PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?character WHERE {
  ?character wdt:P451 wd:Q4205826 .
  ?character wdt:P451 wd:Q4463198 .
}

Geralt of Rivia (wd:Q2492923)

[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] among the characters in the witcher, who has two unmarried partners, Yennefer of Vengerberg and Triss Merigold?

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

[Tool]
Example 1:
Question:
Who is the novelist of the work a song of ice and fire?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q45875 ?p ?uri .
  ?uri wdt:P106 wd:Q6625963 .
}

Using entities:
A Song of Ice and Fire, also known as A Song of Ice and Fire Series, Game of Thrones, Song of Ice and Fire, ASOIAF (wd:Q45875): series of epic fantasy novels by George R. R. Martin
novelist, also known as novel author, novel writer (wd:Q6625963): writer of novels

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:
Which monarchs were married to a German?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q116 ; wdt:P26 ?spouse .
  ?spouse wdt:P27 wd:Q183 .
}

Using entities:
monarch, also known as emperor, empress regnant, king, queen regnant (wd:Q116): person at the head of a monarchy
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe

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)
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
country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt): the object is a country that recognizes the subject as its citizen, country

[Assistant] From the examples, we can see that we need to find a character in the Witcher universe who has two specific unmarried partners. We will need to identify the characters Yennefer of Vengerberg and Triss Merigold, and then find a character who has both of them as unmarried partners. Let's start by searching for the entities representing these characters.

[Tool]
Top 10 entity alternatives:
1. Yennefer of Vengerberg, also known as Yenna, Yen (wd:Q4205826): fictional sorceress from the Witcher series, conspirator, magician, adviser
2. Vengerberg (wd:Q9368391)
3. Pseudotanais yenneferae (wd:Q107100133): species of crustacean

[Assistant] The correct entity for Yennefer of Vengerberg is `wd:Q4205826`. Now let's search for Triss Merigold.

[Tool]
Top 10 entity alternatives:
1. Triss Merigold, also known as Fourteenth of the Hill, Merigold the Fearless (wd:Q4463198): fictional sorceress from the Witcher series, magician, adviser, healer
2. Merigold, also known as Merigold (Mississippi), Merigold, Mississippi, Merigold, MS (wd:Q867528): town in Bolivar County, Mississippi, United States
3. Triss (wd:Q3204428): 2002 novel by Brian Jacques
4. Triss (wd:Q15113667): character in the Shannara, military personnel
5. Merigold (wd:Q37520933): family name
6. Trissino (wd:Q47238): Italian comune
7. Trissolcus (wd:Q14495753): genus of insects
8. Trissernis (wd:Q7844073): genus of insects
9. Trissodoris (wd:Q5226655): genus of insects
10. Trisselwand (wd:Q2454152): mountain in the Totes Gebirge in Styria

[Assistant] The correct entity for Triss Merigold is `wd:Q4463198`. Next, we need to find the property that represents an unmarried partner. Let's search for this property.

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
2. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): full name of a person at birth, if different from their current, generally used name, name
3. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
4. connects with, also known as contacts, couples with, intersects at grade, links to, mates with (wd:P2789 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): item with which the item is physically connected, physically interacts with
5. married name, also known as full name (married) (wd:P2562 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): name or surname adopted by a person upon marriage, name
6. marriageable age, also known as marriage age, minimum age for marriage (wd:P3000 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): minimum age at which a person is generally allowed by law to mar...males (Q6581097), females (Q6581072) or both genders (Q27177113), minimum age
7. partner in business or sport, also known as professional partner, sport partner, sports partner, team mate, team-mate (wd:P1327 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): professional collaborator, significant person
8. kinship to subject, also known as type of relationship, type of kinship, relation to, relationship (kinship), nature of kinship (wd:P1039 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): qualifier of "relative" (P1038) to indicate less usual family re...; indicate how the qualificator item is related to the main item, object of statement has role
9. place of marriage, also known as marriage location, wedding location, wed at, married in, married at (wd:P2842 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location where the marriage was celebrated. Use as qualifier for property "spouse" (P26), significant place
10. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

[Assistant]
The correct property for an unmarried partner is `wd:P451`. Now we can construct a SPARQL query to find the character who has both Yennefer of Vengerberg and Triss Merigold as unmarried partners.

Let's write and execute the SPARQL query.

[Tool]
Got 1 row and 1 column:
| character                     |
| ----------------------------- |
| Geralt of Rivia (wd:Q2492923) |

[Assistant]
The character in the Witcher universe who has both Yennefer of Vengerberg and Triss Merigold as unmarried partners is Geralt of Rivia.

Here is the final SPARQL query and answer:

```sparql
SELECT DISTINCT ?character WHERE {
  ?character wdt:P451 wd:Q4205826 .
  ?character wdt:P451 wd:Q4463198 .
}
```

Answer: Geralt of Rivia (wd:Q2492923)

[Tool] Stopped generation process


Failed to generate SPARQL query

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

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

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

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

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

[User] How many different female mayors did Hamburg have?

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

[Tool]
Example 1:
Question:
Give me all female German chancellors.

