PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?character ?birth ?death ( ( YEAR( ?death ) - YEAR( ?birth ) ) AS ?lifespan ) WHERE {
  VALUES ?character {
    wd:Q713701 wd:Q1057918
  }
  ?character wdt:P569 ?birth ; wdt:P570 ?death .
}
ORDER BY DESC ( ?lifespan )

Sirius Black was born in 1959 and died in 1996, living about 37 years. Bellatrix Lestrange was born in 1951 and died in 1998, living about 47 years. Therefore, Bellatrix Lestrange lived longer than Sirius Black.

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

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

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

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

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

[User] who 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, let's identify the entities "Sirius Black" and "Bellatrix Lestrange" in Wikidata to get their birth and death dates or lifespan information. I will start by searching for "Sirius Black" entity.

[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" is wd:Q713701, a fictional character in J. K. Rowling's Harry Potter novels. Now I will search for "Bellatrix Lestrange" 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" is wd:Q1057918, a fictional character of the Harry Potter series. Now I will check the birth and death dates or lifespan information for Sirius Black (wd:Q713701).

[Tool]
Got 396 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                         | object                                                                                |
| ------------------------- | -------------------------------- | --------------------------------------------------------------------------------------------- |
| Sirius Black (wd:Q713701) | instance of (wdt:P31)            | animagus (wd:Q830248)                                                                         |
| Sirius Black (wd:Q713701) | occupation (wdt:P106)            | vigilante (wd:Q3190387)                                                                       |
| Sirius Black (wd:Q713701) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                            |
| Sirius Black (wd:Q713701) | given name (p:P735)              | s:Q713701-50493C2B-C763-43EC-AB19-18BDBE729026                                                |
| Sirius Black (wd:Q713701) | date of birth (wdt:P569)         | 1959-11-03T00:00:00Z (xsd:dateTime)                                                           |
| Sirius Black (wd:Q713701) | Commons category (wdt:P373)      | Sirius Black                                                                                |
| Sirius Black (wd:Q713701) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Sirius%20Black%20fanart%20-%20Cor-Sa.jpg> |
| Sirius Black (wd:Q713701) | country of citizenship (wdt:P27) | United Kingdom (wd:Q145)                                                                      |
| Sirius Black (wd:Q713701) | family name (wdt:P734)           | Black (wd:Q2662465)                                                                           |
| Sirius Black (wd:Q713701) | part of (wdt:P361)               | Black family (wd:Q804258)                                                                     |
| ...                       | ...                              | ...                                                                                |

[Assistant] Sirius Black (wd:Q713701) has a date of birth: 1959-11-03. Now I will check the death date or date of death for Sirius Black.

[Tool]
Got 1 row and 3 columns:
| subject                   | property                 | object                              |
| ------------------------- | ------------------------ | ----------------------------------- |
| Sirius Black (wd:Q713701) | date of death (wdt:P570) | 1996-06-18T00:00:00Z (xsd:dateTime) |

[Assistant] Sirius Black died on 1996-06-18. Now I will check the birth and death dates or lifespan information for Bellatrix Lestrange (wd:Q1057918).

[Tool]
Got 371 rows and 3 columns, showing the first 10 rows below:
| subject                           | property                         | object                                                                                |
| --------------------------------- | -------------------------------- | -------------------------------------------------------------------------------------------- |
| Bellatrix Lestrange (wd:Q1057918) | instance of (wdt:P31)            | literary character (wd:Q3658341)                                                             |
| Bellatrix Lestrange (wd:Q1057918) | occupation (wdt:P106)            | terrorist (wd:Q12414919)                                                                     |
| Bellatrix Lestrange (wd:Q1057918) | sex or gender (wdt:P21)          | female (wd:Q6581072)                                                                         |
| Bellatrix Lestrange (wd:Q1057918) | given name (wdt:P735)            | Bellatrix (wd:Q10427866)                                                                     |
| Bellatrix Lestrange (wd:Q1057918) | date of birth (wdt:P569)         | 1951-01-01T00:00:00Z (xsd:dateTime)                                                          |
| Bellatrix Lestrange (wd:Q1057918) | Commons category (wdt:P373)      | Bellatrix Lestrange                                                                          |
| Bellatrix Lestrange (wd:Q1057918) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Bellatrix%20Lestrange%20by%20Candra.jpg> |
| Bellatrix Lestrange (wd:Q1057918) | country of citizenship (wdt:P27) | United Kingdom (wd:Q145)                                                                     |
| Bellatrix Lestrange (wd:Q1057918) | family name (wdt:P734)           | Black (wd:Q2662465)                                                                          |
| Bellatrix Lestrange (wd:Q1057918) | part of (wdt:P361)               | Black family (wd:Q804258)                                                                    |
| ...                               | ...                              | ...                                                                                |

