PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT DISTINCT ?actor ?actorLabel WHERE {
  ?production p:P161 ?castStatement .
  ?castStatement ps:P161 ?actor ; pq:P453 wd:Q51746 .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel FILTER ( LANG( ?actorLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| actor                       | actorLabel         |
| --------------------------- | ------------------ |
| Peter Shukoff (wd:Q1280173) | Peter Shukoff (en) |
| Mark Hamill (wd:Q210447)    | Mark Hamill (en)   |
| Seth Gamble (wd:Q3069394)   | Seth Gamble (en)   |

The actors who have played Luke Skywalker include Mark Hamill, Peter Shukoff, and Seth Gamble.

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

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

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

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

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

[User] who would play luke skywalker?

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

[Tool]
Example 1:
Question:
who play luke skywalker?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q51746 .
}

Using entities:
Luke Skywalker, also known as Luke Starkiller (wd:Q51746): fictional character from Star Wars, starship pilot, mechanic, rebel, Jedi

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

Example 2:
Question:
who played luke skywalker in star wars episode 4?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q17738 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q51746 .
}

Using entities:
Star Wars: Episode IV – A New Hope, also known as 1977 Star Wars, A New Hope, Star Wars, Star Wars: A New Hope, Star Wars: Episode IV (wd:Q17738): 1977 film directed by George Lucas
Luke Skywalker, also known as Luke Starkiller (wd:Q51746): fictional character from Star Wars, starship pilot, mechanic, rebel, Jedi

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

Example 3:
Question:
where does luke skywalker live in star wars?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q51746 wdt:P1165 ?x .
}

Using entities:
Luke Skywalker, also known as Luke Starkiller (wd:Q51746): fictional character from Star Wars, starship pilot, mechanic, rebel, Jedi

Using properties:
home world, also known as homeworld, home planet (wd:P1165 as wdt): home planet or natural satellite for a fictional character or species

[Assistant]
From the examples, I see that Luke Skywalker is identified as wd:Q51746 in Wikidata. The property for cast member or actor in a production is P161, and the qualifier for the character role played is P453. To find who would play Luke Skywalker, I need to find entities that are cast members in productions with the character role Luke Skywalker.

I will now write a SPARQL query to find actors who played the character Luke Skywalker in any production.

[Tool]
Got 3 rows and 2 columns:
| actor                       | actorLabel         |
| --------------------------- | ------------------ |
| Peter Shukoff (wd:Q1280173) | Peter Shukoff (en) |
| Mark Hamill (wd:Q210447)    | Mark Hamill (en)   |
| Seth Gamble (wd:Q3069394)   | Seth Gamble (en)   |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?country WHERE {
  ?country wdt:P37 wd:Q1321 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Got 27 rows and 1 column, showing the first 5 and last 5 rows below:
| country                                                        |
| -------------------------------------------------------------- |
| Tilandia Kingdom (wd:Q130337131)                               |
| Kingdom of Patones (wd:Q131839713)                             |
| Gay and Lesbian Kingdom of the Coral Sea Islands (wd:Q1423680) |
| Republic of Cuba (wd:Q14905932)                                |
| Cuba (wd:Q241)                                                 |
| ...                                                            |
| Costa Rica (wd:Q800)                                           |
| Panama (wd:Q804)                                               |
| Nicaragua (wd:Q811)                                            |
| Mexico (wd:Q96)                                                |
| Equatorial Guinea (wd:Q983)                                    |

The countries that have Spanish as the national language are returned by the query.

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

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

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

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

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

[User] what countries have spanish as the national language?

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

[Tool]
Example 1:
Question:
what countries has spanish as their official language?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q1321 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
Spanish, also known as Castilian, Castilian language, es, esp, Español (wd:Q1321): Romance language originating in the Iberian Peninsula
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 spanish wikipedia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q1321 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
Spanish, also known as Castilian, Castilian language, es, esp, Español (wd:Q1321): Romance language originating in the Iberian Peninsula
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 3:
Question:
what countries use english as national language?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q1860 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
English, also known as English (language), The English language, English the Global Language, English-language, English language (wd:Q1860): West Germanic language
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

[Assistant] From the examples, it is clear that the property for official language is wdt:P37 and the entity for Spanish language is wd:Q1321. The entity for country is wd:Q6256. The query should select countries that have Spanish as an official language. I will now write the SPARQL query to get the countries that have Spanish as the national language.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?speciality ?specialityLabel WHERE {
  wd:Q193637 wdt:P413 ?speciality .
  OPTIONAL {
    ?speciality rdfs:label ?specialityLabel FILTER ( LANG( ?specialityLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| speciality                 | specialityLabel    |
| -------------------------- | ------------------ |
| small forward (wd:Q308879) | small forward (en) |

Scottie Pippen was good at the position of small forward in basketball.

