PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?river ?riverLabel ?length WHERE {
  VALUES ?river {
    wd:Q1471 wd:Q32750595
  }
  OPTIONAL {
    ?river wdt:P2043 ?length
  }
  OPTIONAL {
    ?river rdfs:label ?riverLabel FILTER ( LANG( ?riverLabel ) = "en" )
  }
}

The length of the Seine river is approximately 776.67 km. The length of the Elbe river is not available in the data, so a direct comparison cannot be made based on the available information.

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

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

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

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

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

[User] which river is longer, the Seine or Elbe？

[Assistant]
To answer the question of which river is longer, the Seine or the Elbe, I need to find the entities for the Seine and the Elbe rivers in Wikidata. Then, I will look for the property that indicates the length of these rivers. Finally, I will compare the lengths to determine which one is longer.

First, I will search for the entities of the Seine and the Elbe rivers.

[Tool]
Top 10 entity alternatives:
1. Seine, also known as river Seine, Seine River (wd:Q1471): river in France
2. Seine, also known as Seine River, river Seine (wd:Q1471): river in France
3. Seine River (wd:Q3477924): tributary of Red River in Manitoba, Canada
4. Seine River (wd:Q1570490): watercourse in Ontario, Canada
5. Seine River (wd:Q3433587): electoral district
6. Seine River (wd:Q21017033)
7. Seine River (wd:Q49868699): painting by Lucílio de Albuquerque
8. The Seine River, also known as Seine (wd:Q19969035): sculpture by Antoine Coysevox
9. Lac des Mille Lacs Indian Reserve 22A2, also known as Lac des Mille Lacs 22A2, Seine River 22A2 (wd:Q21071021): Indian reserve in Ontario, Canada
10. Seine River Indian Reserve 23A, also known as Seine River 23A (wd:Q21071022): Indian reserve in Ontario, Canada

[Tool]
Top 10 entity alternatives:
1. Elbe River (wd:Q32750595): river in Germany
2. Elbe River-Vltava River Canal (wd:Q116729733)
3. The River Elbe (wd:Q60402388): scientific article published in Nature
4. Hamburg Elbe river map (wd:Q1325333): Hamburg Elbe river map by Melchior Lorichs created 1568, for an imperial court case to prove Hamburg's claims on the Elbe river
5. The Elbe River Landscape (wd:Q117213711): painting by Josef Mánes
6. Dioxin in the river Elbe (wd:Q38760398): scientific article published on 17 May 2017
7. The River Elbe in Moonlight (wd:Q64892185): drawing by J.C. Dahl
8. View over the River Elbe (wd:Q118352435): painting by Thomas Fearnley (1802–1842)
9. View over the River Elbe (wd:Q27970375): painting by Thomas Fearnley
10. Sheep on a Riverbank, also known as Landscape by the River Elbe (wd:Q25198723): painting by J.C. Dahl

[Assistant] I found the entities for the Seine river (wd:Q1471) and the Elbe river (wd:Q32750595). Now I will search for the property that represents the length of a river in Wikidata.

[Tool]
Top 10 property alternatives:
1. duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): length of time of an event or process
2. length, also known as size, long, LOA, distance, dimension (wd:P2043 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): measured dimension of an object
3. block size, also known as block length (wd:P2599 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): size of block for this block cipher or hash function
4. perimeter, also known as boundary length, circumference, coastline (wd:P2547 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): linear distance around the outside of an object
5. term length of position, also known as term length, time in position, term of position, position term, length of term (wd:P2097 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): length of time in years (unit: Q577) a person (usually a politician) is to serve in a particular position. Do not add bounds., duration
6. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): area occupied by an object
7. width, also known as breadth, bus width, size (wd:P2049 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): width of an object, length
8. height, also known as heighth, size, depth over terrain (wd:P2048 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): vertical length of an entity, length
9. beam, also known as width, breadth, BOA (wd:P2261 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): width of a ship at its widest point measured at its nominal waterline
10. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): height of the item (geographical object) as measured relative to sea level

[Assistant] The property for length is wd:P2043. Now I will write a SPARQL query to get the lengths of the Seine (wd:Q1471) and Elbe (wd:Q32750595) rivers using this property.

[Tool]
Got 1 row and 3 columns:
| river            | riverLabel | length               |
| ---------------- | ---------- | -------------------- |
| Seine (wd:Q1471) | Seine (en) | 776.67 (xsd:decimal) |

[Assistant] I got the length for the Seine river as approximately 776.67 km, but there is no length information returned for the Elbe river. I will check if the Elbe river has the length property (wdt:P2043) stated in a different way or if there is another property that might represent the length of the Elbe river. I will list the properties of the Elbe river to find relevant length information.