[Assistant] Bellatrix Lestrange (wd:Q1057918) has a date of birth: 1951-01-01. Now I will check the death date or date of death for Bellatrix Lestrange.

[Tool]
Got 1 row and 3 columns:
| subject                           | property                 | object                              |
| --------------------------------- | ------------------------ | ----------------------------------- |
| Bellatrix Lestrange (wd:Q1057918) | date of death (wdt:P570) | 1998-05-02T00:00:00Z (xsd:dateTime) |

[Assistant] Bellatrix Lestrange died on 1998-05-02. Now I will calculate the lifespan of both characters and compare who lived longer using a SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer correctly identifies the birth and death years of both Sirius Black and Bellatrix Lestrange and calculates their lifespans accurately. The SPARQL query is well-formed, uses the correct entities and properties, and returns the expected results. The explanation clearly states that Bellatrix Lestrange lived longer than Sirius Black based on the data. No further refinement is necessary.


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
  }
  FILTER NOT EXISTS {
    ?country wdt:P31 / wdt:P279 * wd:Q3024240
  }
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 10 (xsd:int) |

After correcting the filter to exclude only historical countries, there are 10 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

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 show how to query countries and their properties. To answer the question "How many countries have never been members of the UN?", I need to:

1. Identify the entity for "country" (likely wd:Q6256).
2. Identify the entity for "United Nations" (likely wd:Q1065).
3. Find the property that indicates membership in an organization (likely wdt:P463 "member of").
4. Query all countries that are not members of the United Nations.
5. Count those countries.

I will first search for the property related to "member of" to confirm the correct property to use.

[Tool]
Top 10 property alternatives:
1. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): the political party of which a person is or has been a member or otherwise affiliated, member of
2. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): 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. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): some or all members of this group share the occupation
4. member count, also known as total members, number of members, count of members, amount of members, membership (wd:P2124 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): number of entities that are part of an organization at a particular time
5. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): (list of) direct subdivisions of an administrative territorial entity, has part(s)
6. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
7. affiliation, also known as association, sister society, affiliated with, affiliated to, associated with (wd:P1416 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): organization that a person or organization is affiliated with (not necessarily member of or employed by)
8. member category, also known as category for members (wd:P6365 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): category item for members of the organization
9. represented by, also known as agent, managed by, manager, managing agent, rep (wd:P1875 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): person or agency that represents or manages the subject
10. start time, also known as start date, since, valid, join time, joined (wd:P580 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): time an entity begins to exist or a statement starts being valid, point in time

[Assistant] The property "member of" (wdt:P463) is the correct property to indicate membership in an organization. Now, I will find the entity for "United Nations" to use it in the query.

[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 "United Nations" is wd:Q1065. Now I will write a SPARQL query to count the number of countries (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        |
| ------------ |
| 17 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly identifies countries (wd:Q6256) and filters out those that are members of the United Nations (wd:Q1065) using the property 'member of' (wdt:P463). However, the property 'member of' (P463) is not the most appropriate for indicating UN membership. Instead, the property 'member of' for organizations is usually represented by 'country's membership in an international organization' (P463) but it might not be consistently used for UN membership. A more precise property to check UN membership is 'member of' (P463) but it is better to verify if there is a dedicated property for UN membership or use a more reliable approach such as checking if the country has the United Nations as an 'instance of' or 'part of' membership. Also, the query does not consider historical or dissolved countries, which might affect the count. The answer '17' might be correct but it is recommended to verify the property used for UN membership and possibly refine the query to ensure accuracy. Additionally, adding labels for better readability in optional clauses could improve the query's usability.

