PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?character ?characterLabel ( ( YEAR( ?deathDate ) - YEAR( ?birthDate ) ) AS ?lifespan ) WHERE {
  VALUES ?character {
    wd:Q713701 wd:Q1057918
  }
  ?character wdt:P569 ?birthDate .
  ?character wdt:P570 ?deathDate .
  ?character rdfs:label ?characterLabel
  FILTER ( LANG( ?characterLabel ) = "en" )
}
ORDER BY DESC ( ?lifespan )

Got 2 rows and 3 columns:
| character                         | characterLabel           | lifespan     |
| --------------------------------- | ------------------------ | ------------ |
| Bellatrix Lestrange (wd:Q1057918) | Bellatrix Lestrange (en) | 47 (xsd:int) |
| Sirius Black (wd:Q713701)         | Sirius Black (en)        | 37 (xsd:int) |

Bellatrix Lestrange lived longer than Sirius Black. Bellatrix Lestrange lived for 47 years, while Sirius Black lived for 37 years.

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

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

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

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

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

[User] who lives longer, series black or bellatrix Lestrange?

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

[Tool] No examples found

[Assistant] There are no similar examples found for this question. Now I will identify the entities "series black" and "bellatrix Lestrange" in Wikidata to understand who they are and if there is information about their lifespan or age. First, I will search for "series black".

[Tool]
Top 10 entity alternatives:
1. black series of Polish documentary, also known as black series, The Black Series, black series of the Polish documentary (wd:Q9197940): Polish film movement
2. Blacklist, also known as Black List, Blacklist GMM, Blacklist  GMMTV, Blacklist The Series (wd:Q96373677): 2019 Thai TV series
3. LG Black Label Series (wd:Q6458370): series of mobile phones manufactured by LG Electronics
4. Alma Negra, also known as Black Soul, Black soul (Chilean series) (wd:Q117278271): Chilean television series
5. Black Mirror, series 5, also known as Black Mirror, season 5 (wd:Q64495720): season of television series
6. Black Mirror, series 1, also known as Black Mirror, season 1 (wd:Q18029789): season of television series
7. Black Mirror, series 2, also known as Black Mirror, season 2 (wd:Q18029874): season of television series
8. Black Mirror, series 3, also known as Black Mirror, season 3 (wd:Q48443750): season of television series
9. Black Mirror, series 4, also known as Black Mirror, season 4 (wd:Q48443908): season of television series
10. Black Mirror, series 6, also known as Black Mirror, season 6 (wd:Q115902593): season of television series

[Assistant] The search for "series black" did not return an entity that clearly corresponds to a person or character named "series black." It mostly returned TV series or product series. It is possible that the user meant "Sirius Black," a character from the Harry Potter series. I will now search for "bellatrix Lestrange" to confirm that it is the character from Harry Potter. Then I will search for "Sirius Black" to confirm the entity.

[Tool]
Top 10 entity alternatives:
1. Bellatrix Lestrange (wd:Q1057918): fictional character of the Harry Potter series, terrorist, magician, murderer
2. Bellatrix, also known as 24 Orionis, Gamma Orionis (wd:Q13066): star in the constellation Orion
3. Lestrange (wd:Q36864844): family name
4. Bellatrix, also known as Kolrassa Krókríðandi (wd:Q4883546): band
5. Bellatrix (wd:Q10427866): given name
6. Bellatrix (wd:Q129168077): French naval vessel
7. Bellatrix, also known as IMO 7043465 (wd:Q106678075): ship built in 1971
8. Bellatrix, also known as IMO 7820203 (wd:Q97996446): tugboat built in 1981
9. Lisbeth, also known as IMO 7233668, Thies, Carolina, Bellatrix (wd:Q115597773): ship built in 1972
10. Bellatrix (wd:Q103909859): shipwreck off the Scottish coast

[Assistant] The entity Bellatrix Lestrange (wd:Q1057918) is confirmed as a fictional character from the Harry Potter series. Now I will search for "Sirius Black" to confirm the entity for the other character.