SPARQL:
SELECT ?uri WHERE {
  ?uri wdt:P21 wd:Q6581072 .
  ?uri wdt:P39 wd:Q4970706 .
}

Using entities:
Federal Chancellor of Germany, also known as German Federal Chancellor, prime minister of Germany, German Chancellor, Federal Chancellor of the Federal Republic of Germany, Federal Chancellor (wd:Q4970706): head of government of the Federal Republic of Germany (1949–present)
female, also known as female human, women, woman, lady, human female (wd:Q6581072): to be used in "sex or gender" (P21) to indicate that the human s...nder" (P10339) to indicate that a word refers to a female person

Using properties:
sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
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 2:
Question:
Who is the mayor of Berlin?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q64 wdt:P6 ?o1 .
}

Using entities:
Berlin, also known as Berlin (Germany), Berlin, Germany, DE-BE (wd:Q64): federated state, capital and largest city of Germany

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

Example 3:
Question:
Who is the mayor of Rotterdam?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q34370 wdt:P6 ?uri .
}

Using entities:
Rotterdam, also known as R'dam, Roffa, Rotjeknor (wd:Q34370): city in South Holland, the Netherlands

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

[Assistant] Based on the examples, we need to identify the entity for Hamburg and the properties for being a mayor and being female. Let's start by searching for the entity representing Hamburg.

[Tool]
Top 10 entity alternatives:
1. Hamburg, also known as Free and Hanseatic City of Hamburg, Hamburg, Germany, Hamburg, Freie und Hansestadt (wd:Q1055): city and state in the North of Germany
2. Hamburger SV, also known as Hamburg SV, HSV, H.S.V., Hamburg Sport Club, HamburgerSV (wd:Q51974): German sports club based in Hamburg, with its largest branch being its football department
3. Hamburg, also known as Hamburg, IA, Hamburg, Iowa (wd:Q998718): city in Fremont County, Iowa, United States
4. Hamburg, also known as Hamburg, AR, Hamburg, Arkansas (wd:Q79657): city in Ashley County, Arkansas, United States
5. Hamburg, also known as Hamburg, Minnesota, Hamburg, MN (wd:Q1005682): city in Carver County, Minnesota, United States
6. Hamburg, also known as Hamburg, New Jersey, Hamburg, NJ (wd:Q1082931): borough in Sussex County, New Jersey, United States
7. Hamburg, also known as Hamburg, New York, Hamburg, NY (wd:Q742785): town in Erie County, New York, United States
8. Hamburg, also known as Hamburg, IL (wd:Q2672139): village in Calhoun County, Illinois, United States
9. Hamburg, also known as Hamburg, PA, Hamburg, Pennsylvania (wd:Q1181264): borough in Berks County, Pennsylvania, United States
10. Hamburg, also known as Hamburgh (wd:Q939795): breed of chicken developed in Germany and Holland prior to 1700

[Assistant] The correct entity for Hamburg, Germany is `wd:Q1055`. Next, let's find the property for "mayor" and confirm it is `wdt:P6`.

[Tool]
Top 10 property alternatives:
1. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
2. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): official with the highest formal authority in a country/state, director / manager, chairperson
3. rector, also known as chancellor, university president, Rector (academia), president (wd:P1075 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): senior official in an educational institution., director / manager, chairperson
4. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): presiding member of an organization, group or body, director / manager, significant person
5. successful candidate, also known as election winner, winning candidate, winner of election, election won by, elected (wd:P991 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): person(s) or political organization(s) elected after the election, candidate, winner
6. position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): persons who hold and/or held the position
7. position held, also known as function, held position, holds position, job, office held (wd:P39 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): subject currently or formerly holds the object position or public office
8. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
9. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): the object is a country that recognizes the subject as its citizen, country
10. elected in, also known as re-elected in, election (wd:P2715 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): election in which a person gained a position (as qualifier), or a position or legislative term is/was elected (as main value)

[Assistant] The property for "mayor" is indeed `wdt:P6`. Now, let's find the property for "female".

[Tool]
Top 10 property alternatives:
1. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
2. grammatical gender, also known as gender (wd:P5185 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): grammatical gender of the word
3. female population (wd:P1539 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): number of female people inhabiting the place; number of female people of subject, population
4. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): female form of name or title (for male use P3321)
5. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
6. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
7. cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
8. given name version for other gender, also known as personal name version for other gender, other genders given name, male version of this female given name, gender inflection of given name, female version of this male given name (wd:P1560 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): equivalent name (with respect to the meaning of the name) in the...n of a female first name. Add primarily the closest matching one
9. has grammatical gender, also known as grammatical genders, has genders (wd:P5109 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): specific form of noun class system of a language. Use qualifier ... subject of" (P805) to link to language specific item if present
10. number of points/goals/set scored, also known as goals scored, score for, points scored, number of points, number of goals (wd:P1351 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): goals / points scored in a match or an event used as qualifier to the participant. Use P1358 for league points.

[Assistant]
The property for "female" is `wdt:P21` with the value `wd:Q6581072` (female). Now, we can construct a SPARQL query to find all the female mayors of Hamburg.

Let's start with a basic query to see if we can find any female mayors of Hamburg.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?dateOfBirth WHERE {
  wd:Q43347 wdt:P569 ?dateOfBirth .
}

Rumi was born on September 30, 1207.

