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 ?partner ?partnerLabel WHERE {
  wd:Q575689 wdt:P451 ?partner .
  ?partner rdfs:label ?partnerLabel .
  FILTER ( LANG( ?partnerLabel ) = "en" )
}

Got 2 rows and 2 columns:
| partner                        | partnerLabel         |
| ------------------------------ | -------------------- |
| Younes Bendjima (wd:Q55200042) | Younes Bendjima (en) |
| Scott Disick (wd:Q7883337)     | Scott Disick (en)    |

Kourtney Kardashian's boyfriends (unmarried partners) are Younes Bendjima and Scott Disick.

[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 kourtney kardashian boyfriends name?

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

[Tool]
Example 1:
Question:
what religion are people in russia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q159 wdt:P3075 ?x .
}

Using entities:
Russia, also known as Russian Federation, RUS, RU, RF, ISO 3166-1:RU (wd:Q159): country in Eastern Europe and Northern Asia

Using properties:
official religion, also known as established religion, state religion (wd:P3075 as wdt): official religion in this administrative entity

Example 2:
Question:
what country was theodor schwann born in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q76745 wdt:P19 ?x .
}

Using entities:
Theodor Schwann, also known as F. T. Schwann, Schwann (wd:Q76745): German physiologist (1810–1882), university teacher, physiologist, biologist, physician, botanist

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

Example 3:
Question:
who does david beckham play for in 2012?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q10520 p:P54 ?p .
  ?p ps:P54 ?x ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2012-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
David Beckham, also known as Becks, Beckham (wd:Q10520): English association football player, association football player, sports executive, businessperson, entrepreneur, blogger, actor, model

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 is about Kourtney Kardashian's boyfriend's name. First, I need to identify the entity for Kourtney Kardashian in Wikidata. Then, I need to find the property that relates to her boyfriend or romantic partner. Finally, I will query the boyfriend's name.

Step 1: Search for the entity "Kourtney Kardashian" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Kourtney Kardashian, also known as Kourtney Kardashian Barker, Kourtney Mary Kardashian, Kourtney (wd:Q575689): American media personality, model and businesswoman (born 1979), media personality, fashion designer, television actor, businessperson, entrepreneur, socialite, celebrity, actor, model
2. Kardashian (wd:Q56538884): family name
3. Kourtney (wd:Q101065644): unisex given name
4. Kanye West, also known as Ye, Kanye Omari West, Yeezy, Kanye Kardashian, Kanye (wd:Q15935): American rapper, record producer, singer and fashion designer (born 1977), fashion designer, record producer, businessperson, entrepreneur, songwriter, director, singer, rapper
5. Kim Kardashian, also known as Kim Kardashian West, Kim K, Kim K., Kimberly Noel Kardashian-West, Kim Kardashian-West (wd:Q186304): American media personality, businesswoman, model and actress (born 1980), erotic photography model, television producer, fashion designer, entrepreneur, voice actor, celebrity, socialite, blogger, actor, model
6. Khloé Kardashian, also known as Khloé Kardashian Odom, Khloé Kardashian-Odom, Khloe Kardashian Odom, Khloe Kardashian, Khloe Odom (wd:Q231270): American media personality,influencer, businesswoman (born 1984), radio personality, television actor, fashion designer, film producer, manufacturer, entrepreneur, film actor, socialite, celebrity, novelist, writer, actor, model
7. Kris Jenner, also known as Kristen Mary Jenner, Kristen Jenner, Kristen Mary Houghton, Kristen Mary "Kris" Jenner, Chris Jenner (wd:Q1138235): American media personality, socialite, and businesswoman, television presenter, television producer, flight attendant, celebrity, socialite, author, actor
8. Robert Kardashian, also known as Robert George Kardashian, Rob Kardashian, Robert G. Kardashian (wd:Q1816737): American attorney and businessman (1944–2003), entrepreneur, jurist, lawyer
9. Rob Kardashian, also known as Robert Arthur Kardashian (wd:Q26318): American television personality and businessman, television actor, businessperson, socialite, model
10. Kardashian-Jenner family, also known as Kardashian family, Kardashians (wd:Q95747857): American family prominent in entertainment, business, and fashion

[Assistant] I found the entity for Kourtney Kardashian: wd:Q575689. Now I need to find the property that relates to her boyfriend or romantic partner. I will search for properties related to "boyfriend" or "partner" for this entity.