[Assistant]
Thank you for the feedback. I will refine the approach to verify if there is a more precise property specifically indicating UN membership or a better way to identify countries that are members of the UN. I will also consider adding labels for better readability and ensure the query excludes historical or dissolved countries.

First, I will search for properties related to "United Nations membership" to see if there is a more specific property than "member of" (wdt:P463).

[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 ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): 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 ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): 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 ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): geographic location code maintained by UNECE
4. start time, also known as start date, since, valid, join time, joined (wd:P580 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): 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 ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): 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 ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): 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 ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): 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 ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): 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 ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): 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 ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): some or all members of this group share the occupation

[Assistant]
There is no more specific property for United Nations membership than "member of" (wdt:P463). However, to ensure accuracy, I will check if countries have a statement about membership in the United Nations (wd:Q1065) using the property "member of" (wdt:P463) and exclude historical or dissolved countries by filtering out those that are instances of "historical country" or "dissolved country."

I will also add labels for better readability. I will now write the refined SPARQL query.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 10 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly identifies countries that have never been members of the United Nations by filtering out historical and dissolved countries. However, there is a mistake in the use of the entity for dissolved countries: wd:Q3024241 refers to a genus of crab spiders (Runcinia), not dissolved countries. The correct entity for dissolved countries should be wd:Q3024241 replaced with wd:Q3024241's intended entity, which is likely wd:Q3024241 is incorrect. You should use wd:Q3024241 replaced by wd:Q3024241's correct identifier for dissolved countries (likely wd:Q3024241 is a typo or wrong). Also, the query uses the property P463 (member of) to check UN membership, but the more appropriate property for country membership in an organization is P463, which is correct, but ensure that the filter excludes countries that have ever been members. Finally, consider adding an optional clause to retrieve labels for better interpretability, but this is optional. Overall, the query logic is sound but needs correction of the dissolved country entity to improve accuracy.

[Assistant] Thank you for the feedback. I will correct the entity for dissolved countries. The entity I used (wd:Q3024241) is incorrect and refers to a genus of crab spiders. I will search for the correct entity for "dissolved country" to use in the query.

[Tool]
Top 10 entity alternatives:
1. country, also known as countries (wd:Q6256): distinct territorial body or political entity
2. country music, also known as country, country and western, country & western (wd:Q83440): genre of American popular music
3. sovereign state, also known as country, nation, sovereign country, sovereign nation, Westphalian state (wd:Q3624078): state that has the highest authority over a territory
4. Dennis Rodman, also known as Rodzilla, Psycho, The Worm, Worm, Country (wd:Q201608): American basketball player, professional wrestler, basketball player, amateur wrestler, basketball coach, voice actor, film actor, actor
5. Country (wd:Q1754454): 1984 film directed by Richard Pearce
6. dissolution, also known as ceased, cessation, closing, dissolve, dissolved (wd:Q5282797): legal event that terminates a legal entity, as of a company, marriage, partnership, or adoption
7. .country (wd:Q20571777): top-level domain
8. Country (wd:Q5177190): music album by Anne Murray
9. Country (wd:Q48816259): People in rural areas of the United States
10. Country (wd:Q26779428): Chilean political party founded in 2016

[Assistant] I did not find a direct entity for "dissolved country" in the search results. I will try searching for "historical country" to see if there is a related entity that might also cover dissolved countries.

[Tool]
Top 10 entity alternatives:
1. historical country, also known as country or state that doesn't exist, country or state that no longer exists, defunct state, former country, former state (wd:Q3024240): country, state or territory that once existed
2. Historical country (wd:L231802-S2)
3. Buffalo Country Historical Marker (wd:Q49476134): park in Valley County, Montana, United States of America
4. Buffalo Country Historical Marker (wd:Q49476133): park in Big Horn County, Montana, United States of America
5. Butte Country Historical Marker (wd:Q34844338): park in the United States of America
6. Comanche Country Historical Marker (wd:Q49479445): park in Quay County, New Mexico, United States of America
7. Copper Country Historical Marker (wd:Q34857271): park in the United States of America
8. Cow Country Historical Marker (wd:Q49480693): park in Musselshell County, Montana, United States of America
9. Indian Country Historical Marker (wd:Q49504757): park in Garfield County, Montana, United States of America
10. Mining Country Historical Marker (wd:Q49526918): park in Jefferson County, Montana, United States of America

[Assistant]
The entity for "historical country" is wd:Q3024240. Since there is no direct entity for "dissolved country," I will only filter out historical countries (wd:Q3024240) in the query to exclude countries that no longer exist.