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

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

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

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

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

[User] When was Rumi born?

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

[Tool]
Example 1:
Question:
Where was Bach born?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1339 wdt:P19 ?uri .
}

Using entities:
Johann Sebastian Bach, also known as J.S. Bach, J. S. Bach, J S Bach, Bach (wd:Q1339): German composer (1685–1750), music educator, choir director, school teacher, harpsichordist, concertmaster, musicologist, conductor, violinist, virtuoso, composer, organist

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:
Where is the birthplace of Goethe?

SPARQL:
SELECT ?res WHERE {
  wd:Q5879 wdt:P19 ?res .
}

Using entities:
Johann Wolfgang von Goethe, also known as Johann Wolfgang Von Goethe, Goethe (wd:Q5879): German writer, artist, natural scientist and politician (1749–1832), theatre manager, autobiographer, art historian, travel writer, visual artist, statesperson, mineralogist, art theorist, music critic, philosopher, playwright, theologian, art critic, politician, librettist, librarian, physicist, zoologist, diplomat, aphorist, polymath, botanist, composer, novelist, literary, diarist, painter, writer, jurist, lawyer, poet

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, we can see that the property `wdt:P19` is used to denote the place of birth. However, since we are interested in the date of birth, we need to find the appropriate property for the date of birth. Let's search for the entity "Rumi" first.

[Tool]
Top 10 entity alternatives:
1. Rumi, also known as Mawlana, Mawlana Rumi, Mawlawi, Jallal ed-Din Muhammad Balkhy, Jelaluddin Rumi (wd:Q43347): Sufi and Persian poet, philosopher, literary, writer, mystic, ʿālim, poet
2. Rum, also known as Arwām, Rūm, Rūmī (wd:Q3943294): autonym
3. Rūmī (wd:Q25908371): crater on planet Mercury
4. POGLUT1, also known as MDSRP, Rumi, protein O-glucosyltransferase 1, MDS010, LGMDR21 (wd:Q18042749): protein-coding gene in the species Homo sapiens
5. Lanmewko, also known as Rumi (wd:Q109342876): Taiwanese Virtual YouTuber, Twitch streamer, VTuber
6. Rumi Rumiyuq (wd:Q25104391): mountain in Bolivia
7. Rumi, also known as るみ (wd:Q97655647): Japanese female given name (るみ)
8. Rumi (wd:Q11241326): Japanese master of ceremonies, rapper
9. Rumi (wd:Q11578550): Japanese actress, actor
10. Rumi (wd:Q19949377)

[Assistant] The top result for "Rumi" is `wd:Q43347`, which refers to the Sufi and Persian poet, philosopher, and mystic. Now, let's search for the property related to the date of birth.

[Tool]
Top 10 property alternatives:
1. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): date on which the subject was born, inception
2. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): most specific known birth location of a person, animal or fictional character, location
3. birthday, also known as b-day, bday, birth day (wd:P3150 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
4. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): the object is a country that recognizes the subject as its citizen, country
5. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): what the place, monument, memorial, or holiday, commemorates, main subject
6. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): full name of a person at birth, if different from their current, generally used name, name
7. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): dissolved, abolished or demolished date, date on which the subject died, end time
8. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): time when an entity begins to exist; for date of official opening use P1619, start time
9. website username or ID, also known as user name, website username, website ID, username in social media, username (wd:P554 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): username or identifier on a website that the person or movement ... account on, for use as qualifier of "website account on" (P553)
10. pseudonym, also known as nom de plume, nom-de-plume, nome de guerre, pen name, ring name (wd:P742 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): alias used by someone (for nickname use P1449), name

[Assistant]
The property `wdt:P569` is the correct one for the date of birth. Now, let's construct a SPARQL query to find out when Rumi was born.

Here is the SPARQL query:

```sparql
SELECT ?dateOfBirth WHERE {
  wd:Q43347 wdt:P569 ?dateOfBirth .
}
```

I will now execute this query.

[Tool]
Got 1 row and 1 column:
| dateOfBirth                         |
| ----------------------------------- |
| 1207-09-30T00:00:00Z (xsd:dateTime) |