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as p/wdt): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
2. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
3. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as p/wdt): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
4. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as p/wdt): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
5. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
6. sibling, also known as is sister of, is the brother of, is the sibling of, is the sister of, sib (wd:P3373 as p/wdt): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), relative
7. Instagram username, also known as IG username, www.instagram.com, urinsta, ufinsta, Insta ID (wd:P2003 as p/wdt): item's username on Instagram, website username or ID
8. stepparent, also known as step-parent, step parent, stepmother, step-mother, step mother (wd:P3448 as p/wdt): subject has the object as their stepparent, relative
9. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The property "unmarried partner" (wdt:P451) seems to be the most appropriate to represent Kourtney Kardashian's boyfriend or romantic partner.

Now I will write a SPARQL query to get the name of Kourtney Kardashian's unmarried partner using this property.

[Tool]
Got 2 rows and 2 columns:
| partner                        | partnerLabel         |
| ------------------------------ | -------------------- |
| Younes Bendjima (wd:Q55200042) | Younes Bendjima (en) |
| Scott Disick (wd:Q7883337)     | Scott Disick (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 ?country ?countryLabel WHERE {
  wd:Q192955 wdt:P27 ?country .
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| country                  | countryLabel        |
| ------------------------ | ------------------- |
| United Kingdom (wd:Q145) | United Kingdom (en) |
| Canada (wd:Q16)          | Canada (en)         |

Steve Nash has two nationalities: United Kingdom and Canada.

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

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

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

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

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

[User] what is steve nash nationality?

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

[Tool]
Example 1:
Question:
where did dolly parton grew up?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q180453 wdt:P19 ?x .
}

Using entities:
Dolly Parton, also known as Dolly Rebecca Parton, Dolly Parton Dean (wd:Q180453): American singer, songwriter and actress, multi-instrumentalist, singer-songwriter, television actor, recording artist, country musician, record producer, autobiographer, businessperson, country singer, film producer, screenwriter, voice actor, songwriter, film actor, guitarist, composer, banjoist, actor

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

Example 2:
Question:
who are the judges of the supreme court?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P39 ?y .
  ?y wdt:P279 wd:Q20706330 .
}

Using entities:
United States Supreme Court justice, also known as Justice of the Supreme Court of the United States, Justices of the Supreme Court of the United States, Justices of the United States Supreme Court (wd:Q20706330): Chief Justice and associate justice of the Supreme Court of the United States

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
position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt): subject currently or formerly holds the object position or public office

Example 3:
Question:
who does dominic monaghan play in lord of the rings?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q127367 p:P161 ?p .
  ?p ps:P161 wd:Q152165 ; pq:P453 ?x .
}

Using entities:
The Lord of the Rings: The Fellowship of the Ring, also known as Lord of the Rings: The Fellowship of the Ring, The Fellowship of the Ring (wd:Q127367): 2001 film by Peter Jackson
Dominic Monaghan (wd:Q152165): German-born British actor, television actor, screenwriter, 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)

[Assistant] To answer the question "What is Steve Nash's nationality?" we need to find the entity for Steve Nash and then find the property that corresponds to nationality or country of citizenship. Let's first search for the entity "Steve Nash" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Steve Nash, also known as Stephen John Nash (wd:Q192955): Canadian basketball player and coach, basketball player, basketball coach, businessperson, film director
2. Steve Nash (wd:Q16137022): English rugby league footballer and coach, rugby league player
3. Steve Nash (wd:Q48851147): disc jockey
4. Steve Nash (wd:Q42316961): actor
5. Steven Jackson, also known as Steven Nash Jackson (wd:Q3499240): American baseball player, baseball player
6. Steven G. Nash (wd:Q98756087): American politician, businessperson, politician
7. Steven Roy Nash, also known as Dr. Steven Roy Nash (wd:Q76187877): Peerage person ID=590989
8. Edward Mungo Steven Nash, also known as Edward Nash (wd:Q76187880): (born 1990)
9. Nash, also known as Nash, Texas, Nash, TX (wd:Q978847): city in Bowie County, Texas, United States
10. Nash, also known as Nash, OK, Nash, Oklahoma (wd:Q2321969): town in Grant County, Oklahoma, United States

[Assistant] The entity for Steve Nash as a Canadian basketball player and coach is wd:Q192955. Now, I will search for the property related to nationality or country of citizenship for this entity.

[Tool]
Top 10 property alternatives:
1. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
2. 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
3. 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
4. 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
5. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
6. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as p/wdt): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
7. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as p/wdt): the place where the person is or has been, resident, location
8. 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
9. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as p/wdt): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
10. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)

No other items found

[Assistant] The property "country of citizenship" (wdt:P27) corresponds to nationality. Now I will write a SPARQL query to get the nationality (country of citizenship) of Steve Nash (wd:Q192955).

