kaine, Mark Warner, and Jim Webb.

[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

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 are the virginia senators 2013?

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

[Tool]
Example 1:
Question:
who are the senators of kansas 2013?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 ; pq:P768 ?w ; pq:P580 ?y ; pq:P582 ?z .
  ?w wdt:P131 wd:Q1558 .
  FILTER ( ( ?y < "2014-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
Kansas, also known as Kan., Kans., Kansas, United States of America, US-KS, KS (wd:Q1558): state of the United States of America
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/p): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pq): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

Example 2:
Question:
who are the current maryland senators?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 .
  ?p pq:P768 ?y .
  ?y wdt:P131 wd:Q1391 .
  FILTER NOT EXISTS {
    ?p pq:P582 ?z .
  }
}

Using entities:
Maryland, also known as Maryland, United States, Md., MD, US-MD, Old Line State (wd:Q1391): state of the United States of America
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/p): subject currently or formerly holds the object position or public office
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pq): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

Example 3:
Question:
who is the senator of the state of texas?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 .
  ?p pq:P768 ?y .
  ?y wdt:P131 wd:Q1439 .
  FILTER NOT EXISTS {
    ?p pq:P582 ?z .
  }
}

Using entities:
Texas, also known as Lone Star State, US-TX, TX, Texas, United States, Tex. (wd:Q1439): state of the United States of America
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/p): subject currently or formerly holds the object position or public office
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pq): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

[Assistant]
From the examples, the approach to find senators of a specific state in a specific year is to look for entities that held the position of United States senator (wd:Q4416090) with an electoral district located in the state, and filter by the start and end time of the position to include the year 2013.

I will now search for the Wikidata entity for Virginia to use in the query.

[Tool]
Top 10 entity alternatives:
1. Virginia, also known as State of Virginia, Old Dominion, US-VA, Va., Commonwealth of Virginia (wd:Q1370): state of the United States of America
2. Virginia, also known as VA, Virginia, United States, Va., US-VA, Old Dominion (wd:Q1370): state of the United States of America
3. 50 Virginia, also known as (50) Virginia, Virginia (wd:Q154933): main-belt asteroid
4. Virginia, also known as Virginia, Minnesota, Virginia, MN (wd:Q986681): city in St. Louis County, Minnesota, United States
5. Virginia, also known as Virginia, Illinois, Virginia, IL (wd:Q579625): city in Illinois, USA
6. Virginia, also known as Virginia, Nebraska, Virginia, NE (wd:Q2207776): village in Gage County, Nebraska, United States
7. Virgínia, also known as Virginia (wd:Q1787215): town and municipality in the state of Minas Gerais, Brazil
8. Verginia, also known as Virginia (wd:Q1278485): 5th-century BC Roman heroine
9. Virginia, also known as Virginia, County Cavan (wd:Q255427): town in County Cavan, Ireland
10. Virginia (wd:Q290763): genus of reptiles

[Assistant] The Wikidata entity for the state of Virginia is wd:Q1370. I will now construct a SPARQL query to find the senators of Virginia in 2013. The query will look for entities that held the position of United States senator (wd:Q4416090) with an electoral district located in Virginia (wd:Q1370) and filter the position's start and end time to include the year 2013.

[Tool]
Got 3 rows and 1 column:
| senator                  |
| ------------------------ |
| Tim Kaine (wd:Q359888)   |
| Mark Warner (wd:Q453893) |
| Jim Webb (wd:Q532279)    |

[Assistant] The query returned three senators for Virginia in 2013: Tim Kaine (wd:Q359888), Mark Warner (wd:Q453893), and Jim Webb (wd:Q532279). I will now provide the final answer with these senators.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly identifies the three Virginia senators in 2013: Tim Kaine, Mark Warner, and Jim Webb. However, the query uses the property 'electoral district' (wdt:P768) to filter senators by Virginia (wd:Q1370), which is not accurate for U.S. senators. U.S. senators represent entire states, not electoral districts. Instead, the query should filter by the state represented using a more appropriate property or by linking the position held to the state of Virginia. Also, the query assumes the position held is 'United States senator' (wd:Q4416090), which is correct. The time filtering is appropriate to cover the year 2013. To improve accuracy, the query should be refined to correctly associate senators with the state of Virginia rather than using electoral districts. This will ensure the query is semantically correct and more robust.

[Assistant]
Thank you for the feedback. I understand that using the property "electoral district" (wdt:P768) is not the correct way to associate U.S. senators with the state they represent, as senators represent entire states, not electoral districts. Instead, I should find a property or qualifier that directly links the position held (United States senator) to the state of Virginia (wd:Q1370).

I will now search for the properties used in the position held statements (P39) for U.S. senators to find a more appropriate property or qualifier to link the senators to the state they represent.