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

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

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

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

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

[User] what was scottie pippen good at?

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

[Tool]
Example 1:
Question:
what year did scottie pippen come into the nba?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q193637 p:P54 ?p .
  ?p ps:P54 ?y .
  ?y wdt:P118 wd:Q155223 .
  ?p pq:P580 ?x .
}
ORDER BY ?x
LIMIT 1

Using entities:
National Basketball Association, also known as Basketball Association of America, BAA, NBA, National Basketball Assn., Nat'l Basketball Assn. (wd:Q155223): North American professional men's basketball league
Scottie Pippen, also known as No Tippin' Pippen, Scotty Maurice Pippen, Scott Pippen, Robin, Pip (wd:Q193637): American basketball player, basketball player, actor

Using properties:
league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt): league or competition in which team or player has played, or in which an event occurs, participant in
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/ps): sports teams or clubs that the subject represents or represented, member of
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time

Example 2:
Question:
what position did john stockton play?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q213346 wdt:P413 ?x .
}

Using entities:
John Stockton, also known as Stock, John Houston Stockton (wd:Q213346): American basketball player, basketball player

Using properties:
position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as wdt): position or specialism of a player on a team

Example 3:
Question:
who did kevin garnett play for before celtics?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q189240 p:P54 ?p .
  ?p ps:P54 ?x ; pq:P582 ?y .
  wd:Q189240 p:P54 ?q .
  ?q ps:P54 wd:Q131371 ; pq:P580 ?z .
  FILTER ( ?y <= ?z )
}

Using entities:
Boston Celtics, also known as Celtics, Celts, C's, Green and White (wd:Q131371): NBA team based in Boston; tied with most NBA Championships
Kevin Garnett, also known as The Kid, The Big Ticket, KG, Kevin Maurice Garnett (wd:Q189240): American retired professional basketball player and actor, basketball player, actor

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/ps): sports teams or clubs that the subject represents or represented, member of
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

[Assistant]
The question "what was Scottie Pippen good at?" is asking about the skills or abilities Scottie Pippen was known for. In Wikidata, this kind of information is often represented by the property "skill" (wdt:P802) or "notable work" or "occupation" or "position played on team / speciality" (wdt:P413) for athletes.

I will first search for Scottie Pippen in Wikidata to get his entity ID. Then I will look for properties related to skills or specialties associated with him.

[Tool]
Top 10 entity alternatives:
1. Scottie Pippen, also known as No Tippin' Pippen, Scotty Maurice Pippen, Scott Pippen, Robin, Pip (wd:Q193637): American basketball player, basketball player, actor
2. Scotty Pippen Jr., also known as Scottie Pippen Jr. (wd:Q100901254): American basketball player, basketball player
3. Slam City with Scottie Pippen (wd:Q3486520): 1994 video game
4. Scottish Terrier, also known as Aberdeen Terrier, Scottie, Scotty Dog (wd:Q39035): dog breed
5. 2024 in anime, also known as Scottie (wd:Q116673398): overview of anime-related events during the year of 2024
6. Pippen, also known as Pippen (surname), Pippen (family name) (wd:Q7197481): family name
7. pronunciation respelling for English, also known as Scottie (wd:Q7249972): non-IPA notation used to convey the pronunciation of English words (lookig like "lew-TEE-shee-əm")
8. Scottie (wd:Q7437589): album by Shirley Scott
9. English-language vowel changes before historic /r/, also known as Scottie (wd:Q5378157): vowel shifts
10. IBM Open Class, also known as scottie (wd:Q5968916): C++ class library

[Assistant] Scottie Pippen's Wikidata entity is wd:Q193637. Now I will search for properties related to skills or specialties for Scottie Pippen. I will start by searching for properties related to "skill" or "specialty" for this entity.

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
3. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
4. sport, also known as play, plays, sport played, sports (wd:P641 as p/wdt): sport that the subject participates or participated in or is associated with
5. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team
8. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as p/wdt): country a person or a team represents when playing a sport, country
9. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
10. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception

No other items found

[Assistant] The property "position played on team / speciality" (wdt:P413) seems to be the most relevant to what Scottie Pippen was good at in the context of basketball. I will query the values of this property for Scottie Pippen.

[Tool]
Got 1 row and 2 columns:
| speciality                 | specialityLabel    |
| -------------------------- | ------------------ |
| small forward (wd:Q308879) | small forward (en) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?continent WHERE {
  wd:Q16 wdt:P30 ?continent .
}

Got 1 row and 1 column:
| continent              |
| ---------------------- |
| North America (wd:Q49) |

Canada belongs to the continent North America.