[Tool]
Got 2 rows and 2 columns:
| country                  | countryLabel        |
| ------------------------ | ------------------- |
| United Kingdom (wd:Q145) | United Kingdom (en) |
| Canada (wd:Q16)          | Canada (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 ?country ?countryLabel WHERE {
  ?country wdt:P463 wd:Q181574 .
  ?country wdt:P31 wd:Q6256 .
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| country                | countryLabel       |
| ---------------------- | ------------------ |
| Canada (wd:Q16)        | Canada (en)        |
| United States (wd:Q30) | United States (en) |
| Mexico (wd:Q96)        | Mexico (en)        |

The countries involved in NAFTA (North American Free Trade Agreement) are Canada, the United States, and Mexico.

[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 are involved in the nafta?

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

[Tool]
Example 1:
Question:
who is darwin and what is his theory?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1035 wdt:P106 ?x .
}

Using entities:
Charles Darwin (wd:Q1035): English naturalist and biologist (1809–1882), travel writer, philosopher, ethologist, naturalist, geologist, botanist, explorer, writer

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 time zone is london in right now?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q84 wdt:P421 ?x .
}

Using entities:
London, also known as Loniniensi, Trinovantum, the Big Smoke, Lundenwic, Lundenburh (wd:Q84): capital and largest city of England and the United Kingdom

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

Example 3:
Question:
what year did lakers win their first championship?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?y wdt:P31 / wdt:P279 * wd:Q842375 ; wdt:P1346 wd:Q121783 ; wdt:P585 ?x .
}
ORDER BY ?x
LIMIT 1

Using entities:
Los Angeles Lakers, also known as Lakers, L.A. Lakers, LA Lakers, Minneapolis Lakers, Purple and Gold (wd:Q121783): American professional basketball team
NBA Finals, also known as NBA World Championship Series [until 1987], NBA title, National Basketball Association ...Championship Series [until 1987], BAA World Championship Series [1947-49], Basketball Association of Americ...ld Championship Series [1947-49] (wd:Q842375): championship series of the National Basketball Association, annu...al Basketball Association World Championship Series through 1987

Using properties:
winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as wdt): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
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)
point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)

[Assistant]
The question is about the countries involved in NAFTA. NAFTA stands for the North American Free Trade Agreement. To answer this, I need to find the entity for NAFTA and then find the countries involved in it. Typically, countries involved in a trade agreement are linked by a property like "member" or "participant."

Step 1: Search for the entity "NAFTA" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. North American Free Trade Agreement, also known as NAFTA (wd:Q181574): trade bloc
2. Nafta, also known as Nefta (wd:Q1026298): Tunisian town
3. nafta (wd:Q1213853): chemical compound
4. Nafta (wd:Q11788993): 1961 film by Stanisław Lenartowicz
5. Nafta (wd:Q6958220): Soviet Union oil company operating abroad
6. Nafta, also known as IMO 8853946 (wd:Q52335786): bunkering tanker built in 1978
7. NAFTA, also known as NAFTA a.s. (wd:Q12772242): Slovak multinational company operating in the field of storage and extraction of hydrocarbons
8. Naftalan (wd:Q152825): city in Azerbaijan
9. Naphtali, also known as Naftali (wd:Q1771963): biblical figure and the sixth son of Jacob through his concubine Bilhah
10. United States–Mexico–Canada Agreement, also known as Canada–United States–Mexico Agreement, CUSMA, NAFTA 2.0, NAFTA Redux, New NAFTA (wd:Q56839716): North American trade bloc

[Assistant] The entity for the North American Free Trade Agreement (NAFTA) is wd:Q181574. Now I will look for the countries involved in this trade bloc. Typically, the property for member countries or participants in an agreement could be "has part" (P527) or "participant" (P710) or "member" (P463). I will search for properties related to countries or members for this entity.

[Tool]
Top 10 property alternatives:
1. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as p/wdt): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
2. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as p/wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
3. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
4. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as p/wdt): language designated as official by this item, language used
5. 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)
6. locator map image, also known as locator map, map image, map (wd:P242 as p/wdt): geographic map image which highlights the location of the subject within some larger entity, image
7. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
8. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as p/wdt): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
9. short name, also known as short title, shortname, abbreviation, shortened name, initialism (wd:P1813 as p/wdt): short name of a place, organisation, person, journal, wikidata property, etc. Used by some Wikipedia templates., name
10. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as p/wdt): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon

No other items found

[Assistant] The search for properties related to countries or members for the NAFTA entity did not return a direct property indicating member countries. I will try to find the countries that have NAFTA as a trade agreement or are part of this trade bloc by querying countries that have a property linking them to NAFTA (wd:Q181574). A possible property to check is "member of" (P463) or "part of" (P361). I will try to find countries that have NAFTA as a member of or part of.