[Tool]
Top 10 property alternatives:
1. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
2. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as wdt/p): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
3. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt/p): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
4. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as wdt/p): main Wikidata property for this item
5. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
6. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
8. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt/p): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
9. term length of position, also known as term length, time in position, term of position, position term, length of term (wd:P2097 as wdt/p): length of time in years (unit: Q577) a person (usually a politician) is to serve in a particular position. Do not add bounds., duration
10. honorific prefix, also known as called, style prefix, referred to as, pre-nominal, honorific title (wd:P511 as wdt/p): word or expression used before a name, in addressing or referring to a person

No other items found

[Assistant]
The search for properties related to "state" for the entity "United States senator" (wd:Q4416090) did not return a direct property linking the senator to the state they represent. However, the property "applies to jurisdiction" (wd:P1001) seems relevant as it indicates the territorial jurisdiction to which the item (institution, law, public office, etc.) applies.

I will now check if the position held statements (P39) for senators have the qualifier "applies to jurisdiction" (P1001) linking to the state they represent. I will do this by listing some statements for a known senator and checking the qualifiers. I will use Tim Kaine (wd:Q359888) as an example.

[Tool]
Got 11 rows and 3 columns, showing the first 10 rows below:
| subject                | property              | object                                         |
| ---------------------- | --------------------- | ---------------------------------------------- |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:Q359888-20A86392-03BF-4014-A08C-5D3DAB3A8FAD |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:q359888-3AB3BED9-A5E1-43B9-83C5-161F07907C9A |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:Q359888-518D806A-65BF-49DB-B1DE-AE3EE27DB309 |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:Q359888-63c11699-4e10-f360-b8c6-762fde809668 |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:Q359888-68535242-5A5B-4638-9A9D-90B04F3B0E94 |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:Q359888-730021da-414d-9d6b-e86b-feb5b8b52b80 |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:Q359888-7d0f051e-4b54-4fa6-4b02-622b46a88bbb |
| Tim Kaine (wd:Q359888) | position held (p:P39) | s:Q359888-A5AE72A0-689F-4D97-B874-0CCE45938020 |
| ...                    | ...                   | ...                                            |

[Assistant] I have found multiple position held statements (P39) for Tim Kaine. I will now check the qualifiers of one of these statements to see if there is a qualifier linking the position to the state of Virginia. I will check the qualifiers of the first statement s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1.

[Tool]
Got 12 rows and 3 columns, showing the first 10 rows below:
| subject                                        | property                                                   | object                                       |
| ---------------------------------------------- | ---------------------------------------------------------- | -------------------------------------------- |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | position held (ps:P39)                                     | chairperson (wd:Q140686)                     |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | start time (pq:P580)                                       | 2009-01-21T00:00:00Z (xsd:dateTime)          |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | end time (pq:P582)                                         | 2011-04-05T00:00:00Z (xsd:dateTime)          |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | replaced by (pq:P1366)                                     | Debbie Wasserman Schultz (wd:Q50104)         |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | replaces (pq:P1365)                                        | Howard Dean (wd:Q337470)                     |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | organization directed by the office or position (pq:P2389) | Democratic National Committee (wd:Q1185863)  |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | wikibase:rank                                              | wikibase:NormalRank                          |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | rdf:type                                                   | wikibase:BestRank                            |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | prov:wasDerivedFrom                                        | ref:e406e766688367265d53f2f89cdeceae72bd8a0b |
| s:Q359888-1199fbea-4c00-8cdd-88e5-5c2ac24122d1 | start time (pqv:P580)                                      | v:c9be03a2c66c6612a8d28aaf9bee2571           |
| ...                                            | ...                                                        | ...                                          |

[Assistant] The qualifiers of this statement do not show a direct link to the state of Virginia. I will check another position held statement for Tim Kaine that might be related to the U.S. Senate. I will check the qualifiers of the second statement s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660.

[Tool]
Got 13 rows and 3 columns, showing the first 10 rows below:
| subject                                        | property                       | object                                                       |
| ---------------------------------------------- | ------------------------------ | ------------------------------------------------------------ |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | position held (ps:P39)         | United States senator (wd:Q4416090)                          |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | start time (pq:P580)           | 2015-01-03T00:00:00Z (xsd:dateTime)                          |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | end time (pq:P582)             | 2017-01-03T00:00:00Z (xsd:dateTime)                          |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | electoral district (pq:P768)   | Virginia Class 1 senate seat (wd:Q101498883)                 |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | parliamentary term (pq:P2937)  | 114th United States Congress (wd:Q16146771)                  |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | parliamentary group (pq:P4100) | Democratic Party (wd:Q29552)                                 |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | elected in (pq:P2715)          | 2012 United States Senate election in Virginia (wd:Q7892087) |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | wikibase:rank                  | wikibase:NormalRank                                          |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | rdf:type                       | wikibase:BestRank                                            |
| s:Q359888-1386511D-2ED6-4E54-B7CA-7A6F48455660 | prov:wasDerivedFrom            | ref:3376953e6ea41712f6055105118c0c3b04484880                 |
| ...                                            | ...                            | ...                                                          |

[Assistant]
In this statement, the qualifier "electoral district" (pq:P768) is used with the value "Virginia Class 1 senate seat" (wd:Q101498883). This indicates that the electoral district qualifier is used to specify the senate seat, which is linked to Virginia.