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

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

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

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

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

[User] what continent does canada belong to?

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

[Tool]
Example 1:
Question:
on what continent is canada found?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q16 wdt:P30 ?x .
}

Using entities:
Canada, also known as CA, CAN, Dominion of Canada, ISO 3166-1:CA (wd:Q16): country in North America

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature

Example 2:
Question:
what continent does the bahamas belong to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q778 wdt:P30 ?x .
}

Using entities:
The Bahamas, also known as BAH, Bahama Islands, Bahamas, bs, Commonwealth of the Bahamas (wd:Q778): island sovereign state in the West Indies

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature

Example 3:
Question:
what continent do the falkland islands belong to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9648 wdt:P30 ?x .
}

Using entities:
Falkland Islands, also known as 🇫🇰, Falklands, FK, FLK, Islas Malvinas (wd:Q9648): archipelago in the South Atlantic Ocean, and a British Overseas Territory, disputed by Argentina

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature

[Assistant]
From the similar examples, we see that the entity for Canada is wd:Q16 and the property for continent is wdt:P30. The query to find the continent of Canada is:

SELECT DISTINCT ?continent WHERE {
  wd:Q16 wdt:P30 ?continent .
}

I will now execute this query to get the continent of Canada.

[Tool]
Got 1 row and 1 column:
| continent              |
| ---------------------- |
| North America (wd:Q49) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?government ?governmentLabel WHERE {
  wd:Q30 wdt:P122 ?government .
  OPTIONAL {
    ?government rdfs:label ?governmentLabel FILTER ( LANG( ?governmentLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| government                      | governmentLabel          |
| ------------------------------- | ------------------------ |
| presidential system (wd:Q49892) | presidential system (en) |
| federal republic (wd:Q512187)   | federal republic (en)    |
| republic (wd:Q7270)             | republic (en)            |

The United States currently has a government that is described as a presidential system, a federal republic, and a republic.

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

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

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

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

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

[User] what kind of government does the united states have currently?

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

[Tool]
Example 1:
Question:
what kind of government does the united states have today?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q30 wdt:P122 ?x .
}

Using entities:
United States, also known as the U.S. of A, United States of America, the US of America, United States of North America, U. S. (wd:Q30): country primarily located in North America

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as wdt): subject's government

Example 2:
Question:
what type of government is the us government?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q30 wdt:P122 ?x .
}

Using entities:
United States, also known as the U.S. of A, United States of America, the US of America, United States of North America, U. S. (wd:Q30): country primarily located in North America

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as wdt): subject's government

Example 3:
Question:
what kind of system of government does the united states have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q30 wdt:P122 ?x .
}

Using entities:
United States, also known as the U.S. of A, United States of America, the US of America, United States of North America, U. S. (wd:Q30): country primarily located in North America

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as wdt): subject's government

[Tool]
Got 3 rows and 2 columns:
| government                      | governmentLabel          |
| ------------------------------- | ------------------------ |
| presidential system (wd:Q49892) | presidential system (en) |
| federal republic (wd:Q512187)   | federal republic (en)    |
| republic (wd:Q7270)             | republic (en)            |

[Tool] Stopped generation process


PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT ?startTime WHERE {
  wd:Q33866 p:P39 ?statement .
  ?statement ps:P39 wd:Q11696 ; pq:P580 ?startTime .
}

Theodore Roosevelt took office as President of the United States on September 14, 1901.

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

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

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

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

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

[User] when did president theodore roosevelt take office?

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

[Tool]
Example 1:
Question:
what state was theodore roosevelt from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q33866 p:P19 ?p .
  ?p ps:P19 ?x .
  ?x wdt:P31 wd:Q107390 .
}

Using entities:
federated state, also known as state in a federation, state of a federation, state, federal state, constituent state (wd:Q107390): territorial and constitutional community forming part of a federal union
Theodore Roosevelt, also known as Theodore Roosevelt, Jr., Teddy Roosevelt (wd:Q33866): 26th President of the United States from 1901 to 1909, husbandry worker, conservationist, autobiographer, ornithologist, statesperson, naturalist, politician, historian, explorer, essayist, diarist, writer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/ps): most specific known birth location of a person, animal or fictional character, location
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
who became president when roosevelt died in office?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q8007 p:P39 ?p .
  ?p ps:P39 wd:Q11696 ; pq:P1366 ?x .
}