[Tool]
Got 3 rows and 2 columns:
| country                | countryLabel       |
| ---------------------- | ------------------ |
| Canada (wd:Q16)        | Canada (en)        |
| United States (wd:Q30) | United States (en) |
| Mexico (wd:Q96)        | Mexico (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 ?placeOfBirth ?placeOfBirthLabel WHERE {
  wd:Q1744 wdt:P19 ?placeOfBirth .
  OPTIONAL {
    ?placeOfBirth rdfs:label ?placeOfBirthLabel FILTER ( LANG( ?placeOfBirthLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| placeOfBirth          | placeOfBirthLabel |
| --------------------- | ----------------- |
| Bay City (wd:Q746820) | Bay City (en)     |

Madonna's place of birth is the closest available information to where she grew up. The query will return the place where Madonna was born.

[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 madonna grew up?

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

[Tool]
Example 1:
Question:
what party was winston churchill in politics?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q8016 wdt:P102 ?x .
}

Using entities:
Winston Churchill, also known as The Right Honourable Sir Winston Leonard Spencer Churchill, The Right Honourable Sir Winston Churchill, The Honourable Sir Winston Spencer Churchill, Sir Winston Spencer Churchill, The Right Honourable Sir Winston Spencer Churchill (wd:Q8016): British statesman, soldier and writer (1874–1965), politician, historian

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

Example 2:
Question:
who did rufus wainwright married?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q192402 wdt:P26 ?x .
}

Using entities:
Rufus Wainwright, also known as Rufus McGarrigle Wainwright (wd:Q192402): American-Canadian singer-songwriter and composer, singer-songwriter, television actor, voice actor, film actor, musician, composer, pianist, singer

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

Example 3:
Question:
who will play clary in city of bones?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q59346 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q65510149 .
}

Using entities:
The Mortal Instruments: City of Bones, also known as Mortal Instruments: City of Bones (wd:Q59346): 2013 film directed by Harald Zwart
Clary Fray, also known as Clarissa Adele Fairchild, Clary Morgenstern, Clary Fairchild, Clarissa Morgenstern, Clarissa Fairchild (wd:Q65510149): fictional character of the Shadowhunters series, demon hunter

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

[Assistant]
The question is "Where did Madonna grow up?" We need to find the entity for Madonna and then find a property that indicates where she grew up.

Step 1: Search for the entity "Madonna" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Madonna, also known as Madonna Ciccone, Madonna Louise Veronica Ciccone, Madonna Louise Ciccone, Madonna L. Ciccone (wd:Q1744): American singer, songwriter, and actress (born 1958), songwriter, singer, actor
2. Mary, also known as Mother of God, Mother of Jesus, Notre Dame, Our Lady, Queen of the Universe (wd:Q345): mother of Jesus
3. Madonna, also known as Madonna: The First Album (wd:Q177943): 1983 self-titled debut studio album by Madonna
4. Madonna (wd:Q1989780): painting composition by Edvard Munch, in different versions
5. Madonna, also known as Madonna in art, The Madonna in art, Virgin Mary in art (wd:Q926743): artistic representation of Mary, either alone or with her child Jesus
6. Madonna (wd:Q19794647): 2015 South Korean film directed by Shin Su-won
7. Madonna (wd:Q1147459): album by …And You Will Know Us by the Trail of Dead
8. Madonna (wd:Q486604): 2010 EP by Secret
9. Madonna, also known as Madonna, MD, Madonna, Maryland (wd:Q6728358): unincorporated community in Harford County, Maryland
10. Virgin and Child with an Angel (Madonna del Latte), also known as Madonna, Madonna with child and John the Baptist (wd:Q3842618): painting by Antonio da Correggio from 1520

[Assistant] The entity for Madonna the American singer-songwriter and actress is wd:Q1744. Now, let's find the property that indicates where she grew up. We can try searching for properties related to "grew up" or "childhood location" for this entity.

[Tool]
Top 10 property alternatives:
1. 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
2. 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
3. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as p/wdt): full name of a person at birth, if different from their current, generally used name, name
4. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
5. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
6. studied in, also known as is studied by, studied by, science, that studies, researched in, researched by (wd:P2579 as p/wdt): subject is studied by this science or domain, field of work
7. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as p/wdt): notable scientific, artistic or literary work, or other work of significance among subject's works
8. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as p/wdt): significant or notable events associated with the subject
9. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as p/wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
10. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as p/wdt): female parent of the subject. For stepmother, use "stepparent" (P3448), parent

No other items found

[Assistant]
The property "place of birth" (wdt:P19) is available, but it indicates where Madonna was born, not necessarily where she grew up. There is no direct property for "grew up" or "childhood location" found for Madonna.