I will now check the details of "Virginia Class 1 senate seat" (wd:Q101498883) to confirm that it is linked to the state of Virginia.

[Tool]
Got 28 rows and 3 columns, showing the first 10 rows below:
| subject                                      | property                                                    | object                                              |
| -------------------------------------------- | ----------------------------------------------------------- | --------------------------------------------------- |
| Virginia Class 1 senate seat (wd:Q101498883) | instance of (wdt:P31)                                       | United States senate seat (Class 1) (wd:Q101434824) |
| Virginia Class 1 senate seat (wd:Q101498883) | country (wdt:P17)                                           | United States (wd:Q30)                              |
| Virginia Class 1 senate seat (wd:Q101498883) | located in the administrative territorial entity (wdt:P131) | Virginia (wd:Q1370)                                 |
| Virginia Class 1 senate seat (wd:Q101498883) | subclass of (wdt:P279)                                      | United States senate constituency (wd:Q58425000)    |
| Virginia Class 1 senate seat (wd:Q101498883) | wdt:P31279                                                  | electoral unit (wd:Q192611)                         |
| Virginia Class 1 senate seat (wd:Q101498883) | schema:description                                          | Class 1 United States senate seat for Virginia (en) |
| Virginia Class 1 senate seat (wd:Q101498883) | schema:name                                                 | senatni sedež razreda 1 Virginije (sl)              |
| Virginia Class 1 senate seat (wd:Q101498883) | rdf:type                                                    | wikibase:Item                                       |
| Virginia Class 1 senate seat (wd:Q101498883) | rdfs:label                                                  | senatni sedež razreda 1 Virginije (sl)              |
| Virginia Class 1 senate seat (wd:Q101498883) | skos:altLabel                                               | Virginia senate seat (I) (en)                       |
| ...                                          | ...                                                         | ...                                                 |

[Assistant]
The "Virginia Class 1 senate seat" (wd:Q101498883) is located in the administrative territorial entity Virginia (wd:Q1370). This confirms that the qualifier "electoral district" (pq:P768) in the position held statement is used to specify the senate seat, which is linked to Virginia.

Therefore, the original approach using the qualifier "electoral district" (pq:P768) to filter senators by Virginia is semantically correct in this context.

I will now refine the original query to include senators who held the position of United States senator with the electoral district linked to Virginia, filtering by the start and end time to cover the year 2013. I will also include labels for better readability.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query returns three senators: Tim Kaine, Mark Warner, and Jim Webb, which matches the answer given. However, the query uses the property pq:P768 (electoral district) with the value wd:Q1370 (Virginia) to filter senators representing Virginia. This is incorrect because pq:P768 refers to an electoral district, which is not the same as the state of Virginia. The correct approach is to use the property wd:P31 (instance of) or a more appropriate property to identify senators representing the state of Virginia. Also, the query filters on start and end times to cover the year 2013, which is good. The answer is correct but the query should be refined to correctly identify senators representing Virginia in 2013 by using the correct property for the state they represent, such as pq:P768 with the correct entity or another property indicating the state represented in the Senate. Additionally, the label retrieval is done correctly with an optional clause. Please refine the query to correctly capture Virginia senators in 2013.

[Assistant]
Thank you for the detailed feedback. I understand that the qualifier pq:P768 (electoral district) is not the correct property to directly link senators to the state of Virginia, even though it was used to link to the Virginia Class 1 and Class 2 senate seats. The feedback suggests using a property like "instance of" (wdt:P31) or another more appropriate property to identify senators representing the state of Virginia.

I will now investigate the qualifiers used in the position held statements for U.S. senators to find the correct property or qualifier that directly links the senator to the state they represent.

I will start by searching for properties related to "state represented" or "state" that are used as qualifiers in the position held (P39) statements for senators.

[Tool]
Top 10 property alternatives:
1. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
2. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as wdt/p): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
3. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt/p): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
4. term length of position, also known as term length, time in position, term of position, position term, length of term (wd:P2097 as wdt/p): length of time in years (unit: Q577) a person (usually a politician) is to serve in a particular position. Do not add bounds., duration
5. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt/p): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
6. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
8. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as wdt/p): main Wikidata property for this item
9. honorific prefix, also known as called, style prefix, referred to as, pre-nominal, honorific title (wd:P511 as wdt/p): word or expression used before a name, in addressing or referring to a person
10. coat of arms image, also known as symbol, representation (heraldic), image of coat of arms, emblem, heraldic, CoA image (wd:P94 as wdt/p): image of the item's coat of arms - for the shield part only use P4004, image

No other items found

[Assistant]
The search for properties related to "state represented" or "state" for the entity "United States senator" (wd:Q4416090) did not return a direct property or qualifier that explicitly indicates the state represented by the senator.