Using entities:
President of the United States, also known as US President, U.S. President, United States President, the president of the United States, President of the U.S. (wd:Q11696): head of state and head of government of the United States of America
Franklin Delano Roosevelt, also known as Roosevelt, President Roosevelt, Franklin Roosevelt, Franklin D. Roosevelt, F. D. Roosevelt (wd:Q8007): president of the United States from 1933 to 1945, statesperson

Using properties:
replaced by, also known as heir, superseded by, successor, succeeded by, next job holder (wd:P1366 as pq): other person or item which continues the item by replacing it in... nor identical, but adds to the series (e.g. books in a series)., followed by
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office

Example 3:
Question:
what was theodore roosevelt's political party?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q33866 wdt:P102 ?x .
}

Using entities:
Theodore Roosevelt, also known as Theodore Roosevelt, Jr., Teddy Roosevelt (wd:Q33866): 26th President of the United States from 1901 to 1909, husbandry worker, conservationist, autobiographer, ornithologist, statesperson, naturalist, politician, historian, explorer, essayist, diarist, writer

Using properties:
member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as wdt): the political party of which a person is or has been a member or otherwise affiliated, member of

[Assistant]
From the examples, I see that Theodore Roosevelt is identified as wd:Q33866 in Wikidata. The property "position held" (wdt:P39) is used to indicate offices held by a person. To find when Theodore Roosevelt took office as president, I should look for the "start time" (wdt:P580) qualifier of the statement where he held the position of "President of the United States" (wd:Q11696).

I will now write a SPARQL query to find the start time of Theodore Roosevelt's presidency.

[Tool]
Got 1 row and 1 column:
| startTime                           |
| ----------------------------------- |
| 1901-09-14T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?location ?locationLabel WHERE {
  wd:Q214524 wdt:P276 ?location .
  OPTIONAL {
    ?location rdfs:label ?locationLabel FILTER ( LANG( ?locationLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| location                | locationLabel   |
| ----------------------- | --------------- |
| Gettysburg (wd:Q694550) | Gettysburg (en) |

The Gettysburg Address was delivered at Gettysburg.

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

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

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

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

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

[User] where did the gettysburg address?

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

[Tool]
Example 1:
Question:
where was the gettysburg war located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q33132 wdt:P276 ?x .
}

Using entities:
Battle of Gettysburg (wd:Q33132): 1863 battle of the American Civil War

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

Example 2:
Question:
where did chancellorsville battle take place?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q745979 wdt:P276 ?x .
}

Using entities:
Battle of Chancellorsville (wd:Q745979): 1863 major battle of the American Civil War

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

Example 3:
Question:
in what state did the bloody battle of antietam take place?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q719252 wdt:P276 ?p .
  ?p wdt:P131 + ?x .
  ?x wdt:P31 wd:Q107390 .
}

Using entities:
federated state, also known as state in a federation, state of a federation, state, federal state, constituent state (wd:Q107390): territorial and constitutional community forming part of a federal union
Battle of Antietam, also known as Battle of Sharpsburg (wd:Q719252): 1862 major battle of the American Civil War

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
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] The Gettysburg Address is a famous speech. To find where it was delivered, I will first search for the entity "Gettysburg Address" in Wikidata to get its identifier. Then I will look for properties related to the location of this speech.

[Tool]
Top 10 entity alternatives:
1. Gettysburg Address (wd:Q214524): speech by U.S. President Abraham Lincoln
2. Gettysburg Address (wd:Q19046068): version of the text inscribed on the walls at the Lincoln Memorial in Washington, D.C.
3. The Gettysburg Address, also known as Gettysburg Address (wd:Q17097518): 2017 film directed by Sean Conant
4. A Gettysburg Address (wd:Q4656986): episode of Homeland (S2 E6)
5. Address at Gettysburg, also known as The Gettysburg Address (wd:Q56524787): version of Lincoln's speech, 1898 publication
6. Lincoln's Gettysburg Address (wd:Q3832569): 1912 short film
7. The Gettysburg Address (wd:Q14752119): live album by Moon Safari
8. Lincoln's Gettysburg Address (wd:Q76440716): print in the National Gallery of Art (NGA 144034)
9. Lincoln's Gettysburg Address (wd:Q100307054): newspaper published in New York, New York
10. The Gettysburg Address (wd:Q87280588): episode of In Our Time

[Assistant] The entity "Gettysburg Address" as a speech by U.S. President Abraham Lincoln is wd:Q214524. Now I will search for properties related to the location of this speech. Likely properties could be "location," "place," or similar. I will search for properties of this entity with the query "location."