[Tool]
Top 10 entity alternatives:
1. Sirius Black, also known as Padfoot, Snuffles, Sirius Black III (wd:Q713701): fictional character in J. K. Rowling's Harry Potter novels, vigilante
2. Sirius Black I, also known as Sirius Black (wd:Q15269539): fictional character in the Harry Potter series
3. Sirius Black II (wd:Q15269521): fictional character of the Harry Potter series
4. black, also known as blackness (wd:Q23445): darkest color
5. Sirius, also known as 9 Canis Majoris, HD 48915 (wd:Q3409): binary star system in the constellation of Canis Major
6. Black, also known as Black, AL (wd:Q66825): town in Alabama, United States
7. Black (wd:Q504409): English pop singer (1962–2016), singer-songwriter, singer
8. Black (wd:Q515416): 2005 film directed by Sanjay Leela Bhansali
9. Black, also known as Black (2006 video game), Black (video game) (wd:Q880040): 2006 first-person shooter video game
10. Black, also known as Beulraek (wd:Q38226507): 2017 South Korean TV series

[Assistant] The entity Sirius Black (wd:Q713701) is confirmed as a fictional character in the Harry Potter novels. Now I will check if there is information about the lifespan or age of these two characters: Sirius Black (wd:Q713701) and Bellatrix Lestrange (wd:Q1057918). I will start by listing the properties of Sirius Black to find relevant properties related to lifespan or age.

[Tool]
Top 10 property alternatives:
1. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as p/wdt): dissolved, abolished or demolished date, date on which the subject died, end time
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
3. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as p/wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
4. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as p/wdt): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
5. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as p/wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
6. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as p/wdt): female parent of the subject. For stepmother, use "stepparent" (P3448), parent
7. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as p/wdt): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
8. 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
9. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as p/wdt): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
10. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name

No other items found

[Assistant] For Sirius Black, the properties "date of birth" (wdt:P569) and "date of death" (wdt:P570) are available. Now I will check the same properties for Bellatrix Lestrange.

[Tool]
Top 10 property alternatives:
1. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as p/wdt): dissolved, abolished or demolished date, date on which the subject died, end time
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
3. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as p/wdt): full name of a person at birth, if different from their current, generally used name, name
4. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as p/wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
5. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as p/wdt): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
6. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as p/wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
7. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as p/wdt): female parent of the subject. For stepmother, use "stepparent" (P3448), parent
8. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as p/wdt): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
9. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
10. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

No other items found

[Assistant] Both Sirius Black and Bellatrix Lestrange have properties for date of birth (wdt:P569) and date of death (wdt:P570). I will now query these dates for both characters to compare their lifespans.

[Tool]
Got 2 rows and 4 columns:
| character                         | characterLabel           | birthDate                           | deathDate                           |
| --------------------------------- | ------------------------ | ----------------------------------- | ----------------------------------- |
| Bellatrix Lestrange (wd:Q1057918) | Bellatrix Lestrange (en) | 1951-01-01T00:00:00Z (xsd:dateTime) | 1998-05-02T00:00:00Z (xsd:dateTime) |
| Sirius Black (wd:Q713701)         | Sirius Black (en)        | 1959-11-03T00:00:00Z (xsd:dateTime) | 1996-06-18T00:00:00Z (xsd:dateTime) |

[Assistant] The data shows that Bellatrix Lestrange was born in 1951 and died in 1998, while Sirius Black was born in 1959 and died in 1996. To determine who lived longer, I will calculate the lifespan for each character and compare them. I will now write a SPARQL query to calculate the lifespan in years for both characters and compare them.

[Tool]
Got 2 rows and 3 columns:
| character                         | characterLabel           | lifespan     |
| --------------------------------- | ------------------------ | ------------ |
| Bellatrix Lestrange (wd:Q1057918) | Bellatrix Lestrange (en) | 47 (xsd:int) |
| Sirius Black (wd:Q713701)         | Sirius Black (en)        | 37 (xsd:int) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( DISTINCT ?country ) AS ?count ) WHERE {
  ?country wdt:P31 wd:Q6256 .
  FILTER NOT EXISTS {
    ?country wdt:P463 wd:Q1065
  }
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 20 (xsd:int) |

There are 20 countries that have never been members of the United Nations.

[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 countries have never been members of the UN?

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

[Tool]
Example 1:
Question:
What is the largest country in the world?

SPARQL:
SELECT DISTINCT * WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P2046 ?area .
  ?uri rdfs:label ?label
}
ORDER BY DESC ( ?area )
LIMIT 1

Using entities:
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
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)

Example 2:
Question:
With how many countries Iran has borders?