Let's check if there is a property related to "residence" or "hometown" that might indicate where she grew up. I will search for properties related to "residence" for Madonna.

[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. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
3. owner of, also known as owns, owns property, shareholder of (wd:P1830 as p/wdt): entities owned by the subject
4. 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
5. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as p/wdt): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
6. net worth, also known as declared patrimony, estimated net worth, net wealth, net worth estimate, personal assets (wd:P2218 as p/wdt): totality of wealth possessed by a person
7. 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)
8. 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
9. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
10. Guardian topic ID, also known as Guardian, The Guardian topic, The Guardian topic ID (wd:P3106 as p/wdt): identifier for a topic at the Guardian newspaper website

No other items found

[Assistant]
There is no direct property for "residence" or "hometown" found for Madonna. The closest relevant property is "place of birth" (wdt:P19).

Since "grew up" is not directly available, we can provide the place of birth as the closest information related to where Madonna grew up.

I will now write a SPARQL query to get Madonna's place of birth.

[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 ?formOfGovernment ?formOfGovernmentLabel WHERE {
  wd:Q928 wdt:P122 ?formOfGovernment .
  OPTIONAL {
    ?formOfGovernment rdfs:label ?formOfGovernmentLabel FILTER ( LANG( ?formOfGovernmentLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| formOfGovernment    | formOfGovernmentLabel |
| ------------------- | --------------------- |
| republic (wd:Q7270) | republic (en)         |

The form of government of the Philippines is 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 form of government do we have in the philippines?

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

[Tool]
Example 1:
Question:
which country is north of the usa?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q30 p:P47 ?p .
  ?p ps:P47 ?x ; pq:P560 wd:Q659 .
}

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
north, also known as N, northbound, northerly, septentrion (wd:Q659): one of the four cardinal directions

Using properties:
shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as p/ps): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.
direction (wd:P560 as pq): relative direction of an entity

Example 2:
Question:
who played carlton banks?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q9697446 .
}

Using entities:
Carlton Banks (wd:Q9697446): character from "The Fresh Prince of Bel-Air"

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 do the san francisco giants play baseball?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q308966 wdt:P115 ?x .
}

Using entities:
San Francisco Giants, also known as Giants, Gothams, New York Giants, New York Gothams, SFG (wd:Q308966): baseball team and Major League Baseball franchise in San Francisco, California, United States

Using properties:
home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt): home stadium or venue of a sports team or applicable performing arts organization, location

[Assistant]
The question is about the form of government of the Philippines. The key entity here is "Philippines" and the key property is the "form of government."

Step 1: Search for the entity "Philippines" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Philippines, also known as ph, The Philippines, RP, Republic of the Philippines, Philippine Islands (wd:Q928): archipelagic country in Southeast Asia
2. Philippines (wd:Q70886687): scientific article published on 01 January 1966
3. Philippines (wd:Q116754458): scientific article published on 15 November 2001
4. Philippines (wd:Q47409215): scientific article published in August 1986
5. Philippines (wd:Q57715247): entry in Encyclopedia of Global Warming & Climate Change
6. Philippines. (wd:Q39611725): scientific article published on September 1983
7. Philippines (wd:L1259985-S1)
8. Philippines (wd:L476739-F2)
9. Philippines (wd:L254248-F1)
10. Philippines (wd:L254248)

[Assistant] The entity for the country Philippines is wd:Q928. Now, I will search for properties related to "form of government" for this entity.

[Tool]
Top 10 property alternatives:
1. basic form of government, also known as form of government, government, type of government (wd:P122 as p/wdt): subject's government
2. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity
3. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as p/wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
4. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as p/wdt): political office that is fulfilled by the head of the government of this item
5. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as p/wdt): political office that is fulfilled by the head of state of this item
6. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
7. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as p/wdt): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
8. diplomatic relation, also known as political relation, political relations, foreign relations, foreign relation, diplomatic relations (wd:P530 as p/wdt): diplomatic relations of the country
9. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as p/wdt): official with the highest formal authority in a country/state, director / manager, chairperson
10. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as p/wdt): (list of) direct subdivisions of an administrative territorial entity, has part(s)

No other items found

[Assistant] The property "basic form of government" (wdt:P122) corresponds to the form of government of a country. Now, I will write a SPARQL query to get the form of government of the Philippines (wd:Q928) using this property.