[Tool]
Top 10 property alternatives:
1. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
2. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
3. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
4. full work available at URL, also known as full text available at, full text available at URL, full text url, online mirror, online version (wd:P953 as p/wdt): URL of a web page containing the full body of this item, URL
5. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
6. title, also known as name, titled, page name, original title, known as (wd:P1476 as p/wdt): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
7. author, also known as writer, written by, poet, playwright, maker (wd:P50 as p/wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
8. main subject, also known as primary topic, primary subject, primary keyword, plot keyword, of (wd:P921 as p/wdt): primary topic of a work (see also P180: depicts), depicts
9. point in time, also known as at time, as of, year, when, time of event (wd:P585 as p/wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
10. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as p/wdt): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))

No other items found

[Assistant] The property "location" (wdt:P276) seems to be the most suitable property for the location of the Gettysburg Address. I will now write a SPARQL query to find the location where the Gettysburg Address (wd:Q214524) took place using this property.

[Tool]
Got 1 row and 2 columns:
| location                | locationLabel   |
| ----------------------- | --------------- |
| Gettysburg (wd:Q694550) | Gettysburg (en) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?occupation ?occupationLabel WHERE {
  wd:Q5702260 wdt:P106 ?occupation .
  OPTIONAL {
    ?occupation rdfs:label ?occupationLabel FILTER ( LANG( ?occupationLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| occupation                | occupationLabel |
| ------------------------- | --------------- |
| film actor (wd:Q10800557) | film actor (en) |
| actor (wd:Q33999)         | actor (en)      |
| model (wd:Q4610556)       | model (en)      |

Helen Flanagan is an English film actor, actor, and model.

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

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

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

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

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

[User] what does helen flanagan do?

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

[Tool]
Example 1:
Question:
what did florence sabin do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q449487 wdt:P106 ?x .
}

Using entities:
Florence R. Sabin, also known as Florence Rena Sabin, Florence Sabin (wd:Q449487): American medical scientist (1871–1953), university teacher, physician, scientist, anatomist

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

Example 2:
Question:
what does annie leibovitz do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q225283 wdt:P106 ?x .
}

Using entities:
Annie Leibovitz, also known as Anna-Lou Leibovitz (wd:Q225283): American photographer (born 1949), fashion photographer, film director, photographer

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

[Assistant] The examples suggest that the property "occupation" (wdt:P106) is used to find out what a person does. Next, I will search for the entity "Helen Flanagan" in Wikidata to get her identifier. Then I will query her occupation using the property wdt:P106.

[Tool]
Top 10 entity alternatives:
1. Helen Flanagan (wd:Q5702260): English actress, film actor, model, actor
2. Helen Anna Flanagan (wd:Q108477380): performance artist, visual artist, video artist, artist
3. Helen of Troy, also known as Helen, Helen of Argos, Helen of Sparta (wd:Q164061): daughter of Zeus in Greek mythology
4. Helen, also known as Helen, GA, Helen, Georgia (wd:Q1601823): city in White County, Georgia, United States
5. Helen, also known as Helen Khan, Helen Richardson Khan, Helen Jairag Richardson, Helen Ann Richardson Khan (wd:Q467223): Indian film actress and dancer of Anglo-Burmese descent, television actor, film actor, dancer
6. Flanagan, also known as Flanagan, Illinois (wd:Q1929330): human settlement in Illinois, United States of America
7. Helen, also known as Eur. Hel. (wd:Q1248812): ancient Greek tragedy by Euripides
8. Nakajima Ki-49 Donryu, also known as Helen bomber, Type 100 Heavy Bomber, Storm Dragon, Ki49, Ki-49 (wd:Q1393091): Japanese bomber aircraft
9. Helen, also known as Helen, West Virginia, Helen, WV (wd:Q511980): census designated place in Raleigh County, West Virginia, United States
10. Helen, also known as Helen (first name), Helen (given name) (wd:Q13376892): female given name

[Assistant] The entity "Helen Flanagan" corresponds to wd:Q5702260 in Wikidata. Now I will query the occupation (wdt:P106) of Helen Flanagan (wd:Q5702260).

[Tool]
Got 3 rows and 2 columns:
| occupation                | occupationLabel |
| ------------------------- | --------------- |
| film actor (wd:Q10800557) | film actor (en) |
| actor (wd:Q33999)         | actor (en)      |
| model (wd:Q4610556)       | model (en)      |

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT DISTINCT ?senator ?senatorLabel WHERE {
  ?senator p:P39 ?positionStatement .
  ?positionStatement ps:P39 wd:Q4416090 .
  ?positionStatement pq:P768 ?seat .
  FILTER ( ?seat IN ( wd:Q101498874 , wd:Q101498986 ) ) .
  FILTER NOT EXISTS {
    ?positionStatement pq:P582 ?endTime
  }
  OPTIONAL {
    ?senator rdfs:label ?senatorLabel FILTER ( LANG( ?senatorLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| senator                          | senatorLabel            |
| -------------------------------- | ----------------------- |
| John Fetterman (wd:Q3181500)     | John Fetterman (en)     |
| David H. McCormick (wd:Q5234544) | David H. McCormick (en) |

The current U.S. senators of Pennsylvania are John Fetterman and David H. McCormick.