Given this, I will try a different approach: I will check the electoral district qualifier (pq:P768) values for the senators of Virginia in 2013 to see if they are consistently linked to specific senate seats that are located in Virginia. Then, I will verify if these senate seats are instances of "United States senate seat" and are located in Virginia. This approach will ensure that the senators are linked to Virginia through the senate seats they hold.

I will start by querying the electoral district qualifier values for the senators of Virginia in 2013.

[Tool]
Got 2 rows and 1 column:
| seat                                         |
| -------------------------------------------- |
| Virginia Class 1 senate seat (wd:Q101498883) |
| Virginia Class 2 senate seat (wd:Q101498993) |

[Assistant]
The electoral district qualifier values for the Virginia senators in 2013 are "Virginia Class 1 senate seat" (wd:Q101498883) and "Virginia Class 2 senate seat" (wd:Q101498993). Both are linked to Virginia (wd:Q1370).

I will now check the properties of "Virginia Class 2 senate seat" (wd:Q101498993) to confirm it is also linked to Virginia.

[Tool]
Got 32 rows and 3 columns, showing the first 10 rows below:
| subject                                      | property                                                    | object                                              |
| -------------------------------------------- | ----------------------------------------------------------- | --------------------------------------------------- |
| Virginia Class 2 senate seat (wd:Q101498993) | instance of (wdt:P31)                                       | United States senate seat (Class 2) (wd:Q101434854) |
| Virginia Class 2 senate seat (wd:Q101498993) | country (wdt:P17)                                           | United States (wd:Q30)                              |
| Virginia Class 2 senate seat (wd:Q101498993) | located in the administrative territorial entity (wdt:P131) | Virginia (wd:Q1370)                                 |
| Virginia Class 2 senate seat (wd:Q101498993) | subclass of (wdt:P279)                                      | United States senate constituency (wd:Q58425000)    |
| Virginia Class 2 senate seat (wd:Q101498993) | wdt:P31279                                                  | electoral unit (wd:Q192611)                         |
| Virginia Class 2 senate seat (wd:Q101498993) | schema:description                                          | Class 2 United States senate seat for Virginia (en) |
| Virginia Class 2 senate seat (wd:Q101498993) | schema:name                                                 | senatni sedež razreda 2 Virginije (sl)              |
| Virginia Class 2 senate seat (wd:Q101498993) | rdf:type                                                    | wikibase:Item                                       |
| Virginia Class 2 senate seat (wd:Q101498993) | rdfs:label                                                  | senatni sedež razreda 2 Virginije (sl)              |
| Virginia Class 2 senate seat (wd:Q101498993) | skos:altLabel                                               | Virginia senate seat (II) (en)                      |
| ...                                          | ...                                                         | ...                                                 |

[Assistant]
The "Virginia Class 2 senate seat" (wd:Q101498993) is also located in the administrative territorial entity Virginia (wd:Q1370) and is an instance of "United States senate seat (Class 2)" (wd:Q101434854).

This confirms that the electoral district qualifier (pq:P768) values for the senators represent specific senate seats that are linked to Virginia.

Therefore, the correct approach to find Virginia senators in 2013 is to look for entities that held the position of United States senator (wd:Q4416090) with the electoral district qualifier (pq:P768) being a senate seat located in Virginia (wd:Q1370), and filter by the start and end time to cover the year 2013.

I will now finalize the refined SPARQL query and answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?governor WHERE {
  wd:Q812 wdt:P6 ?governor .
}

The current state governor of Florida is Ron DeSantis.

[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

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

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

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

[User] who is the state governor of florida?

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

[Tool]
Example 1:
Question:
who is the new governor of florida 2011?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q20198851 wdt:P1308 ?x .
}

Using entities:
Governor of Florida, also known as Florida Governor (wd:Q20198851): head of state and of government of the U.S. state of Florida

Using properties:
position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as wdt): persons who hold and/or held the position

Example 2:
Question:
who is the current governor of georgia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q739 wdt:P6 ?x .
}

Using entities:
Colombia, also known as The Republic of Colombia, Republic of Colombia, ISO 3166-1:CO, Colombiá, COL (wd:Q739): sovereign state in South America

Using properties:
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

Example 3:
Question:
who is the elected governor of california?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q99 wdt:P6 ?x .
}

Using entities:
California, also known as US-CA, State of California, The Golden State, Calif., Cali. (wd:Q99): state of the United States of America

Using properties:
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

[Assistant]
From the examples, it appears that the property "head of government" (wdt:P6) is used to indicate the governor or head of government of a state. The entity for Florida is wd:Q812.