SPARQL:
SELECT ?uri WHERE {
  wd:Q794 wdt:P47 ?uri .
}

Using entities:
Iran, also known as ir, IRI, IRN, Islamic Rep. Iran, Islamic Republic of Iran (wd:Q794): country in Western Asia

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

Example 3:
Question:
Which countries have more than ten volcanoes?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  {
    ?volcano wdt:P31 wd:Q8072 .
  } UNION {
    ?volcano wdt:P31 ?type .
    ?type wdt:P279 * wd:Q8072 .
  }
  ?volcano wdt:P17 ?uri .
}
GROUP BY ?uri
HAVING ( COUNT( ?volcano ) > 10 )

Using entities:
volcano (wd:Q8072): natural, surface vent or fissure usually in a mountainous form

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

[Assistant]
The examples found do not directly address the question about countries that have never been members of the UN. However, from the examples, I identified that "country" is represented by wd:Q6256 and "instance of" is represented by wdt:P31.

To answer the question, I need to:
1. Identify all countries (instances of wd:Q6256).
2. Identify countries that have been members of the United Nations.
3. Count the countries that are not members of the United Nations.

I will start by searching for the property that indicates membership in the United Nations.

[Tool]
Top 10 property alternatives:
1. member count, also known as total members, number of members, count of members, amount of members, membership (wd:P2124 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): number of entities that are part of an organization at a particular time
2. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
3. UN/LOCODE, also known as LOCCODE, LOCODE, UNECE location code, UNECE LOCODE, United Nations location code (wd:P1937 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): geographic location code maintained by UNECE
4. start time, also known as start date, since, valid, join time, joined (wd:P580 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): time an entity begins to exist or a statement starts being valid, point in time
5. UN number, also known as UN code (wd:P695 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): four-digit number that identify hazardous substances and articles in the framework of international transport
6. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): the political party of which a person is or has been a member or otherwise affiliated, member of
7. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
8. union of, also known as exhaustive union of (wd:P2737 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): every instance of this class is an instance of at least one clas... "list item" P11260 as qualifiers to specify the list of classes
9. disjoint union of, also known as disjunction among, disjunction between, union of (wd:P2738 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): every instance of this class is an instance of exactly one class... "list item" P11260 as qualifiers to specify the list of classes, union of
10. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): some or all members of this group share the occupation

[Assistant]
The property "member of" (wdt:P463) seems to be the appropriate property to indicate membership in an organization such as the United Nations.

Next, I will find the entity for the United Nations to use it in the query. I will search for "United Nations" entity.

[Tool]
Top 10 entity alternatives:
1. United Nations, also known as the U.N., the UN, U.N., UN, United Nations Organization (wd:Q1065): global international and intergovernmental organization
2. United Nations (wd:Q7888317): American band
3. United Nations (wd:Q7888316): United Nations album
4. United Nations (wd:Q7888314): Rui En album
5. United Nations, also known as Canadian United, Canada United, Global United Nations Syndicate (wd:Q7888319): criminal gang who started in Vancouver, British Columbia
6. United Nations (wd:Q74063664): print in the National Gallery of Art (NGA 64023)
7. United Nations, also known as q Sm514 United Nations (wd:Q104713070): subject category of the 20th Century Press Archives
8. United Nations, also known as Star Trek UN, Star Trek United Nations, UN (wd:Q111240888): United Nations as depicted in the Star Trek multiverse
9. United Nations (wd:L620589-S1)
10. United Nations (wd:L618606-F1)

[Assistant]
The entity for the United Nations is wd:Q1065.

Now, I will write a SPARQL query to count the number of countries (instances of wd:Q6256) that have never been members of the United Nations (wd:Q1065) using the property "member of" (wdt:P463).

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 20 (xsd:int) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?person ?personLabel WHERE {
  ?person wdt:P800 wd:Q315296 .
  OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( LANG( ?personLabel ) = "en" )
  }
}

The Erlangen program was written by Felix Klein.

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

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

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

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

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

[User] Who wrote the Erlangen program?