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

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

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

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

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

[User] who are the u s senators of pennsylvania?

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

[Tool]
Example 1:
Question:
who are senators from new jersey?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 .
  ?p pq:P768 ?y .
  ?y wdt:P131 wd:Q1408 .
  FILTER NOT EXISTS {
    ?p pq:P582 ?z .
  }
}

Using entities:
New Jersey, also known as Garden State, US-NJ, the State of New Jersey, the Garden State, State of New Jersey (wd:Q1408): 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 p/ps): 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 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 p/ps): 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 united states 2010?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2011-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2010-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): 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

[Assistant]
From the examples, the query to find U.S. senators of a state involves:
- Finding entities with position held (P39) as United States senator (Q4416090)
- Filtering by electoral district (P768) which is the state entity
- Filtering out those whose position has ended (no end time P582)

Now I need to find the Wikidata entity for Pennsylvania.

[Tool]
Top 10 entity alternatives:
1. Pennsylvania, also known as PA, Pa., US-PA, State of Pennsylvania, Pennsylvania, United States (wd:Q1400): state of the United States of America
2. Pennsylvania, also known as US-PA, State of Pennsylvania, Pennsylvania, United States, Penna., Pa. (wd:Q1400): state of the United States of America
3. Province of Pennsylvania, also known as Colony of Pennsylvania, Pennsylvania, Pennsylvania Colony (wd:Q2475732): former colony in North America, part of Great Britain
4. Pennsylvania, also known as Pennsylvania, AL (wd:Q18392474): unincorporated community in Alabama
5. Pennsylvania (wd:Q3960056): state song of Pennsylvania, United States
6. Pennsylvania (wd:Q7163626): suburb in Exeter, Devon, England, UK
7. Pennsylvania (wd:Q1777290): steamboat
8. Pennsylvania (wd:Q7163634): album by Pere Ubu
9. Pennsylvania (wd:Q23863889): article in Otto's encyclopedia
10. Pennsylvania, also known as IMO 9486958 (wd:Q83651224): ship built in 2012

[Assistant]
The Wikidata entity for the state of Pennsylvania is wd:Q1400. The entity for United States senator is wd:Q4416090.

I will now construct a SPARQL query to find the current U.S. senators of Pennsylvania using these entities and the properties from the examples.

[Tool] Got no rows and 2 columns

[Assistant]
The query returned no results, which might be because the property P768 (electoral district) is not used for the state in this context. Instead, the property P131 (located in the administrative territorial entity) might be used to indicate the state for the senators.

I will modify the query to use P131 instead of P768 to filter senators by Pennsylvania.

[Tool] Got no rows and 2 columns

[Assistant]
The query still returned no results. It seems that the property to indicate the state represented by a U.S. senator might be different or not directly linked with pq:P131 or pq:P768.

I will try a different approach by checking the properties of the position statement for a known U.S. senator from Pennsylvania to find the correct property used for the state. I will first find some U.S. senators from Pennsylvania without filtering by current position and then inspect their position statements.

[Tool]
Got 10 rows and 2 columns:
| senator                           | positionStatement                               |
| --------------------------------- | ----------------------------------------------- |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-0E17F893-5695-45D3-833D-33968D3A29D0 |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-17D33453-4AC4-4508-B668-23AE9E65086C |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-1A5E2017-B106-4AB6-9229-6F8E01855F0F |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-3572BC81-3B09-49A7-926F-BDB3F094D05B |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-35D2231F-A0BF-4049-9106-7FAF3051DA26 |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-411CF54F-DDF6-4C29-B493-7E3FDD288477 |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-43DA9744-65B8-4888-B1F3-2274E9E33DAD |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-4C7098B3-C49B-4FA0-8C24-D7B54730206F |
| Joseph C. O'Mahoney (wd:Q1000051) | s:Q1000051-6CB874C9-B335-4956-9890-84B7E5451BEB |

[Assistant]
The results show position statements for Joseph C. O'Mahoney, but I need to check the properties of these position statements to find the property that links to the state represented.

I will now list the properties and values for one of these position statements to identify the property used for the state or electoral district. I will use the first position statement from the list.