I will now write a SPARQL query to find the current governor of Florida using the property wdt:P6.

[Tool]
Got 1 row and 1 column:
| governor                   |
| -------------------------- |
| Ron DeSantis (wd:Q3105215) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the current state governor of Florida by using the property for head of government (wdt:P6) on the entity for Florida (wd:Q812). The query returns the expected result, Ron DeSantis, which matches the known current governor. The answer is accurate and complete. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?school ?schoolLabel WHERE {
  wd:Q127417 wdt:P69 ?school .
  FILTER ( ?school != wd:Q6861744 ) OPTIONAL {
    ?school rdfs:label ?schoolLabel FILTER ( LANG( ?schoolLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| school                                                             | schoolLabel                                               |
| ------------------------------------------------------------------ | --------------------------------------------------------- |
| United States Army Command and General Staff College (wd:Q1115050) | United States Army Command and General Staff College (en) |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       |

Douglas MacArthur attended the United States Military Academy and the United States Army Command and General Staff College. The previously listed Milwaukee High School of the Arts is excluded as it is unlikely to be correct for his historical context.

[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

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 school did douglas macarthur go to?

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

[Tool]
Example 1:
Question:
where did douglas macarthur die?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q127417 wdt:P20 ?x .
}

Using entities:
Douglas MacArthur, also known as MacArthur, D. MacArthur, General MacArthur, General Douglas MacArthur (wd:Q127417): United States Army general in WWI, WWII and Korea (1880–1964), military officer, army officer

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 2:
Question:
where did eleanor roosevelt go to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q83396 wdt:P69 ?x .
}

Using entities:
Eleanor Roosevelt, also known as Eleanor Roosevelt Roosevelt, Elaenore Roosevelt, Anna Eleanor Roosevelt Roosevelt, First Lady of the world, Anna Roosevelt (wd:Q83396): First Lady of the United States from 1933 to 1945, women's rights activist, human rights activist, peace activist, autobiographer, journalist, politician, columnist, diplomat, writer

Using properties:
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 3:
Question:
where did barack obama went to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q76 wdt:P69 ?x .
}

Using entities:
Barack Obama, also known as Honorable Barack Obama, BHO, Obama, Barry O Bomber, President Obama (wd:Q76): president of the United States from 2009 to 2017, community organizer, political writer, statesperson, politician, podcaster, memoirist, academic, lawyer, jurist

Using properties:
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

[Assistant] From the similar examples, the property "educated at" (wdt:P69) is used to find the schools a person attended. Also, Douglas MacArthur is identified as wd:Q127417 in Wikidata. I will now query the schools Douglas MacArthur attended using the property "educated at" (wdt:P69).

[Tool]
Got 3 rows and 2 columns:
| school                                                             | schoolLabel                                               |
| ------------------------------------------------------------------ | --------------------------------------------------------- |
| United States Army Command and General Staff College (wd:Q1115050) | United States Army Command and General Staff College (en) |
| Milwaukee High School of the Arts (wd:Q6861744)                    | Milwaukee High School of the Arts (en)                    |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the schools Douglas MacArthur attended using the property 'educated at' (wdt:P69). However, the result includes 'Milwaukee High School of the Arts,' which is unlikely to be correct for Douglas MacArthur given his historical timeline and biography. This suggests that the data might have some inaccuracies or that the query is retrieving all schools linked by the property without filtering for relevant time periods or types of institutions. To improve, consider filtering the schools by their instance type (e.g., military academy, high school) or by dates if available, to better match the historical context of Douglas MacArthur's education. Also, ensure that the labels are retrieved in English as done. Overall, the query is structurally correct but could be refined to improve answer relevance and accuracy.

[Assistant] Thank you for the feedback. To refine the query, I will filter the schools attended by Douglas MacArthur to include only those that are military academies or higher education institutions, which are more relevant to his historical context. I will check for the instance of the school (e.g., military academy, university) and include only those in the results. I will now update the query accordingly.

[Tool] Got no rows and 3 columns

[Assistant] The filtering by specific instance types military academy (wd:Q189008), university (wd:Q43229), and college (wd:Q2385804) returned no results. This might be because the schools Douglas MacArthur attended are not directly typed as these instances in Wikidata. I will try a broader approach by checking if the schools are subclasses of educational institutions or military academies using a property path. I will also include high schools as a possible type. I will update the query accordingly.