[Assistant]
The SPARQL query has returned the date of birth for Rumi. According to the result, Rumi was born on September 30, 1207.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?dateOfBirth WHERE {
  wd:Q43347 wdt:P569 ?dateOfBirth .
}
```

Answer: Rumi was born on September 30, 1207.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?deaths ?injured WHERE {
  wd:Q815436 wdt:P1120 ?deaths .
  OPTIONAL {
    wd:Q815436 wdt:P1339 ?injured .
  }
}

The Troubles resulted in 3,532 deaths and 47,541 injuries.

[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] How many casualties were a result of the Troubles?

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

[Tool] No examples found

[Assistant] Since we couldn't find any similar examples, let's start by searching for the entity "Troubles" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. The Troubles, also known as Troubles, Northern Irish Troubles, Northern Ireland Troubles, Northern Ireland conflict, Conflict in Northern Ireland (wd:Q815436): 1960s–1990s conflict in Northern Ireland
2. Troubles (wd:Q4000425): novel by James Gordon Farrell
3. Troubles (wd:Q7846501): album by Steve Lacy
4. Troubles (wd:Q7846503): UK musical group
5. Troubles (wd:Q109812273): Movie directed by Érik Papatie
6. Troubles (wd:Q129262318): 2022 track by Denzel Curry
7. Troubles (wd:Q131565207): hardback edition (en)
8. Troubles (wd:Q42196874)
9. Troubles (wd:Q7846502): album by Troubles
10. troubles (wd:L1330100-S1)

[Assistant] The first result, "The Troubles, also known as Troubles, Northern Irish Troubles, Northern Ireland Troubles, Northern Ireland conflict, Conflict in Northern Ireland (wd:Q815436)", seems to be the correct entity we're looking for. Let's now look for properties related to casualties or death toll for this entity.

[Tool]
Top 10 property alternatives:
1. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as p/wdt): total (cumulative) number of people who died since start as a direct result of an event or cause
2. number of injured, also known as injured, injuries, injury toll, non-fatal injuries, number injured (wd:P1339 as p/wdt): number of people with non-fatal injuries in an event
3. point in time, also known as at time, as of, year, when, time of event (wd:P585 as p/wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
4. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as p/wdt): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
5. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
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. 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. 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
9. start time, also known as start date, since, valid, join time, joined (wd:P580 as p/wdt): time an entity begins to exist or a statement starts being valid, point in time

No other items found

[Assistant]
The property "number of deaths" (wd:P1120) seems to be the most relevant for our query. Let's construct a simple SPARQL query to retrieve the number of deaths associated with the Troubles.

```sparql
SELECT ?deaths
WHERE {
  wd:Q815436 wdt:P1120 ?deaths .
}
```

I'll execute this query to see if it returns the expected result.

[Tool]
Got 1 row and 1 column:
| deaths             |
| ------------------ |
| 3532 (xsd:decimal) |

[Assistant]
The query returned the number of deaths associated with the Troubles, which is 3,532.

To provide a complete answer, let's also check if there is any information about the number of injured, as this might give us a more comprehensive view of the casualties.

I'll modify the query to include the number of injured as well:

```sparql
SELECT ?deaths ?injured
WHERE {
  wd:Q815436 wdt:P1120 ?deaths .
  OPTIONAL { wd:Q815436 wdt:P1339 ?injured . }
}
```

I'll execute this updated query.

[Tool]
Got 1 row and 2 columns:
| deaths             | injured             |
| ------------------ | ------------------- |
| 3532 (xsd:decimal) | 47541 (xsd:decimal) |

[Assistant]
The query returned both the number of deaths and the number of injured associated with the Troubles. According to the data:

- Number of deaths: 3,532
- Number of injured: 47,541

This gives us a comprehensive view of the casualties resulting from the Troubles.

Now, I will provide the final SPARQL query and the answer to the user's question.