[Tool]
Got 13 rows and 3 columns, showing the first 10 rows below:
| subject                                         | property                       | object                                                        |
| ----------------------------------------------- | ------------------------------ | ------------------------------------------------------------- |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | position held (ps:P39)         | United States senator (wd:Q4416090)                           |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | start time (pq:P580)           | 1949-01-03T00:00:00Z (xsd:dateTime)                           |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | end time (pq:P582)             | 1951-01-03T00:00:00Z (xsd:dateTime)                           |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | electoral district (pq:P768)   | Wyoming Class 1 senate seat (wd:Q101498961)                   |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | parliamentary term (pq:P2937)  | 81st United States Congress (wd:Q4644572)                     |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | parliamentary group (pq:P4100) | Democratic Party (wd:Q29552)                                  |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | elected in (pq:P2715)          | 1946 United States Senate election in Wyoming (wd:Q104947299) |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | wikibase:rank                  | wikibase:NormalRank                                           |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | rdf:type                       | wikibase:BestRank                                             |
| s:Q1000051-0B060BE4-C4D7-4FA5-B403-2C44BE1EA26D | prov:wasDerivedFrom            | ref:5a60f19b90d652b287bdaeffe7b3fe4376d48ce2                  |
| ...                                             | ...                            | ...                                                           |

[Assistant]
The property pq:P768 (electoral district) is used to link to a more specific electoral district entity (e.g., Wyoming Class 1 senate seat).

I will now find the electoral district entities for Pennsylvania to see if there are specific senate seat entities for Pennsylvania.

[Tool]
Top 10 entity alternatives:
1. Pennsylvania Class 1 senate seat, also known as Pennsylvania senate seat (I) (wd:Q101498874): Class 1 United States senate seat for Pennsylvania
2. Pennsylvania Class 3 senate seat, also known as Pennsylvania senate seat (III) (wd:Q101498986): Class 3 United States senate seat for Pennsylvania
3. Pennsylvania State Senate (wd:Q2269864): upper house of the Pennsylvania state legislature
4. Pennsylvania Senate elections (wd:Q16960082): election for state senators in Pennsylvania, U.S.
5. 2020 Pennsylvania Senate election (wd:Q85736721): election for state senators in Pennsylvania, U.S
6. 2006 Pennsylvania Senate election, also known as Pennsylvania Senate elections, 2006 (wd:Q7164171): election for state senators in Pennsylvania, U.S.
7. 2008 Pennsylvania Senate election, also known as Pennsylvania Senate elections, 2008 (wd:Q7164174): election for state senators in Pennsylvania, U.S.
8. 2010 Pennsylvania Senate election, also known as Pennsylvania Senate elections, 2010 (wd:Q7164173): election for state senators in Pennsylvania, U.S.
9. 2022 Pennsylvania Senate election (wd:Q105043699): election for state senators in Pennsylvania, U.S
10. 2024 Pennsylvania Senate election (wd:Q116291187)

[Assistant]
There are two relevant entities for Pennsylvania senate seats:
- Pennsylvania Class 1 senate seat (wd:Q101498874)
- Pennsylvania Class 3 senate seat (wd:Q101498986)

I will now modify the query to filter senators who hold either of these two senate seats as their electoral district and who currently hold the position of United States senator.

[Tool]
Got 2 rows and 2 columns:
| senator                          | senatorLabel            |
| -------------------------------- | ----------------------- |
| John Fetterman (wd:Q3181500)     | John Fetterman (en)     |
| David H. McCormick (wd:Q5234544) | David H. McCormick (en) |

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?character ?characterLabel WHERE {
  ?work wdt:P8345 wd:Q462 .
  ?work p:P161 ?castStatement .
  ?castStatement ps:P161 wd:Q358345 ; pq:P453 ?character .
  OPTIONAL {
    ?character rdfs:label ?characterLabel FILTER ( LANG( ?characterLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| character                    | characterLabel        |
| ---------------------------- | --------------------- |
| Lando Calrissian (wd:Q51799) | Lando Calrissian (en) |

Billy D. Williams played the character Lando Calrissian in Star Wars.

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

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

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

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

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

[User] what character did billy d williams play in star wars?