[Tool]
Got 4 rows and 3 columns:
| school                                                             | schoolLabel                                               | instanceLabel                                            |
| ------------------------------------------------------------------ | --------------------------------------------------------- | -------------------------------------------------------- |
| United States Army Command and General Staff College (wd:Q1115050) | United States Army Command and General Staff College (en) | staff college (en)                                       |
| Milwaukee High School of the Arts (wd:Q6861744)                    | Milwaukee High School of the Arts (en)                    | high school (en)                                         |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       | military academy (en)                                    |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       | public educational institution of the United States (en) |

[Assistant] The refined query still returns Milwaukee High School of the Arts, which is a high school, along with the United States Military Academy and the United States Army Command and General Staff College. Since Milwaukee High School of the Arts is unlikely to be correct for Douglas MacArthur, I will exclude high schools from the results and keep only military academies and staff colleges. I will update the query to exclude high schools.

[Tool]
Got 4 rows and 3 columns:
| school                                                             | schoolLabel                                               | instanceLabel                                            |
| ------------------------------------------------------------------ | --------------------------------------------------------- | -------------------------------------------------------- |
| United States Army Command and General Staff College (wd:Q1115050) | United States Army Command and General Staff College (en) | staff college (en)                                       |
| Milwaukee High School of the Arts (wd:Q6861744)                    | Milwaukee High School of the Arts (en)                    | high school (en)                                         |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       | military academy (en)                                    |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       | public educational institution of the United States (en) |

[Assistant] The exclusion filter for high school (wd:Q23442) did not work as expected because the instance of Milwaukee High School of the Arts is "high school" (wd:Q6861744) which is different from the high school entity I excluded. I will explicitly exclude the instance "high school" (wd:Q6861744) instead. I will update the query accordingly.

[Tool]
Got 4 rows and 3 columns:
| school                                                             | schoolLabel                                               | instanceLabel                                            |
| ------------------------------------------------------------------ | --------------------------------------------------------- | -------------------------------------------------------- |
| United States Army Command and General Staff College (wd:Q1115050) | United States Army Command and General Staff College (en) | staff college (en)                                       |
| Milwaukee High School of the Arts (wd:Q6861744)                    | Milwaukee High School of the Arts (en)                    | high school (en)                                         |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       | military academy (en)                                    |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       | public educational institution of the United States (en) |

[Assistant] The filter to exclude high school (wd:Q6861744) did not remove Milwaukee High School of the Arts from the results. This might be because the instance of the school is directly "high school" and not a subclass of educational institution (wd:Q2385804) or the filtering logic is not excluding it properly. I will try a different approach: I will explicitly include only military academies and staff colleges by their instance or subclass. I will use the instances military academy (wd:Q189008) and staff college (wd:Q1115050) explicitly.

[Tool] Got no rows and 3 columns

[Assistant] The explicit filtering by instance military academy (wd:Q189008) and staff college (wd:Q1115050) returned no results. This indicates that the schools Douglas MacArthur attended might not be directly typed as these instances. I will now try to retrieve the schools without filtering by instance but exclude the Milwaukee High School of the Arts by its specific entity ID (wd:Q6861744) to get a more accurate list.

[Tool]
Got 2 rows and 2 columns:
| school                                                             | schoolLabel                                               |
| ------------------------------------------------------------------ | --------------------------------------------------------- |
| United States Army Command and General Staff College (wd:Q1115050) | United States Army Command and General Staff College (en) |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the educational institutions attended by Douglas MacArthur, excluding the irrelevant Milwaukee High School of the Arts. The answer lists the United States Military Academy and the United States Army Command and General Staff College, which are historically accurate. The query follows best practices by returning identifiers and labels, and the explanation clarifies the exclusion of the unlikely school. Overall, the output is correct and complete.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?actor ?actorLabel WHERE {
  wd:Q3577037 p:P161 ?castStatement .
  ?castStatement ps:P161 ?actor ; pq:P453 wd:Q3036775 .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel FILTER ( LANG( ?actorLabel ) = "en" )
  }
}

The actor who played Donna Moss on The West Wing is Janel Moloney.

[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

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 played donna on west wing?

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

[Tool]
Example 1:
Question:
who plays claudia joy on army wives?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2308037 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q5129199 .
}

Using entities:
Army Wives (wd:Q2308037): American television series
Claudia Joy Holden (wd:Q5129199): fictional character

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as ps/p): 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:
who plays moira on the l word?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q216792 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q3319244 .
}

Using entities:
The L Word (wd:Q216792): American-Canadian television series
Max Sweeney, also known as Moira Sweeney (wd:Q3319244): fictional character from the television series The L Word

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as ps/p): 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 plays meg in family guy?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5930 p:P725 ?p .
  ?p ps:P725 ?x ; pq:P453 wd:Q908772 .
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom
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

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 ps/p): 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

[Assistant]
From the examples, the pattern to find who played a character in a TV series is:
- Use the TV series entity with property P161 (cast member)
- Use the character role qualifier P453 to specify the character

Next, I need to find the Wikidata entity for "The West Wing" and the entity for the character "Donna" in that series. Then I will use the pattern to find the actor who played Donna on The West Wing. I will start by searching for the entity "The West Wing".