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

[Tool]
Example 1:
Question:
Who was the doctoral supervisor of Albert Einstein?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q937 wdt:P184 ?uri
}

Using entities:
Albert Einstein (wd:Q937): German-born theoretical physicist (1879–1955), physicist

Using properties:
doctoral advisor, also known as PhD supervisor, promotor, supervisor, thesis advisor, advisor (wd:P184 as wdt): person who supervised the doctorate or PhD thesis of the subject, supervised by, student of

[Assistant]
The Erlangen program is likely an entity related to mathematics or a mathematical program. The question asks for the author or writer of the Erlangen program. The property we are looking for is likely "author" or "creator" or "written by."

I will first search for the entity "Erlangen program" in Wikidata to get its identifier. Then I will look for properties related to authorship or creators for that entity.

[Tool]
Top 10 entity alternatives:
1. Erlangen program (wd:Q315296): research program on the symmetries of geometry
2. computer program, also known as program, software program (wd:Q40056): sequence of instructions written in programming language to perform a specified task with a computer
3. Erlangen, also known as Medical Valley (wd:Q3126): city in Bavaria, Germany
4. project, also known as effort, program, programme (wd:Q170584): collaborative enterprise, frequently involving research or design, that is carefully planned to achieve a particular aim
5. plan, also known as plans, program, programme (wd:Q1371819): outline of a strategy for achievement of an objective
6. programme, also known as program (wd:Q1508646): informational booklet given out before a live event
7. The Program, also known as Icon, Program (wd:Q15615185): 2015 film
8. educational program, also known as programme, program, educational programme (wd:Q5341296): program written by the institution of education which determines the learning progress of individuals
9. Erlangen, also known as Erlangen station (wd:Q800737): railway halt in the urban district of Erlangen, Middle Franconia, Germany
10. The Program, also known as Program (wd:Q826289): 1993 film by David S. Ward

[Assistant]
The Erlangen program is identified as wd:Q315296 in Wikidata. It is described as a research program on the symmetries of geometry.

Next, I will search for properties related to authorship or creators for this entity. I will search for properties of the Erlangen program entity with a query related to "author" or "creator."

[Tool]
Top 10 property alternatives:
1. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as p/wdtn/wdt): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)
2. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
3. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
4. Treccani's Enciclopedia della Matematica ID, also known as Enciclopedia della Matematica ID (wd:P9621 as p/wdt): identifier for a topic in Treccani's Enciclopedia della Matematica, an Italian encyclopedia regarding mathematics
5. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as p/wdt): identifier for an article in the online version of Encyclopædia Britannica
6. ProofWiki ID, also known as Proof Wiki ID (wd:P6781 as p/wdt): identifier for a ProofWiki article
7. Encyclopedia of China (Third Edition) ID, also known as Encyclopedia of China ID (Third Edition) (wd:P10565 as p/wdt): identifier for an article in the online version of Encyclopedia of China (Third Edition)
8. Lex ID, also known as Den Store Danske ID, DSD ID (wd:P8313 as p/wdt): identifier of an article in the online encyclopedia.lex.dk

No other items found

[Assistant] The search for properties related to "author" for the Erlangen program entity did not return a direct property for author or creator. I will now try a more general property search for "creator" or "written by" to find a suitable property that might indicate the author of the Erlangen program.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as p/wdtn/wdt): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)
3. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as p/wdt): identifier for an article in the online version of Encyclopædia Britannica
4. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
5. ProofWiki ID, also known as Proof Wiki ID (wd:P6781 as p/wdt): identifier for a ProofWiki article
6. Lex ID, also known as Den Store Danske ID, DSD ID (wd:P8313 as p/wdt): identifier of an article in the online encyclopedia.lex.dk

No other items found

[Assistant] No direct property for "creator" or "author" was found for the Erlangen program entity. I will now try a general property search with the query "written by" to see if there is any relevant property.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as p/wdtn/wdt): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)
3. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
4. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as p/wdt): identifier for an article in the online version of Encyclopædia Britannica
5. ProofWiki ID, also known as Proof Wiki ID (wd:P6781 as p/wdt): identifier for a ProofWiki article

No other items found

[Assistant] No direct property for "written by" was found for the Erlangen program entity. I will now try to find the author by querying the property "author" (wdt:P50) for the Erlangen program entity directly. This property is commonly used for authorship in Wikidata.