I will now refine the SPARQL query accordingly and add optional labels for better interpretability.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 10 (xsd:int) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?author ?authorLabel WHERE {
  wd:Q315296 wdt:P31 wd:Q42240 .
  ?author wdt:P800 wd:Q315296 .
  ?author rdfs:label ?authorLabel
  FILTER ( LANG( ?authorLabel ) = "en" )
}
LIMIT 1

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

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 in Wikidata, and the question is about the author or writer of it. The property "author" or "creator" might be used to find the person who wrote the Erlangen program.

First, I will search for the entity "Erlangen program" in Wikidata.

[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. Now, I will search for properties related to "author" or "creator" for this entity to find who wrote the Erlangen program.

[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 wdtn/wdt/p): 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 the property "author" related to the Erlangen program entity did not return a direct "author" or "creator" property. I will now try searching for the property "author" in general in Wikidata to find the relevant property for authorship.

[Tool]
Top 10 property alternatives:
1. theorized by, also known as author, supported by, suggested by, proposer, proposed by (wd:P8403 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): subject who suggested or proposed this concept or immaterial invention
2. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): author of song lyrics, author
3. author, also known as writer, written by, poet, playwright, maker (wd:P50 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
4. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): notable scientific, artistic or literary work, or other work of significance among subject's works
5. author given names, also known as given name, given names, first name, author first names, author first name (wd:P9687 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): qualifier for string representation of given or secondary sortin...presented in a bibliographic reference file (for example BibTeX), given name
6. used by, also known as armiger, user, played by, of (wd:P1535 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): item or concept that makes use of the subject (use sub-properties when appropriate)
7. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): person, profession, organization or entity that operates the equipment, facility, or service, used by
8. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): maker of this creative work or other object (where no more specific property exists)
9. author last names, also known as author last name, surnames, surname, last names, last name (wd:P9688 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): qualifier to provide string representation of family or primary ...presented in a bibliographic reference file (for example BibTeX), family name
10. object named as, also known as original wording, place name string, printed as, reference wording, [sic] (wd:P1932 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): use as qualifier to indicate how the object's value was given in the source, name

[Assistant]
There are two relevant properties for authorship:
- "author" (wdt:P50) which is the main creator(s) of a written work.
- "theorized by" (wdt:P8403) which can be used for concepts or immaterial inventions.

Since the Erlangen program is a research program on the symmetries of geometry, "theorized by" might be more appropriate. I will try to query the Erlangen program entity with both properties to see which one returns the author.

[Tool] Got no rows and 2 columns

[Tool] Got no rows and 2 columns

[Assistant] Neither "author" (P50) nor "theorized by" (P8403) properties returned any results for the Erlangen program entity. I will now try to find the creator or author by looking for statements or properties related to the Erlangen program entity that might indicate the author. I will list some properties of the Erlangen program entity.

[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 entity do not directly indicate the author. I will now try to find statements with the property "author" (P50) or "theorized by" (P8403) that have the Erlangen program as the object. This might help find the author by reversing the direction of the property.

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Assistant] There are no statements with the Erlangen program as the object for the properties "author" (P50) or "theorized by" (P8403). I will try a different approach by searching for the Erlangen program in the description or label of people to find the author. I will search for people related to the Erlangen program.

[Tool]
Top 10 entity alternatives:
1. Erlangen program (wd:Q315296): research program on the symmetries of geometry
2. Code stylometry, also known as program authorship attribution, source code authorship analysis (wd:Q56275944): application of stylometry to computer code
3. Program test authority (wd:Q7248436): after a construction permit but before a broadcast license
4. Authoritative Recommendations Program (wd:Q119013299): publication published in 2022
5. Authorized Program Analysis Report, also known as APAR (wd:Q48803269): An APAR (Authorized Program Analysis Report) is an IBM designati... to identify situations that could result in potential problems.
6. Microsoft Authorized Refurbisher Program, also known as MAR (wd:Q15835159): program by Microsoft
7. Book and Author Programme (wd:Q131933547)
8. Computer program detects author gender (wd:Q128190724): scholarly article
9. Authoritative Recommendations Program (superseded) (wd:Q66475694): superseded NIOSH program performance one-pager published in 2018
10. Authoritative Recommendations Program (superseded) (wd:Q112236315): superseded publication published in 2021

[Assistant] The search for "Erlangen program author" did not return a direct author entity. I will now try to search for the Erlangen program in relation to mathematicians or authors to find the person who wrote it. I will search for "Erlangen program mathematician" to see if it leads to the author.