```sparql
SELECT ?deaths ?injured
WHERE {
  wd:Q815436 wdt:P1120 ?deaths .
  OPTIONAL { wd:Q815436 wdt:P1339 ?injured . }
}
```

The answer to the user's question is that the Troubles resulted in 3,532 deaths and 47,541 injuries.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?sibling WHERE {
  wd:Q189307 wdt:P3373 ?sibling .
  FILTER NOT EXISTS {
    ?sibling wdt:P570 []
  }
}

Got 6 rows and 1 column:
| sibling                            |
| ---------------------------------- |
| Hubert Messner (wd:Q28032172)      |
| Helmut Messner (wd:Q28053539)      |
| Erich Messner (wd:Q28053548)       |
| Waltraud Kastlunger (wd:Q28053561) |
| Hansjörg Messner (wd:Q28053579)    |
| Werner Messner (wd:Q28053586)      |

6 of Reinhold Messner's brothers and sisters are still alive.

[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] How many of Reinhold Messner's brothers still live?

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

[Tool]
Example 1:
Question:
Which actors were born in Germany?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q10800557 .
  {
    ?uri wdt:P19 wd:Q183 .
  } UNION {
    ?uri wdt:P19 / wdt:P17 wd:Q183 .
  }
}

Using entities:
film actor, also known as film actress, movie actor, movie actress (wd:Q10800557): actor who appears in films
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe

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)
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
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] None of these examples directly relate to our question about Reinhold Messner's brothers. However, we can infer that we need to look for information about Reinhold Messner and his siblings, and then filter out the ones who are still alive. Let's start by searching for Reinhold Messner in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Reinhold Messner (wd:Q189307): Italian mountaineer, adventurer and explorer, film director, mountaineer, politician, explorer, writer
2. Reinhold Messner, also known as Reinhold Meßner, Reinhold Oswald Messner (wd:Q121337911): Austrian Franciscan priest and philosopher, regular priest, philosopher
3. Markus Lanz und Reinhold Messner (wd:Q55978741): episode of Reinhold Beckmann trifft … (S1 E2)
4. The Unauthorized Biography of Reinhold Messner (wd:Q3989773): album by Ben Folds Five
5. 18092 Reinhold, also known as Reinhold (wd:Q2618622): asteroid
6. Reinhold (wd:Q2141320): lunar impact crater
7. Messner (wd:Q28812178): family name
8. Reinhold, also known as Reinhold (first name), Reinhold (given name) (wd:Q18091397): male given name
9. Bernhard Reinhold, also known as B. Reinhold, Reinhold (wd:Q16761534): German painter, painter
10. Messner (wd:Q1777589): 2012 film directed by Andreas Nickel

[Assistant] The first result, Reinhold Messner (wd:Q189307), is the correct entity we're looking for. Now let's find out what properties are associated with this entity, particularly those that might tell us about his siblings.

[Tool]
Got 657 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                         | object                                                                                |
| ----------------------------- | -------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- |
| Reinhold Messner (wd:Q189307) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Reinhold Messner (wd:Q189307) | occupation (wdt:P106)            | writer (wd:Q36180)                                                                                |
| Reinhold Messner (wd:Q189307) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                                |
| Reinhold Messner (wd:Q189307) | given name (wdt:P735)            | Andreas (wd:Q4926263)                                                                                |
| Reinhold Messner (wd:Q189307) | date of birth (wdt:P569)         | 1944-09-17T00:00:00Z (xsd:dateTime)                                                                                |
| Reinhold Messner (wd:Q189307) | Commons category (wdt:P373)      | Reinhold Messner                                                                                |
| Reinhold Messner (wd:Q189307) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Reinhold%20Messner%20at%20Frankfurt%20Book%20Fair%202017%20%2826%29%20%28cropped%29.jpg> |
| Reinhold Messner (wd:Q189307) | country of citizenship (wdt:P27) | Italy (wd:Q38)                                                                                |
| Reinhold Messner (wd:Q189307) | family name (wdt:P734)           | Messner (wd:Q28812178)                                                                                |
| Reinhold Messner (wd:Q189307) | place of birth (wdt:P19)         | Brixen (wd:Q185541)                                                                                |
| ...                           | ...                              | ...                                                                                |

[Assistant] From the list of properties, we don't see any direct information about Reinhold Messner's siblings. We need to search for a property that indicates siblings or family members. Let's search for such a property.

[Tool]
Top 10 property alternatives:
1. sibling, also known as is sister of, is the brother of, is the sibling of, is the sister of, sib (wd:P3373 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), relative
2. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
3. number of children, also known as children, children (number), how many children, issue, kids (wd:P1971 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): number of children of the person, animal, or character
4. child, also known as has son, kids, mother of, kid, issue (wd:P40 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
5. family, also known as royal house, noble family, member of family, house, dynasty (wd:P53 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): family, including dynasty and nobility houses. Not family name (use P734 for family name)., member of
6. family name identical to this given name, also known as surname identical to this given name, surname identical to this first name, related surname, related family name, last name identical to this first name (wd:P1533 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): last name that is the same as a given first name. Use on items for given names, different from
7. generational suffix, also known as age suffix, family suffix, Jr., Junior, Senior (wd:P8017 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): suffix used in name
8. twinning, also known as crystal twinning (wd:P537 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): type of twins a crystal forms
9. kinship to subject, also known as type of relationship, type of kinship, relation to, relationship (kinship), nature of kinship (wd:P1039 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): qualifier of "relative" (P1038) to indicate less usual family re...; indicate how the qualificator item is related to the main item, object of statement has role

[Assistant] The property `sibling` (wd:P3373) seems to be the most relevant for finding information about Reinhold Messner's siblings. Let's use this property to find his siblings and then check if they are still alive.

[Tool]
Got 8 rows and 1 column:
| sibling                            |
| ---------------------------------- |
| Günther Messner (wd:Q195351)       |
| Hubert Messner (wd:Q28032172)      |
| Helmut Messner (wd:Q28053539)      |
| Siegfried Messner (wd:Q28053544)   |
| Erich Messner (wd:Q28053548)       |
| Waltraud Kastlunger (wd:Q28053561) |
| Hansjörg Messner (wd:Q28053579)    |
| Werner Messner (wd:Q28053586)      |

[Assistant]
We have found the siblings of Reinhold Messner. Now, we need to determine which of these siblings are still alive. We can use the property `date of death` (wdt:P570) to check if a sibling has passed away. If a sibling does not have a `date of death`, it means they are still alive.

Let's construct a SPARQL query to find out which of these siblings are still alive.

[Tool]
Got 6 rows and 1 column:
| sibling                            |
| ---------------------------------- |
| Hubert Messner (wd:Q28032172)      |
| Helmut Messner (wd:Q28053539)      |
| Erich Messner (wd:Q28053548)       |
| Waltraud Kastlunger (wd:Q28053561) |
| Hansjörg Messner (wd:Q28053579)    |
| Werner Messner (wd:Q28053586)      |

[Assistant]
Based on the query results, we have determined that 6 of Reinhold Messner's siblings are still alive. These siblings are:

- Hubert Messner (wd:Q28032172)
- Helmut Messner (wd:Q28053539)
- Erich Messner (wd:Q28053548)
- Waltraud Kastlunger (wd:Q28053561)
- Hansjörg Messner (wd:Q28053579)
- Werner Messner (wd:Q28053586)

Now, let's provide the final answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?olympicGame ) AS ?count ) WHERE {
  wd:Q25369 wdt:P1344 ?olympicGame .
  ?olympicGame wdt:P31 / wdt:P279 * wd:Q5389
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 2 (xsd:int) |

Kobe Bryant participated in 2 Olympic Games.

[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] How many Olympic Games has Kobe Bryant taken part in?

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

[Tool] No examples found

[Assistant] There were no similar examples found. Let's start by searching for Kobe Bryant in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Kobe Bryant, also known as Kobe Bean Bryant, Kobe B. Bryant, Kobe, KB24, Black Mamba (wd:Q25369): American basketball player (1978–2020), professional athlete, basketball player, screenwriter