[Tool]
Got 1 row and 2 columns:
| formOfGovernment    | formOfGovernmentLabel |
| ------------------- | --------------------- |
| republic (wd:Q7270) | republic (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 ?movie ?movieLabel WHERE {
  ?movie wdt:P57 wd:Q103646 .
  ?movie wdt:P31 wd:Q11424 .
  OPTIONAL {
    ?movie rdfs:label ?movieLabel FILTER ( LANG( ?movieLabel ) = "en" )
  }
}

Got 36 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                              | movieLabel               |
| ---------------------------------- | ------------------------ |
| Thirteen Lives (wd:Q105962844)     | Thirteen Lives (en)      |
| Apollo 13 (wd:Q106428)             | Apollo 13 (en)           |
| Cocoon (wd:Q1105463)               | Cocoon (en)              |
| Splash (wd:Q1127184)               | Splash (en)              |
| Parenthood (wd:Q1137831)           | Parenthood (en)          |
| ...                                | ...                      |
| Frost/Nixon (wd:Q691672)           | Frost/Nixon (en)         |
| Ransom (wd:Q752362)                | Ransom (en)              |
| Far and Away (wd:Q839341)          | Far and Away (en)        |
| Rebuilding Paradise (wd:Q96314873) | Rebuilding Paradise (en) |
| Night Shift (wd:Q997228)           | Night Shift (en)         |

Ron Howard directed the following movies: Thirteen Lives, Apollo 13, Cocoon, Splash, Parenthood, Frost/Nixon, Ransom, Far and Away, Rebuilding Paradise, Night Shift, and others (total 36 movies found).

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

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

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

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

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

[User] what movies did ron howard director?

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

[Tool]
Example 1:
Question:
what are taylor swift's albums?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 wd:Q482994 ; wdt:P175 wd:Q26876 .
}

Using entities:
Taylor Swift, also known as Taylor Alison Swift (wd:Q26876): American singer-songwriter (born 1989), music video director, singer-songwriter, record producer, philanthropist, film director, lyricist, composer, singer, actor
album, also known as full album, record album, music album, full-length album, audio album (wd:Q482994): grouping of album releases by an artist usually released at the ...racks but in different formats for consumption (digital, CD, LP)

Using properties:
performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
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:
what states does the missouri river touch?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5419 wdt:P131 + ?x .
  ?x wdt:P31 / wdt:P279 * 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
Missouri River, also known as Missouri, The Missouri (wd:Q5419): major river in central United States

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

Example 3:
Question:
where was st elizabeth ann seton born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q459032 wdt:P19 ?x .
}

Using entities:
Elizabeth Ann Seton, also known as Elizabeth Seton, St. Elizabeth Ann Seton, Elizabeth Ann Bayley Seton, Elizabeth Ann Bayley (wd:Q459032): first native-born American saint of the Roman Catholic Church (1774-1821), memoirist, teacher, abbess, nurse, nun

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

[Assistant]
From the examples, I see that to find movies directed by a person, we need to find the entity for Ron Howard and then find movies where he is the director. The property for director is usually "director" (wdt:P57) in Wikidata.

Step 1: Find the entity for Ron Howard.
Step 2: Query movies where Ron Howard is the director using the property wdt:P57.

I will start by searching for the entity Ron Howard.

[Tool]
Top 10 entity alternatives:
1. Ron Howard, also known as Ronald William Howard (wd:Q103646): American film director, producer, and actor, television producer, television director, television actor, film producer, film director, screenwriter, voice actor, film actor, director, actor
2. Ron Howard (wd:Q4883): American basketball player, basketball player
3. Ron Howard, also known as Ronald Ford Howard (wd:Q3940969): American football player (born 1951), American football player, basketball player
4. Ron Howard, also known as Ronald John Howard (wd:Q19874445): Australian rules footballer (1940-2023), Australian rules football player
5. Ron Howard, also known as Ron Dean Howard (wd:Q107646515): politician
6. Ron Howard (wd:Q112407850)
7. Ron Howard (wd:Q100982902): college basketball player (1986–1986) U.S. International, basketball player
8. Ronald Howard (wd:Q2165643): British actor (1918–1996), television actor, stage actor, actor
9. Ronald A. Howard, also known as Ronald Arthur Howard, Ronald Howard (wd:Q7364615): management engineer, university teacher, American professor, academic
10. Ronald Howard, also known as Vice-Admiral Ronald Howard (wd:Q75253869): (1878-1959)

[Assistant] The entity for Ron Howard the film director is wd:Q103646. Now I will write a query to find movies directed by Ron Howard using the property "director" (wdt:P57). I will also include the movie labels for better readability.