[Tool] Got no rows and 2 columns

[Assistant] The Erlangen program entity does not have a direct "author" property (wdt:P50) assigned. I will now try to find the creator or author by looking for statements about the Erlangen program that might indicate the person who wrote or created it. I will try to find any property linking the Erlangen program to a person. I will list all properties and objects for the Erlangen program to see if any indicate authorship.

[Tool]
Got 128 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                                                | object                              |
| ----------------------------- | ------------------------------------------------------- | ----------------------------------- |
| Erlangen program (wd:Q315296) | instance of (wdt:P31)                                   | research (wd:Q42240)                |
| Erlangen program (wd:Q315296) | Freebase ID (wdt:P646)                                  | /m/01k8tb                           |
| Erlangen program (wd:Q315296) | Microsoft Academic ID (wdtn:P6366)                      | <https://makg.org/entity/111593780> |
| Erlangen program (wd:Q315296) | Encyclopædia Britannica Online ID (wdt:P1417)           | topic/Erlanger-program              |
| Erlangen program (wd:Q315296) | Lex ID (wdt:P8313)                                      | Erlangen-programmet                 |
| Erlangen program (wd:Q315296) | Encyclopedia of China (Third Edition) ID (wdt:P10565)   | 318393                              |
| Erlangen program (wd:Q315296) | nLab ID (wdt:P4215)                                     | Erlangen program                    |
| Erlangen program (wd:Q315296) | ProofWiki ID (wdt:P6781)                                | Definition:Erlangen_Program         |
| Erlangen program (wd:Q315296) | Treccani's Enciclopedia della Matematica ID (wdt:P9621) | programma-di-erlangen               |
| Erlangen program (wd:Q315296) | wdt:P31279                                              | research (wd:Q42240)                |
| ...                           | ...                                                     | ...                                 |

[Assistant] The properties listed for the Erlangen program do not directly indicate an author or creator. I will now try a different approach: I will search for people related to the Erlangen program by querying for people who have the Erlangen program as a notable work or something similar. I will search for people whose notable work (wdt:P800) is the Erlangen program (wd:Q315296).

[Tool]
Got 1 row and 2 columns:
| person                  | personLabel      |
| ----------------------- | ---------------- |
| Felix Klein (wd:Q76641) | Felix Klein (en) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( DISTINCT ?character ) AS ?count ) WHERE {
  ?character wdt:P31 wd:Q95074 .
  ?character wdt:P106 wd:Q11397897 .
  ?character wdt:P21 wd:Q6581072 .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 6 (xsd:int) |

There are 6 fictional female swordfighters in Wikidata.

[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 fictional female swordfighters are there?

[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]
The example shows how to query for female individuals by using the property "sex or gender" (P21) with the value "female" (Q6581072). We need to find entities that are fictional swordfighters and female.

Step 1: Identify the entity for "fictional swordfighter."
Step 2: Use the property "sex or gender" (P21) with the value "female" (Q6581072).
Step 3: Count the number of such entities.

I will first search for the entity "fictional swordfighter" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. fiction, also known as imaginary genre, imaginary art genre, fiction form, fictional, fictional art form (wd:Q8253): genre and narrative form, in any medium, consisting of people, e... imaginary—in other words, not based strictly on history or fact
2. swordfighter, also known as sword-fighter, swordsman, swordsmen, swordswoman (wd:Q11397897): person who fights with a sword
3. Fictional (wd:Q5446562): German musical project formed by Gerrit Thomas
4. Fictional (wd:Q110568363): podcast
5. fictional (wd:L614098-S1)
6. fictional (wd:L4587-F1)
7. fictional (wd:L4587)
8. fictional (wd:L205494-S1)
9. character, also known as fictional character (wd:Q95074): fictional human or non-human character in a narrative work of art
10. villain, also known as evil character, villainess, fictional villainess, fictional villain, fictional bad guy (wd:Q290691): evil character in a story

[Assistant]
The entity "swordfighter" (wd:Q11397897) corresponds to a person who fights with a sword. We want fictional swordfighters, so we need to combine this with the concept of "fictional character" (wd:Q95074).

Next, I will search for properties that can link a fictional character to being a swordfighter or having the occupation of swordfighter. I will search for properties related to "occupation" or "instance of" for the entity "fictional character" to find if "swordfighter" can be an occupation or instance.