2. Kobe Bryant Day (wd:Q98969272): proposed Federal Holiday
3. death of Kobe Bryant, also known as Kobe Bryant death, Kobe Bryant's death (wd:Q83737550): 26 January 2020 death of Kobe Bryant in helicopter crash
4. Kobe Bryant Boulevard (wd:Q107299206): proposed street renaming in Los Angeles
5. NBA All-Star Game Kobe Bryant Most Valuable Player Award, also known as Kobe Bryant Most Valuable Player Award, Kobe Bryant MVP Award, NBA All-Star Game Kobe Bryant MVP Award (wd:Q31391): basketball award of the National Basketball Association (NBA)
6. Kobe Bryant China Fund (wd:Q6424297): for education, sports, and culture programs for children from China and the United States
7. Statue of Kobe Bryant (wd:Q125101336): sculpture in Los Angeles, California, U.S
8. Kobe Bryant/Ice Cube (wd:Q125446155): episode of All That (S4 E19)
9. Kobe Bryant sexual assault case (wd:Q6424298): legal case
10. Kobe Bryant in NBA Courtside (wd:Q3198120): 1998 video game

[Assistant] The top result is the entity we're looking for: Kobe Bryant (wd:Q25369). Now let's look for a property that indicates participation in the Olympic Games.

[Tool]
Top 10 property alternatives:
1. number of players in region, also known as number of people practicing sport, number of registered players, number of sportspeople, number of sportspersons (wd:P4909 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): number of registered players in a sport or people practicing a sport in a region
2. sports discipline competed in, also known as sport discipline competed in, weight class competed in, sports event, sports disciplines competed in, sports discipline (wd:P2416 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): discipline an athlete competed in within a sport, field of work
3. sports competition competed at (wd:P5249 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): edition of sports competitions at which the club or team that pl...ple: 2012–13 FC Barcelona season → 2012–13 UEFA Champions League
4. country, also known as sovereign state, state, land, host country (wd:P17 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. Kazakhstan Olympic Committee athlete ID, also known as NOC Kazakhstan athlete ID, olympic.kz, National Olympic Committee of the Republic of Kazakhstan athlete ID (wd:P11024 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for an athlete at the National Olympic Committee of the Republic of Kazakhstan website
6. record or record progression, also known as olympic record, world record (wd:P2869 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): links to item on the record or record progression
7. Olympic.org athlete ID (archived), also known as Olympic.org athlete identifier (archived), Olympic.org ID (wd:P3171 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for an athlete (sportsperson) at Olympic.org, a former website of the International Olympic Committee
8. Sports-Reference.com Olympic athlete ID (archived), also known as Olympic Reference ID, Sports-Reference.com Olympic athlete identifier (archived), Sports Reference ID, SRID, SR/Olympics athlete ID (wd:P1447 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for an Olympic athlete (sportsperson) at sports-reference.com/olympics/athletes/
9. World Games athlete ID, also known as International World Games Association athlete ID, IWGA athlete ID, The World Games athlete ID, TWG athlete ID, WG athlete ID (wd:P4588 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for an athlete at theworldgames.org, the official website of The World Games
10. New Zealand Olympic Committee athlete ID, also known as NZOC athlete ID, Olympic NZ, olympic.org.nz (wd:P4056 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for an athlete (sportsperson) at olympic.org.nz, a website of the New Zealand Olympic Committee (NZOC)

[Assistant]
None of these properties directly indicate participation in the Olympic Games. However, the property "sports competition competed at" (P5249) seems promising. We can check if it is used for Kobe Bryant and if it includes Olympic Games.

Let's list the triples where Kobe Bryant is the subject and "sports competition competed at" is the property.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that the property "sports competition competed at" (P5249) is not used for Kobe Bryant. Let's try another approach. We can search for the Olympic Games events and then see if Kobe Bryant participated in any of them.

First, let's search for the Olympic Games events.

[Tool]
Top 10 entity alternatives:
1. Olympic Games, major international sport event (wd:L64877-S1)
2. The Events of the Olympic Games (wd:Q54177476): scientific article published in April 1980
3. Cardiovascular Events in the 1996 Olympic Games (wd:Q44592451): scientific article published on November 15, 1997
4. Olympic Games, also known as Olympics (wd:Q5389): major international multi-sport event organised by International Olympic Committee
5. ancient Olympic Games, also known as Olympic Games (wd:Q188468): athletic competitions in ancient Greece
6. Olympic Games (wd:Q7089074): 1927 film by Robert A. McGowan
7. Olympic Games (wd:Q131445278): 2004 novel by Leslie What
8. Olympic Games (wd:Q76440806): print in the National Gallery of Art (NGA 144101)
9. Unfairness of certain events in the Olympic games (wd:Q52873125): scientific article published in October 1968
10. Olympics, Olympic Games (wd:L582506-S1)

[Assistant]
The top result for "Olympic Games" is wd:Q5389, which refers to the modern Olympic Games. Let's now check if Kobe Bryant participated in any of these events by looking for a property that connects athletes to the Olympic Games.

We can try the property "participant in" (P710) to see if it connects Kobe Bryant to any Olympic Games events.

[Tool] Got no rows and 3 columns

[Assistant]
The property "participant in" (P710) does not seem to connect Kobe Bryant to any Olympic Games events. Let's try another property that might indicate participation in the Olympic Games.

We can try the property "participated in" (P1344), which is often used to indicate participation in events.

[Tool]
Got 3 rows and 3 columns:
| subject                 | property                   | object                                       |
| ----------------------- | -------------------------- | -------------------------------------------- |
| Kobe Bryant (wd:Q25369) | participant in (wdt:P1344) | 2012 Summer Olympics (wd:Q8577)              |
| Kobe Bryant (wd:Q25369) | participant in (wdt:P1344) | 2008 Summer Olympics (wd:Q8567)              |
| Kobe Bryant (wd:Q25369) | participant in (wdt:P1344) | 2007 FIBA Americas Championship (wd:Q178595) |

[Assistant]
The property "participated in" (P1344) shows that Kobe Bryant participated in the 2008 Summer Olympics (wd:Q8567) and the 2012 Summer Olympics (wd:Q8577).

Now, let's write a SPARQL query to count the number of Olympic Games he participated in.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Assistant]
It seems that the initial query did not return the expected result. Let's refine the query to ensure we are correctly identifying the Olympic Games events.

We can use the property "instance of" (P31) to filter for events that are instances of the Olympic Games (wd:Q5389). Let's try the query again with this filter.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Assistant]
It seems that the query is still not returning the expected result. Let's verify the entities and properties involved:

1. **Kobe Bryant**: wd:Q25369
2. **Participated in**: wdt:P1344
3. **Olympic Games**: wd:Q5389
4. **Instance of**: wdt:P31

We know from the previous list that Kobe Bryant participated in the 2008 and 2012 Summer Olympics. Let's check if these events are indeed instances of the Olympic Games.

First, let's verify the instance of the 2008 and 2012 Summer Olympics.

[Tool]
Got 1 row and 3 columns:
| subject                         | property              | object                            |
| ------------------------------- | --------------------- | --------------------------------- |
| 2008 Summer Olympics (wd:Q8567) | instance of (wdt:P31) | Summer Olympic Games (wd:Q159821) |

[Assistant] The 2008 Summer Olympics (wd:Q8567) is an instance of the Summer Olympic Games (wd:Q159821). Let's check the 2012 Summer Olympics as well.

[Tool]
Got 1 row and 3 columns:
| subject                         | property              | object                            |
| ------------------------------- | --------------------- | --------------------------------- |
| 2012 Summer Olympics (wd:Q8577) | instance of (wdt:P31) | Summer Olympic Games (wd:Q159821) |

[Assistant]
The 2012 Summer Olympics (wd:Q8577) is also an instance of the Summer Olympic Games (wd:Q159821).

Since both events are instances of the Summer Olympic Games, we need to adjust our query to include the Summer Olympic Games (wd:Q159821) as well.

Let's update the SPARQL query to count the number of Olympic Games Kobe Bryant participated in, considering both the Olympic Games (wd:Q5389) and the Summer Olympic Games (wd:Q159821).

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 2 (xsd:int) |

[Assistant]
The updated SPARQL query correctly counts the number of Olympic Games Kobe Bryant participated in. He participated in 2 Olympic Games.

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(?olympicGame) AS ?count)
WHERE {
  wd:Q25369 wdt:P1344 ?olympicGame .
  ?olympicGame wdt:P31/wdt:P279* wd:Q5389
}
```