[Tool]
Got 36 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                              | movieLabel               |
| ---------------------------------- | ------------------------ |
| Thirteen Lives (wd:Q105962844)     | Thirteen Lives (en)      |
| Apollo 13 (wd:Q106428)             | Apollo 13 (en)           |
| Cocoon (wd:Q1105463)               | Cocoon (en)              |
| Splash (wd:Q1127184)               | Splash (en)              |
| Parenthood (wd:Q1137831)           | Parenthood (en)          |
| ...                                | ...                      |
| Frost/Nixon (wd:Q691672)           | Frost/Nixon (en)         |
| Ransom (wd:Q752362)                | Ransom (en)              |
| Far and Away (wd:Q839341)          | Far and Away (en)        |
| Rebuilding Paradise (wd:Q96314873) | Rebuilding Paradise (en) |
| Night Shift (wd:Q997228)           | Night Shift (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 ?school ?schoolLabel WHERE {
  wd:Q19526 wdt:P69 ?school .
  OPTIONAL {
    ?school rdfs:label ?schoolLabel FILTER ( LANG( ?schoolLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| school                                      | schoolLabel                        |
| ------------------------------------------- | ---------------------------------- |
| California Labor School (wd:Q16850567)      | California Labor School (en)       |
| George Washington High School (wd:Q5545977) | George Washington High School (en) |

Maya Angelou attended George Washington High School and California Labor School.

[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 high school did maya angelou go to?

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

[Tool]
Example 1:
Question:
where did pharaoh hatshepsut live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q129234 wdt:P19 ?x .
}

Using entities:
Hatshepsut, also known as Hatasou, Hatasu, Hatsehpsut, Hatchepsut (wd:Q129234): 5th Pharaoh of the Eighteenth Dynasty of Egypt (c. 1479 BC - 1458 BC), statesperson

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

Example 2:
Question:
what religions are recognized in canada?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q16 wdt:P140 ?x .
}

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

Using properties:
religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as wdt): religion of a person, organization or religious building, or associated with this subject

Example 3:
Question:
who runs china 2011?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q849418 ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2012-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z > "2011-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
General Secretary of the Chinese Communist Party, also known as CCP General Secretary, General Secretary of the Communist Party of China, General Secretary of the Central...e of the Chinese Communist Party, General Secretary, General Secretary of the CCP (wd:Q849418): head of the Chinese Communist Party (CCP) and de facto leader of China

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]
The question is about the high school Maya Angelou attended. We need to find the entity for Maya Angelou and the property related to the high school or education institution she attended.

Step 1: Search for the entity "Maya Angelou" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Maya Angelou, also known as Marguerite Annie Johnson, Marguerite Ann Johnson, Marguerite Johnson, Marguerite Anne Johnson (wd:Q19526): American poet, author, and civil rights activist (1928–2014), human rights activist, television producer, television actor, autobiographer, film producer, film director, screenwriter, stage actor, playwright, journalist, politician, songwriter, professor, essayist, novelist, dancer, singer, writer
2. Maya Angelou, also known as Marguerite Ann Johnson, Marguerite Annie Johnson, Marguerite Johnson, Marguerite Anne Johnson (wd:Q19526): American poet, author, and civil rights activist (1928–2014), human rights activist, television producer, television actor, autobiographer, film director, film producer, screenwriter, stage actor, journalist, playwright, songwriter, politician, professor, essayist, novelist, writer, singer, dancer
3. Maya Angelou (wd:Q108467711): magazine article from 'American Funeral Director' published in 2014
4. Maya Angelou (wd:Q47513615): painting by Ross R. Rossin
5. Maya Angelou Academy (wd:Q14692192): American alternative school
6. Maya Angelou Birthplace, also known as Birthplace of Maya Angelou (wd:Q132261323): The house in St. Louis, Missouri where Maya Angelou was born
7. Maya Angelou, 1928-2014 (wd:Q116228315): journal article
8. Maya Angelou Library (wd:Q66364225): public library in Stockton, California, USA
9. Maya Angelou Northeast (wd:Q69781127): public library in Wichita, Kansas, USA
10. rue Maya Angelou (wd:Q125778051)

[Assistant] The entity for Maya Angelou is wd:Q19526. Now, we need to find the property that relates to the high school or educational institution she attended. Let's search for properties related to education or high school for the entity Maya Angelou.

[Tool]
Top 10 property alternatives:
1. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
2. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as p/wdt): specialization of a person or organization; see P106 for the occupation, interested in
3. 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
4. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
5. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as p/wdt): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
6. 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
7. 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
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
9. 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)
10. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)

No other items found

[Assistant] The property "educated at" (wdt:P69) is the relevant property for the high school or educational institution attended by Maya Angelou. Now, let's query the educational institutions Maya Angelou attended using this property.