[Tool]
Top 10 entity alternatives:
1. Erlangen program (wd:Q315296): research program on the symmetries of geometry
2. mathematician (wd:Q170790): person with an extensive knowledge of mathematics
3. 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
4. Erlangen, also known as Medical Valley (wd:Q3126): city in Bavaria, Germany
5. 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
6. plan, also known as plans, program, programme (wd:Q1371819): outline of a strategy for achievement of an objective
7. programme, also known as program (wd:Q1508646): informational booklet given out before a live event
8. The Program, also known as Icon, Program (wd:Q15615185): 2015 film
9. 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
10. Erlangen, also known as Erlangen station (wd:Q800737): railway halt in the urban district of Erlangen, Middle Franconia, Germany

[Assistant] The search did not directly return the author of the Erlangen program. I will now try to find the author by querying for mathematicians who have a notable work or contribution related to the Erlangen program. I will use the property "notable work" (wdt:P800) to find mathematicians associated with the Erlangen program.

[Tool] Got no rows and 2 columns

[Assistant] No mathematicians have the Erlangen program listed as a notable work. I will try a broader approach by searching for people who have any relation to the Erlangen program using any property. I will query for any entities related to the Erlangen program.

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

[Assistant] The query found Felix Klein (wd:Q76641) as a person related to the Erlangen program. Felix Klein is known as a mathematician. I will now confirm that Felix Klein is the author of the Erlangen program by checking if there is a property linking Felix Klein to the Erlangen program as the author or creator.

[Tool]
Got 1 row and 2 columns:
| property                | propertyLabel |
| ----------------------- | ------------- |
| notable work (wdt:P800) |               |

[Assistant] Felix Klein has the Erlangen program listed as a notable work (wdt:P800). This confirms that Felix Klein wrote the Erlangen program. I will now provide the final SPARQL query and answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies Felix Klein as the author of the Erlangen program by using the property 'notable work' (wdt:P800) linking Felix Klein to the Erlangen program (wd:Q315296). The query returns the author's identifier and English label, which is appropriate and follows the guidelines. The answer is correct and complete.


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

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

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]
From the example, we see that to find female entities, we use the property "sex or gender" (wdt:P21) with the value "female" (wd:Q6581072). Now, I need to identify the entity or class for "fictional swordfighter" or "fictional character who is a swordfighter" to count how many such female characters exist.

Next, I will search for the entity "fictional swordfighter" or related terms like "fictional character" and "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]
I found relevant entities: "swordfighter" (wd:Q11397897) and "fictional character" (wd:Q95074). To find fictional swordfighters, I need to find entities that are instances of or subclasses of fictional characters and also swordfighters. Then, I will filter for female gender.

Next, I will search for properties that relate an entity to being a fictional character or swordfighter. I want to see if there is a property that indicates the occupation or role of a fictional character.

[Tool]
Top 10 property alternatives:
1. personality trait of fictional character, also known as personality trait, personality trait of fictitious character, personal quality of fictional character, fictitious character personality trait, personal quality of fictitious character (wd:P9652 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): particular personality trait which applies to this fictional character
2. from narrative universe, also known as from narrative, in continuity, from universe, in cycle, in world of (wd:P1080 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): subject's fictional entity is in the object narrative. See also P1441 (present in work) and P1445 (fictional universe described in), part of
3. character role, also known as role, plays, performer of, as, acting role (wd:P453 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
4. name of the character role, also known as character named as, role named as, role name, name of the role, name of the character (wd:P4633 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): name by which a character role is recorded in a database or ment...ably a specific performance of a theatrical production of a play, name
5. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
6. takes place in fictional universe, also known as universe featured, described fictional universe, universe described, set in fictional universe, fictional universe described (wd:P1434 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): the subject is a work describing a fictional universe, i.e. whose plot occurs in this universe
7. characters, also known as appears in this work (wd:P674 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): characters which appear in this item (like plays, operas, operettas, books, comics, films, TV series, video games)
8. fictional or mythical analog of, also known as fictionalisation of, mythical analog of, fictional version of, fictionalization of, fictional analog of (wd:P1074 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): used to link an entity or class of entities appearing in a creat...with the analogous entity or class of entities in the real world, inspired by
9. character type, also known as -dere, stock character, stereotype, dere, character stereotype (wd:P9071 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): generic character type that this fictional character represents, manifestation of
10. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject

[Assistant]
There is no direct property for "occupation" or "role" of a fictional character that explicitly states "swordfighter." However, "occupation" (wdt:P106) is a common property used for roles or jobs, including fictional characters. I will check if "swordfighter" (wd:Q11397897) is used as an occupation for any entities.

Next, I will query for entities with occupation swordfighter and gender female to count how many fictional female swordfighters exist. I will also check if these entities are instances of fictional characters.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies fictional female swordfighters by checking for occupation as swordfighter, gender as female, and instance as fictional character. The query returns the count of distinct such entities, which matches the answer given (6). The query follows the rules by returning only the count and uses appropriate properties and entities. No further refinement is necessary.


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

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 when an entity was built or started. I will now search for the entity "Hollywood Walk of Fame" in Wikidata to get its identifier.

[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" corresponds to wd:Q71719. Next, I will check the properties related to the inception or opening date of this entity. I will search for properties related to "inception" or "opening" for this entity.

[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. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p): label for the items in their official language  or their original language, name
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. 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
5. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
6. located on street, also known as on street, street address, street, square, road (wd:P669 as p/wdt): street, road, or square, where the item is located. To add the n...perty P6375 "street address", if there is no item for the street, location, part of
7. IMDb ID, also known as IMDb identifier, Internet Movie Database identifier (wd:P345 as p/wdt): identifier for the IMDb (with prefix 'tt', 'nm', 'co', 'ev', 'ch' or 'ni')
8. 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
9. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
10. ground level 360 degree view URL, also known as Mapillary, virtual tour URL, tour URL, street view URL, Mapy.CZ (wd:P5282 as p/wdt): URL to access a service that allows to visually navigate through images at ground level in the proximity of the item, URL

No other items found

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

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

[Assistant] The Hollywood Walk of Fame officially opened in the year 1960. I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the official opening date (wdt:P1619) of the Hollywood Walk of Fame (wd:Q71719) from Wikidata. The result is the year 1960, which matches the provided answer. The query and answer are accurate and complete for the user's question.


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

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, we see that the property for official language is wdt:P37 and the entity for Pakistan is wd:Q843. We can use these to count the number of official languages of Pakistan. I will now write a SPARQL query to count the official languages of Pakistan.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of official languages of Pakistan using the property wdt:P37. The result matches the answer given, which states Pakistan has 2 official languages according to Wikidata. The query is well-formed, returns the correct count, and adheres to the guidelines. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
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

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 the creator of a work is wdt:P170. Now I need to find the Wikidata entity for "Unbreakable Kimmy Schmidt" and then query its creator using the property wdt:P170. I will first 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. Now I will query 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

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the creators of 'Unbreakable Kimmy Schmidt' using the property P170 (creator). It returns both the identifiers and English labels of Tina Fey and Robert Carlock, which matches the known information about the show's creators. The query is well-formed, uses appropriate properties, and the answer is complete and accurate. No further refinement is necessary.


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

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, we see that the property "director" (wdt:P57) is used to link a movie to its director. Akira Kurosawa is identified by wd:Q8006. To answer the question "How many movies were directed by Akira Kurosawa?", we can count the distinct movies where Akira Kurosawa is the director.

I will now write and execute a SPARQL query to count the number of movies directed by Akira Kurosawa.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of distinct movies directed by Akira Kurosawa using the property wdt:P57 (director) and the entity wd:Q8006 (Akira Kurosawa). The query returns the count as 32, which matches the provided answer. The query is simple, efficient, and follows the rules for SPARQL queries. No further refinement is needed.