Answer: Kobe Bryant participated in 2 Olympic Games.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?state WHERE {
  wd:Q732858 wdt:P131 ?state .
  ?state wdt:P31 wd:Q35657 .
}

New Jersey

[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] which state inside USA is batman living in?

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

[Tool]
Example 1:
Question:
What is Batman's real name?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q2695156 wdt:P460 ?uri .
}

Using entities:
Batman, also known as the Bat-Man, the Batman, the Caped Crusader, the Bat, Sir Hemingford Grey (wd:Q2695156): fictional character in DC Comics, chief executive officer, businessperson, martial artist, philanthropist, vigilante, detective, superhero

Using properties:
said to be the same as, also known as may be, the same as, synonymous with, same as, same (wd:P460 as wdt): this item is said to be the same as that item, though this may be uncertain or disputed

Example 2:
Question:
Who created Batman?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q2695156 wdt:P170 ?uri .
}

Using entities:
Batman, also known as the Bat-Man, the Batman, the Caped Crusader, the Bat, Sir Hemingford Grey (wd:Q2695156): fictional character in DC Comics, chief executive officer, businessperson, martial artist, philanthropist, vigilante, detective, superhero

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)

Example 3:
Question:
Which state of the United States of America has the highest density?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q35657 ; wdt:P2046 ?area ; wdt:P1082 ?population .
  BIND( ( ?population / ?area ) AS ?density ) .
}
ORDER BY DESC ( ?density )
LIMIT 1

Using entities:
U.S. state, also known as U.S. states, US state, USA state, U.S.A. state, United States states (wd:Q35657): constituent political entity of the United States of America

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] From the examples, we can see that the entity for Batman is `wd:Q2695156`. We need to find out where Batman lives, specifically the state in the USA. Let's first check if there is a property that indicates Batman's place of residence.