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

[Tool]
Example 1:
Question:
what was liam neeson's character in star wars?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p wdt:P8345 wd:Q462 ; p:P161 ?y .
  ?y ps:P161 wd:Q58444 ; pq:P453 ?x .
}

Using entities:
Star Wars, also known as 1977 Star Wars (wd:Q462): epic space opera multimedia franchise created by George Lucas
Liam Neeson, also known as William John Neeson (wd:Q58444): Northern Irish actor, television actor, voice actor, stage actor, film actor, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
media franchise, also known as franchise, mass media franchise, media mix, presented in media franchise (wd:P8345 as wdt): this creative work belongs to this media franchise

Example 2:
Question:
who play luke skywalker?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q51746 .
}

Using entities:
Luke Skywalker, also known as Luke Starkiller (wd:Q51746): fictional character from Star Wars, starship pilot, mechanic, rebel, Jedi

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

Example 3:
Question:
who was the voice of darth vader in episode iii?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q42051 p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q51752 .
}

Using entities:
Star Wars: Episode III – Revenge of the Sith, also known as Star Wars Episode III, Star Wars: Episode III -- Revenge of the Sith, Star Wars: Revenge of the Sith (wd:Q42051): 2005 American epic space opera film directed by George Lucas
Anakin Skywalker, also known as Anakin, Ani, General Skywalker, The Chosen One (wd:Q51752): fictional character from Star Wars, Jedi

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

[Assistant]
From the examples, the property P161 (cast member) with the qualifier P453 (character role) is used to find the character played by an actor in a media franchise like Star Wars.

Step 1: Identify the entity for Billy D. Williams.
Step 2: Identify the entity for Star Wars.
Step 3: Query for the character role (P453) played by Billy D. Williams (P161) in Star Wars (P8345).

I will first search for the entity of Billy D. Williams.

[Tool]
Top 10 entity alternatives:
1. Billy Dee Williams, also known as William December Williams Jr., William December "Billy Dee" Williams Jr. (wd:Q358345): American actor (born 1937), recording artist, television actor, screenwriter, voice actor, film actor, novelist, painter, writer, singer, actor
2. Billy Drease Williams, also known as Edreys, Edreys Wajed (wd:Q4912488): record producer, American rapper, songwriter, rapper, singer
3. Billy Williams, also known as William Dennis "Billy" Williams, William Dennis Williams (wd:Q4913466): association football player, footballer, born 1905
4. Billy Dee Williams Self-Portrait (wd:Q47513010): painting by Billy Dee Williams
5. Bill Maynard, also known as Billy Williams (wd:Q3736724): English comedian and actor (1928–2018), association football player, stand-up comedian, television actor, stage actor, actor
6. Billy Williams (wd:Q123745): British cinematographer, camera operator, cinematographer, film actor, actor
7. Billy Williams, also known as Billy Leo Williams (wd:Q4913471): American former professional baseball outfielder, baseball player
8. David Williams, also known as D. Williams (wd:Q1177203): Welsh mathematician working in probability theory, university teacher, mathematician
9. Billy Williams, also known as Wilfred Williams (wd:Q3640062): American basketball player, basketball player
10. Billy Williams, also known as Wilfred Williams (wd:Q863272): African-American singer (1910-1972), singer

[Assistant] The entity for Billy D. Williams is wd:Q358345 (Billy Dee Williams). Now I will search for the entity for Star Wars.

[Tool]
Top 10 entity alternatives:
1. Star Wars, also known as 1977 Star Wars (wd:Q462): epic space opera multimedia franchise created by George Lucas
2. Star Wars: Episode IV – A New Hope, also known as 1977 Star Wars, A New Hope, Star Wars, Star Wars: A New Hope, Star Wars: Episode IV (wd:Q17738): 1977 film directed by George Lucas
3. Star Wars, also known as Star Wars: The Arcade Game (wd:Q54317): 1983 video game
4. Star Wars, also known as Star Wars (Original Motion Picture Soundtrack), Star Wars soundtrack (wd:Q2715371): 1977 soundtrack album
5. Star Wars, also known as 1991 Star Wars, Game Boy Star Wars, NES Star Wars (wd:Q54320): 1991 video game
6. Star Wars (wd:Q30597407): 1977 composition by John Williams
7. Star Wars: Starfighter (wd:Q55225): 2001 video game
8. Star Wars, also known as 1987 Star Wars (wd:Q54319): 1987 video game
9. Star Wars (wd:Q20720789): album by Wilco
10. Star Wars (wd:Q3180475): Japanese manga series

[Assistant] The entity for the Star Wars media franchise is wd:Q462. Now I will construct a SPARQL query to find the character role (P453) played by Billy Dee Williams (wd:Q358345) in the Star Wars media franchise (wd:Q462) using the cast member property (P161) with the qualifier character role (P453).

[Tool]
Got 1 row and 2 columns:
| character                    | characterLabel        |
| ---------------------------- | --------------------- |
| Lando Calrissian (wd:Q51799) | Lando Calrissian (en) |

[Tool] Stopped generation process