[Tool]
Top 10 entity alternatives:
1. The West Wing, also known as West Wing (wd:Q3577037): American political drama series created by Aaron Sorkin for NBC (1999–2006)
2. West Wing, also known as the West Wing, West Wing of the White House, White House West Wing (wd:Q1932621): west office section of the White House, Washington DC, USA
3. McGuffey Hall, also known as The West Wing (wd:Q123015331): building of Ohio University in Athens, Ohio, USA
4. The West Wing (wd:Q130511003): song by Akuma Kira
5. The West Wing (wd:Q130511005): instrumental track by Akuma Kira, Jarren Crist and Nolan Reese; 2015 studio recording
6. Pilot, also known as The West Wing pilot (wd:Q7194391): episode of The West Wing (S1 E1)
7. The West Wing Weekly (wd:Q28127811): American podcast
8. The West Wing Thing (wd:Q104867287): American podcast series
9. The West Wing, season 5 (wd:Q3730540): season of television series
10. The West Wing, season 4 (wd:Q3730539): season of television series

[Assistant] The entity for the TV series "The West Wing" is wd:Q3577037. Next, I will search for the character "Donna" related to this series. I will search for the entity "Donna West Wing" to find the character entity.

[Tool]
Top 10 entity alternatives:
1. The West Wing, also known as West Wing (wd:Q3577037): American political drama series created by Aaron Sorkin for NBC (1999–2006)
2. West Wing, also known as the West Wing, West Wing of the White House, White House West Wing (wd:Q1932621): west office section of the White House, Washington DC, USA
3. Donna West (wd:Q130267686): clinical assistant professor of nursing, clinical assistant professor
4. Donna E West, also known as Donna West (wd:Q85753634): researcher
5. West Wing (wd:Q26387306): building in Ringwood, New Forest, Hampshire, England, UK
6. First Assessment, also known as West Crow Wing, Minnesota, West Crow Wing (wd:Q5862254): unorganized territory of Crow Wing County, Minnesota, US
7. East Wing West Wing (wd:Q5329697): Hong Kong Drama Series
8. West Wing Week (wd:Q7987008): Weekly web-episode produced by The White House about the week's events concerning the President of the United States.
9. Buffalo West Wing (wd:Q30632637): 2011 novel by Julie Hyzy
10. McGuffey Hall, also known as The West Wing (wd:Q123015331): building of Ohio University in Athens, Ohio, USA

[Assistant] There is no direct entity for the character "Donna" from The West Wing in the search results. I will try to find the cast members of The West Wing (wd:Q3577037) and check if any of them have a character role "Donna". I will list the cast members with their character roles for The West Wing.

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

[Assistant] The query failed because the SERVICE wikibase:label is not supported by the endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use optional rdfs:label for actor and character.

[Tool]
Got 10 rows and 4 columns:
| actor                           | actorLabel             | character                    | characterLabel      |
| ------------------------------- | ---------------------- | ---------------------------- | ------------------- |
| Stockard Channing (wd:Q1117390) | Stockard Channing (en) | Abbey Bartlet (wd:Q3603297)  | Abbey Bartlet (en)  |
| Janel Moloney (wd:Q114447)      | Janel Moloney (en)     | Donna Moss (wd:Q3036775)     | Donna Moss (en)     |
| Martin Sheen (wd:Q184572)       | Martin Sheen (en)      | Josiah Bartlet (wd:Q2715593) | Josiah Bartlet (en) |
| Allison Janney (wd:Q229487)     | Allison Janney (en)    | C. J. Cregg (wd:Q1080587)    | C. J. Cregg (en)    |
| Rob Lowe (wd:Q296505)           | Rob Lowe (en)          | Sam Seaborn (wd:Q3946354)    | Sam Seaborn (en)    |
| Bradley Whitford (wd:Q352180)   | Bradley Whitford (en)  | Josh Lyman (wd:Q5656906)     | Josh Lyman (en)     |
| John Spencer (wd:Q352748)       | John Spencer (en)      | Leo McGarry (wd:Q6524042)    | Leo McGarry (en)    |
| Richard Schiff (wd:Q355209)     | Richard Schiff (en)    | Toby Ziegler (wd:Q1345373)   | Toby Ziegler (en)   |
| Dulé Hill (wd:Q458664)          | Dulé Hill (en)         | Charlie Young (wd:Q3666688)  | Charlie Young (en)  |
| Joshua Malina (wd:Q60422)       | Joshua Malina (en)     | Will Bailey (wd:Q8002690)    | Will Bailey (en)    |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the actor who played the character Donna Moss on The West Wing by using the character role qualifier on the cast member property. The query returns the expected actor Janel Moloney with the correct label. The answer is accurate and complete, and the query follows the guidelines for returning identifiers and labels properly. No further refinement is needed.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?country ?countryLabel WHERE {
  ?country wdt:P37 wd:Q188 ; wdt:P31 wd:Q6256 .
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = "en" )
  }
}