[Tool]
Top 10 property alternatives:
1. 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
2. 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)
3. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as p/wdt): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
4. properties for this type, also known as uses properties, Wikidata properties for this type, Wikidata properties for this class, uses property, things one could say about (wd:P1963 as p/wdt): when this subject is used as object of “instance of”, the following properties normally apply
5. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as p/wdt): main Wikidata property for this item
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
8. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
9. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
10. equivalent class, also known as schema.org type, same kind of thing, same grouping, same class, external class (wd:P1709 as p/wdt): equivalent class in other ontologies (use property URI), exact match, URL

No other items found

[Assistant]
The property "instance of" (wdt:P31) is commonly used to indicate that an entity is an instance of a class. We can use this to check if a fictional character is an instance of a swordfighter.

Now, I will check if there are any fictional female swordfighters by querying for entities that are instances of swordfighter (wd:Q11397897) and have the sex or gender female (wd:Q6581072). I will also check if these entities are instances of fictional character (wd:Q95074) to ensure they are fictional. Then I will count the number of such entities.

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

[Assistant]
The query returned 0, meaning there are no entities in Wikidata that are explicitly marked as fictional female swordfighters using the properties "instance of swordfighter," "sex or gender female," and "instance of fictional character."

I will try a broader approach by checking if there are fictional characters who have the occupation or role of swordfighter and are female. I will search for properties related to "occupation" or "role" for fictional characters.

[Tool]
Top 10 property alternatives:
1. 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
2. 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)
3. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as p/wdt): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
4. properties for this type, also known as uses properties, Wikidata properties for this type, Wikidata properties for this class, uses property, things one could say about (wd:P1963 as p/wdt): when this subject is used as object of “instance of”, the following properties normally apply
5. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as p/wdt): main Wikidata property for this item
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
8. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
9. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
10. equivalent class, also known as schema.org type, same kind of thing, same grouping, same class, external class (wd:P1709 as p/wdt): equivalent class in other ontologies (use property URI), exact match, URL

No other items found

[Assistant] There is no direct property for occupation or role for fictional characters in the search results. I will try to find properties related to "occupation" in general to see if swordfighter is used as an occupation. I will search for properties related to "occupation."

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
3. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): some or all members of this group share the occupation
4. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): type of agents that study this subject or work in this field
5. position held, also known as function, held position, holds position, job, office held (wd:P39 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): subject currently or formerly holds the object position or public office
6. employer, also known as working at, working for, working place, works at, works for (wd:P108 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): person or organization for which the subject works or worked, affiliation
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): the object is a country that recognizes the subject as its citizen, country
8. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): person or organization occupying property, used by
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): specialization of a person or organization; see P106 for the occupation, interested in
10. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): location where persons or organisations were actively participating in employment, business or other work, significant place, location

[Assistant]
The property "occupation" (wdt:P106) is the relevant property to indicate the occupation of a person.

I will now query for entities that are fictional characters (wd:Q95074), have the occupation swordfighter (wd:Q11397897), and are female (wd:Q6581072). Then I will count the number of such entities.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 6 (xsd:int) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?date WHERE {
  wd:Q71719 wdt:P1619 ?date .
}

The Hollywood Walk of Fame officially opened in the year 1960.

[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] In what year did the Hollywood Walk of Fame open?

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

[Tool]
Example 1:
Question:
When was the Statue of Liberty built?

SPARQL:
SELECT DISTINCT ?date WHERE {
  wd:Q9202 wdt:P571 ?date .
}

Using entities:
Statue of Liberty, also known as La Liberte eclairant la monde, La Liberté éclairant le monde, Liberty Enlightening the World, The Statue of Liberty Enlightening the World (wd:Q9202): sculpture on Liberty Island in New York Harbor in New York City, New York, United States

Using properties:
inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt): time when an entity begins to exist; for date of official opening use P1619, start time

[Assistant]
The example shows that the property wdt:P571 (inception) is used to find the year something was built or started. For the Hollywood Walk of Fame, we can try to find its entity and then query its inception or opening date.