[Tool]
Got 2 rows and 2 columns:
| school                                      | schoolLabel                        |
| ------------------------------------------- | ---------------------------------- |
| California Labor School (wd:Q16850567)      | California Labor School (en)       |
| George Washington High School (wd:Q5545977) | George Washington High School (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 ?college ?collegeLabel WHERE {
  wd:Q116960730 wdt:P69 ?college .
  OPTIONAL {
    ?college rdfs:label ?collegeLabel FILTER ( LANG( ?collegeLabel ) = "en" )
  }
}

None of the Otto Frank entities I checked have information about where they went to college in Wikidata. It is possible that the specific Otto Frank you are referring to is not well documented in Wikidata with this information. Could you please specify if you mean Otto Frank, the father of Anne Frank, or another Otto Frank? This will help me narrow down the search.

[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 otto frank go to college?

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

[Tool]
Example 1:
Question:
who is the current leader of china today?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P6 ?x .
}

Using entities:
People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia

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

Example 2:
Question:
where did david duke go to college?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q163042 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q38723 .
}

Using entities:
David Duke, also known as Dorothy Vanderbilt, James Konrad, David Ernest Duke (wd:Q163042): American white nationalist and politician, politician, journalist, historian, writer
higher education institution, also known as HEI, Higher Education school, institution of higher education, Superior Institute (wd:Q38723): institution that provides higher education (e.g., universities, ...es, liberal arts colleges, institutes of technology, and others)

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

Example 3:
Question:
what language do denmark?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q35 wdt:P37 ?x .
}

Using entities:
Denmark, also known as 🇩🇰, Danmark, DEK, TAN, DEN (wd:Q35): country in Northern Europe

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

[Assistant] From the examples, I see that the property "educated at" (wdt:P69) is used to find the educational institutions a person attended. I will now search for the entity "Otto Frank" in Wikidata to find his identifier.

[Tool]
Top 10 entity alternatives:
1. Frank Otto (wd:Q1443909): German water polo player, water polo player
2. Otto Frank, also known as Otto Friedrich Frank, Friedrich Wilhelm Ferdinand Otto Frank (wd:Q89925): German physiologist (1865–1944), university teacher, cardiologist, physiologist, physician
3. Frank Otto (wd:Q1443902): German media entrepreneur, film director, geologist, director
4. Frank Otto (wd:Q16104521): American linguist (1936-2017), linguist
5. Frank Otto (wd:Q1443905): German historian of modern age, historian of Modern Age, writer
6. Otto Frank (wd:Q36977791): German FDP politician (1900-1963), politician
7. Otto Frank (wd:Q94791903): military officer, cartographer
8. Frank Otto (wd:Q96110480): researcher
9. Otto Frank (wd:Q94941069): engineer
10. Otto Frank (wd:Q116960730): Austrian architect, architect

[Assistant] There are multiple entities named Otto Frank. The most well-known Otto Frank related to education is Otto Frank (wd:Q89925), a German physiologist and university teacher. I will now check the property "educated at" (wdt:P69) for this entity to find where he went to college.

[Tool] Got no rows and 2 columns

[Assistant] The entity Otto Frank (wd:Q89925) does not have any "educated at" (wdt:P69) property values in Wikidata. I will check the other Otto Frank entities to see if any of them have the "educated at" property. I will check Otto Frank (wd:Q36977791) next.

[Tool] Got no rows and 2 columns

[Assistant] The entity Otto Frank (wd:Q36977791) also does not have any "educated at" (wdt:P69) property values in Wikidata. I will check the next Otto Frank entity with a known profession, Otto Frank (wd:Q94791903), who is a military officer and cartographer.

[Tool] Got no rows and 2 columns

[Assistant] The entity Otto Frank (wd:Q94791903) also does not have any "educated at" (wdt:P69) property values in Wikidata. I will check the next Otto Frank entity with a known profession, Otto Frank (wd:Q94941069), who is an engineer.

[Tool] Got no rows and 2 columns

[Assistant] The entity Otto Frank (wd:Q94941069) also does not have any "educated at" (wdt:P69) property values in Wikidata. I will check the last Otto Frank entity with a known profession, Otto Frank (wd:Q116960730), who is an Austrian architect.

[Tool] Got no rows and 2 columns

[Assistant] None of the Otto Frank entities I checked have information about where they went to college in Wikidata. It is possible that the specific Otto Frank you are referring to is not well documented in Wikidata with this information. Could you please specify if you mean Otto Frank, the father of Anne Frank, or another Otto Frank? This will help me narrow down the search.