[Tool]
Top 10 property alternatives:
1. 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
2. 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)
3. 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
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. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. student, also known as teacher to, teacher of, had student, students, pupils (wd:P802 as p/wdt): notable student(s) of the subject individual, significant person
8. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
9. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
10. collection, also known as editorial collection, series, repository, museum collection, held by (wd:P195 as p/wdt): art, museum, archival, or bibliographic collection of which the subject is part, part of

No other items found

[Assistant]
The property `wdt:P551` (residence) seems to be the most relevant for finding Batman's place of residence. Let's use this property to find out where Batman lives.

I will now construct a SPARQL query to find the place of residence for Batman.

[Tool]
Got 1 row and 1 column:
| residence                |
| ------------------------ |
| Gotham City (wd:Q732858) |

[Assistant]
The result shows that Batman's place of residence is Gotham City. Now, we need to determine which state in the USA Gotham City is located in. Let's find the state where Gotham City is situated.

I will construct a SPARQL query to find the state in the USA where Gotham City is located.

[Tool]
Got 1 row and 1 column:
| state                 |
| --------------------- |
| New Jersey (wd:Q1408) |

[Assistant]
The result indicates that Gotham City is located in New Jersey. Therefore, Batman lives in the state of New Jersey in the USA.

Here is the final SPARQL query and answer:

```sparql
SELECT ?state WHERE {
  wd:Q732858 wdt:P131 ?state .
  ?state wdt:P31 wd:Q35657 .
}
```

Answer: Batman lives in the state of New Jersey in the USA.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?woman ) AS ?count ) WHERE {
  wd:Q152778 wdt:P112 ?member .
  ?member wdt:P21 wd:Q6581072 .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[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] How many women were amongst the founding members of “The Bridge” (“Die Brücke”)?

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

[Tool]
Example 1:
Question:
Give me all female German chancellors.

SPARQL:
SELECT ?uri WHERE {
  ?uri wdt:P21 wd:Q6581072 .
  ?uri wdt:P39 wd:Q4970706 .
}

Using entities:
Federal Chancellor of Germany, also known as German Federal Chancellor, prime minister of Germany, German Chancellor, Federal Chancellor of the Federal Republic of Germany, Federal Chancellor (wd:Q4970706): head of government of the Federal Republic of Germany (1949–present)
female, also known as female human, women, woman, lady, human female (wd:Q6581072): to be used in "sex or gender" (P21) to indicate that the human s...nder" (P10339) to indicate that a word refers to a female person

Using properties:
sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
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

[Assistant] From the example, we can see that we need to identify the entity for "The Bridge" ("Die Brücke"), and then look for the founding members who are women. Let's first search for the entity "Die Brücke".

[Tool]
Top 10 entity alternatives:
1. Die Brücke, also known as The Bridge (wd:Q152778): German expressionist artist group
2. The Bridge, also known as Die Brücke, Freedom to Die (wd:Q509003): 1959 film directed by Bernhard Wicki
3. The Bridge, also known as Die Brücke (wd:Q1211772): short story by Franz Kafka
4. Die Brücke (wd:Q1211761): 2008 film directed by Wolfgang Panzer
5. Die Brücke (wd:Q895658): voluntary association
6. Die Brücke (wd:Q1211771): 1958 novel by Gregor Dorfmeister
7. Die Brücke (wd:Q1211766): former culture club in Brunswick, Germany
8. Brücke, Die (wd:Q103894820): encyclopedia article
9. Die Brücke (wd:Q123592907): periodical
10. Die Brücke (wd:Q120402955)

[Assistant] The correct entity for "Die Brücke" is `wd:Q152778`, which represents the German expressionist artist group. Next, let's find out the founding members of this group.

[Tool]
Top 10 property alternatives:
1. 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
2. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as p/wdt): founder or co-founder of this organization, religion, place or entity, creator
3. influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as p/wdt): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”

No other items found

[Assistant]
The property `founded by` (`wdt:P112`) seems to be the most relevant for identifying the founding members of "Die Brücke". Let's use this property to find the founding members and then filter out the women among them.

We will use the property `sex or gender` (`wdt:P21`) to check if the founding members are women. The IRI for "female" is `wd:Q6581072`.

Let's construct the SPARQL query to find the number of women among the founding members of "Die Brücke".

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Assistant]
The result shows that there are 0 women among the founding members of "Die Brücke".

Therefore, the answer to the question is:

**0 women were amongst the founding members of “The Bridge” (“Die Brücke”).**

Here is the final SPARQL query:

```sparql
SELECT (COUNT(?woman) AS ?count) WHERE {
  wd:Q152778 wdt:P112 ?member .
  ?member wdt:P21 wd:Q6581072 .
}
```

And the answer is:

**0**

[Tool] Stopped generation process