Next, I will search for the entity "Hollywood Walk of Fame" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Hollywood Walk of Fame, also known as Walk of Fame (wd:Q71719): more than 2,700 five-pointed terrazzo and brass stars embedded i...ulevard and three blocks of Vine Street in Hollywood, California
2. star on Hollywood Walk of Fame, also known as Hollywood Walk of Fame star (wd:Q17985761): award in the Hollywood Walk of Fame, Hollywood, California, United States
3. Hollywood's Rock Walk of Fame (wd:Q3139400)
4. Walk of Fame (wd:Q48673901): 2017 film by Jesse Thomas
5. Walk of Fame (wd:Q51084447): street in Saint Petersburg, Russia
6. Starr gets star; Ringo added to Hollywood Walk of Fame (wd:Q18021457): Wikinews article
7. Walk of Fame (wd:Q7962075): memorial for famous dogs in Battersea Park, London, England, UK
8. walk of fame (wd:Q47502370): sidewalk or similar construction that commemorates outstanding individuals in a particular group
9. Walk of Fame (wd:Q114476628): episode of Cupcake Wars (S2 E11)
10. Walk of Fame, also known as Wigan's Walk of Fame, Believe Square (wd:Q121879112): public walkway in Wigan, England

[Assistant] The entity "Hollywood Walk of Fame" is wd:Q71719. Now I will check the properties related to dates for this entity, focusing on inception or opening date.

[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. date of official opening, also known as launch date, launched, officially opened on, official opening, official opening time (wd:P1619 as p/wdt): date or point in time a place, organization, or event officially opened, start time, inception
3. title, also known as name, titled, page name, original title, known as (wd:P1476 as p/wdt): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
4. 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
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. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
8. 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
9. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant] The property "date of official opening" (wdt:P1619) seems to be the most appropriate to find the year the Hollywood Walk of Fame opened. I will now query the date of official opening for the Hollywood Walk of Fame (wd:Q71719).

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 1960-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?language ) AS ?count ) WHERE {
  wd:Q843 wdt:P37 ?language .
}

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

Pakistan has 2 official languages according to Wikidata.

[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 official languages has Pakistan ?

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

[Tool]
Example 1:
Question:
What languages are spoken in Pakistan?

SPARQL:
SELECT * {
  wd:Q843 wdt:P2936 ?uri .
}

Using entities:
Pakistan, also known as Islamic Republic of Pakistan, PAK, pk, Republic of Pakistan (wd:Q843): sovereign state in South Asia

Using properties:
language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt): language widely used (spoken or written) in this place or at this event or organisation

Example 2:
Question:
Which countries have more than two official languages?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P37 ?language .
}
GROUP BY ?uri
HAVING ( COUNT( ?language ) > 2 )

Using entities:
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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

Example 3:
Question:
Which country has the most official languages?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P37 ?language .
}
GROUP BY ?uri
ORDER BY DESC ( COUNT( ?language ) )
LIMIT 1

Using entities:
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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

[Assistant] From the examples, I see that the entity for Pakistan is wd:Q843 and the property for official language is wdt:P37. I will now write a query to count the number of official languages of Pakistan.

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

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?creator ?creatorLabel WHERE {
  wd:Q16889037 wdt:P170 ?creator .
  OPTIONAL {
    ?creator rdfs:label ?creatorLabel FILTER ( LANG( ?creatorLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| creator                      | creatorLabel        |
| ---------------------------- | ------------------- |
| Tina Fey (wd:Q14540)         | Tina Fey (en)       |
| Robert Carlock (wd:Q7342763) | Robert Carlock (en) |

The creators of Unbreakable Kimmy Schmidt are Tina Fey and Robert Carlock.

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

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

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

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

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

[User] Who was the creator of Unbreakable Kimmy Schmidt ?

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

[Tool]
Example 1:
Question:
Who created Family Guy?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q5930 wdt:P170 ?uri
}

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

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 2:
Question:
Who created Goofy?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q111135 wdt:P170 ?uri .
}

Using entities:
Goofy, also known as Dippy Dawg, George Geef, Goofy Goof (wd:Q111135): Disney cartoon character

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 television shows were created by Walt Disney?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 / wdt:P279 * wd:Q7725310 ; wdt:P170 wd:Q8704 .
}

Using entities:
series of creative works, also known as serial (wd:Q7725310): ordered set of creative works
Walt Disney (wd:Q8704): American animator and producer (1901–1966), television presenter, film producer, film director, caricaturist, manufacturer, screenwriter, illustrator, voice actor, film actor, producer, director, animator, inventor, painter, writer, actor

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

[Assistant]
From the examples, the property for "creator" or "created by" is wdt:P170. We need to find the entity for "Unbreakable Kimmy Schmidt" and then query its creator using this property.