Got 6 rows and 2 columns:
| country                 | countryLabel       |
| ----------------------- | ------------------ |
| Germany (wd:Q183)       | Germany (en)       |
| Belgium (wd:Q31)        | Belgium (en)       |
| Luxembourg (wd:Q32)     | Luxembourg (en)    |
| Liechtenstein (wd:Q347) | Liechtenstein (en) |
| Switzerland (wd:Q39)    | Switzerland (en)   |
| Austria (wd:Q40)        | Austria (en)       |

The current recognized countries where German is an official language are Germany, Belgium, Luxembourg, Liechtenstein, Switzerland, and Austria.

[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

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] which countries speak german officially?

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

[Tool]
Example 1:
Question:
what countries in the world speak german?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q188 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
German, also known as de, German language (wd:Q188): West Germanic language spoken mainly in Central Europe
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 2:
Question:
what countries speak german as a first language?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 wd:Q6256 ; wdt:P37 wd:Q188 .
}

Using entities:
German, also known as de, German language (wd:Q188): West Germanic language spoken mainly in Central Europe
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 3:
Question:
where is german an official language?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q188 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
German, also known as de, German language (wd:Q188): West Germanic language spoken mainly in Central Europe
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

[Tool]
Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| country                                 | countryLabel             |
| --------------------------------------- | ------------------------ |
| Brandenburg-Prussia (wd:Q157367)        | Brandenburg-Prussia (en) |
| Germany (wd:Q183)                       | Germany (en)             |
| Asgardia (wd:Q27304761)                 | Asgardia (en)            |
| Belgium (wd:Q31)                        | Belgium (en)             |
| Luxembourg (wd:Q32)                     | Luxembourg (en)          |
| ...                                     | ...                      |
| Austria (wd:Q40)                        | Austria (en)             |
| German Empire (wd:Q43287)               | German Empire (en)       |
| Grand Duchy of Westarctica (wd:Q551375) | Westarctica (en)         |
| Denmark–Norway (wd:Q62651)              | Denmark–Norway (en)      |
| Kugelmugel (wd:Q877579)                 | Kugelmugel (en)          |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves entities that have German as an official language and are instances or subclasses of countries. However, the result includes historical or special entities (e.g., Brandenburg-Prussia, German Empire, Asgardia) that are not current recognized countries. The user likely expects current countries where German is an official language. To improve, the query should be refined to filter for current sovereign states or recognized countries, excluding historical or micronations. This can be done by adding a filter for instance of 'sovereign state' (wd:Q3624078) or similar. Also, the answer should clarify that some entities are historical or special cases and distinguish them from current countries.

[Assistant] Thank you for the feedback. I will refine the query to only include current recognized sovereign states where German is an official language, excluding historical or special entities. I will filter for instance of "sovereign state" (wd:Q3624078) to achieve this. Then I will provide a clearer answer distinguishing current countries from historical or special cases.

[Tool]
Got 7 rows and 2 columns:
| country                   | countryLabel       |
| ------------------------- | ------------------ |
| Germany (wd:Q183)         | Germany (en)       |
| Belgium (wd:Q31)          | Belgium (en)       |
| Luxembourg (wd:Q32)       | Luxembourg (en)    |
| Liechtenstein (wd:Q347)   | Liechtenstein (en) |
| Switzerland (wd:Q39)      | Switzerland (en)   |
| Austria (wd:Q40)          | Austria (en)       |
| German Empire (wd:Q43287) | German Empire (en) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves countries where German is an official language, but it also includes the German Empire, which is a historical entity and not a current sovereign state. To improve the query, add a filter to exclude historical or non-sovereign entities, for example by ensuring the country is a current sovereign state (wdt:P31 wd:Q6256) instead of a broader class like wd:Q3624078. This will provide a more accurate list of current countries where German is officially spoken.

[Assistant] Thanks for the feedback. I will refine the query to include only entities that are instances of "country" (wd:Q6256) to ensure we get current recognized countries where German is an official language, excluding historical or non-sovereign entities like the German Empire.

[Tool]
Got 6 rows and 2 columns:
| country                 | countryLabel       |
| ----------------------- | ------------------ |
| Germany (wd:Q183)       | Germany (en)       |
| Belgium (wd:Q31)        | Belgium (en)       |
| Luxembourg (wd:Q32)     | Luxembourg (en)    |
| Liechtenstein (wd:Q347) | Liechtenstein (en) |
| Switzerland (wd:Q39)    | Switzerland (en)   |
| Austria (wd:Q40)        | Austria (en)       |

[Tool] Stopped generation process