First, I will search for the entity "Unbreakable Kimmy Schmidt" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Unbreakable Kimmy Schmidt (wd:Q16889037): American comedy streaming television series
2. Unbreakable Kimmy Schmidt, season 1 (wd:Q21186375): season of television series
3. Unbreakable Kimmy Schmidt, season 4 (wd:Q54847377): season of television series
4. Unbreakable Kimmy Schmidt, season 3 (wd:Q30158232): season of television series
5. Unbreakable Kimmy Schmidt, season 2 (wd:Q25093973): season of television series
6. Unbreakable Kimmy Schmidt theme song (wd:Q28787990): song
7. Unbreakable Kimmy Schmidt: Kimmy vs. the Reverend, also known as Kimmy vs. the Reverend, Unbreakable Kimmy Schmidt: Kimmy vs the Reverend (wd:Q98708760): 2020 interactive film directed by Claire Scanlon
8. Kimmy Schmidt, also known as Kimberly Cougar Schmidt, Kimberly Schmidt (wd:Q23017207): fictional Protagonist of Unbreakable Kimmy Schmidt
9. Käthe Kollwitz, also known as Kėte Kolʹvit︠s︡, Käthe Schmidt Kollwitz, Kʻo-le-hui-chih, Kathe Schmidt, Käthe Schmidt (wd:Q142472): German printmaker and sculptor (1867–1945), architectural draftsperson, graphic artist, autobiographer, poster artist, draftsperson, lithographer, illustrator, printmaker, sculptor, designer, painter, artist
10. Unbreakable (wd:Q650613): 2000 film directed by M. Night Shyamalan

[Assistant] I found the entity for "Unbreakable Kimmy Schmidt" as wd:Q16889037 which is an American comedy streaming television series. Now I will query for the creator (wdt:P170) of this entity.

[Tool]
Got 2 rows and 2 columns:
| creator                      | creatorLabel        |
| ---------------------------- | ------------------- |
| Tina Fey (wd:Q14540)         | Tina Fey (en)       |
| Robert Carlock (wd:Q7342763) | Robert Carlock (en) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( DISTINCT ?movie ) AS ?count ) WHERE {
  ?movie wdt:P57 wd:Q8006 .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 32 (xsd:int) |

Akira Kurosawa directed 32 movies according to Wikidata.

[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 movies were directed by Akira Kurosawa ?

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

[Tool]
Example 1:
Question:
Which movies did Kurosawa direct?

SPARQL:
SELECT DISTINCT * WHERE {
  ?uri wdt:P57 wd:Q8006 .
}

Using entities:
Akira Kurosawa, also known as Kurosawa Akira, Kurosawa (wd:Q8006): Japanese filmmaker (1910–1998), film producer, film director, screenwriter, film editor, producer, director, painter, writer

Using properties:
director, also known as film director, movie director, game director, directed by (wd:P57 as wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator

Example 2:
Question:
Which films did Stanley Kubrick direct?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P57 wd:Q2001
}

Using entities:
Stanley Kubrick, also known as Kubrick (wd:Q2001): American filmmaker (1928–1999), executive producer, camera operator, cinematographer, film producer, film director, screenwriter, photographer, scenographer, film editor, director

Using properties:
director, also known as film director, movie director, game director, directed by (wd:P57 as wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator

Example 3:
Question:
How many movies did Park Chan-wook direct?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) as ?count ) WHERE {
  ?uri wdt:P57 wd:Q315484 .
}

Using entities:
Park Chan-wook, also known as Park Chan-uk, Chan-wook Park (wd:Q315484): South Korean film director, screenwriter and film producer (born 1963), film director, film producer, screenwriter, film critic, politician, director

Using properties:
director, also known as film director, movie director, game director, directed by (wd:P57 as wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator

[Assistant] From the examples, the property for director is wdt:P57 and Akira Kurosawa's entity is wd:Q8006. We can count the number of movies directed by Akira Kurosawa using a similar query pattern. I will now write and execute the SPARQL query to get the count of movies directed by Akira Kurosawa.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 32 (xsd:int) |

[Tool] Stopped generation process