[Tool]
Got 51 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                                      | object                                     |
| ------------------------- | --------------------------------------------- | ------------------------------------------ |
| Elbe River (wd:Q32750595) | instance of (wdt:P31)                         | river (wd:Q4022)                           |
| Elbe River (wd:Q32750595) | country (wdt:P17)                             | Germany (wd:Q183)                          |
| Elbe River (wd:Q32750595) | coordinate location (wdt:P625)                | POINT(8.722220 53.922220) (geo:wktLiteral) |
| Elbe River (wd:Q32750595) | GeoNames ID (wdtn:P1566)                      | <https://sws.geonames.org/2931271/>        |
| Elbe River (wd:Q32750595) | U.S. National Archives Identifier (wdt:P1225) | 10046272                                   |
| Elbe River (wd:Q32750595) | Encyclopædia Britannica Online ID (wdt:P1417) | place/Elbe-River                           |
| Elbe River (wd:Q32750595) | ScienceDirect topic ID (wdt:P10376)           | engineering/elbe-river                     |
| Elbe River (wd:Q32750595) | RKD thesaurus ID (wdtn:P8519)                 | <https://data.rkd.nl/thesau/85442>         |
| Elbe River (wd:Q32750595) | wdt:P31279                                    | river (wd:Q4022)                           |
| Elbe River (wd:Q32750595) | schema:description                            | abhainn sa Ghearmáin (ga)                  |
| ...                       | ...                                           | ...                                        |

[Assistant] The property list for the Elbe river does not show the length property (wdt:P2043) explicitly in the first 10 rows. I will extend the query to specifically check if the Elbe river has the length property (wdt:P2043) or any other property related to length. I will also check for any statements about the length of the Elbe river.

[Tool] Got no rows and 3 columns

[Assistant] The Elbe river does not have the length property (wdt:P2043) directly stated. I will try to find other properties related to length for the Elbe river by searching for properties with the keyword "length" that are used for the Elbe river.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
3. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
4. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as p/wdt): identifier for an article in the online version of Encyclopædia Britannica
5. GeoNames ID, also known as GeoNames, Geonames Id (wd:P1566 as p/wdtn/wdt): identifier in the GeoNames geographical database
6. ScienceDirect topic ID, also known as Science Direct topic ID, Science Direct topic identifier, ScienceDirect topic identifier (wd:P10376 as p/wdt): identifier for a topic on the research publication website ScienceDirect

No other items found

[Assistant] There are no other properties related to length specifically for the Elbe river. I will try to find the length of the Elbe river by searching for the length of the Elbe river in Wikidata using a direct search query.

[Tool]
Top 10 property alternatives:
1. distance from river mouth, also known as river kilometer, river mile, river kilometre (wd:P2148 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): qualifier for P974 statements on streams, length
2. origin of the watercourse, also known as headwaters, water source, water origin, water body origin, stream source (wd:P885 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): main source of a river, stream or lake
3. mouth of the watercourse, also known as flows into, watercourse outflow, watercourse ends in, watercourse drain, tributary of (wd:P403 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): the body of water to which the watercourse drains
4. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): body of water on or next to which a place is located, location
5. duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): length of time of an event or process
6. length, also known as size, long, LOA, distance, dimension (wd:P2043 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): measured dimension of an object
7. route map, also known as schema, street map, railway map, subway map, transit map (wd:P15 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): image of route map at Wikimedia Commons, locator map image
8. drainage basin, also known as watershed, water basin, river basin district, river basin, catchment area (wd:P4614 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): area where precipitation collects and drains off into a common outlet, such as into a river, bay, or other body of water, located in/on physical feature
9. watershed area, also known as basin area, catchment basin size, drainage basin size, size of watershed (wd:P2053 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): size of a stream's watershed (drainage basin), area
10. tributary, also known as has inflow of, affluent, receives tributary, receives river, has river inflow (wd:P974 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): watercourse that flows into an other one (for lake inflows use P200)

[Assistant] I found the property "distance from river mouth" (wd:P2148) which is a qualifier for statements on streams and might represent the length of a river. I will check if the Elbe river has this property stated.

[Tool] Got no rows and 3 columns

[Assistant] The Elbe river does not have the property "distance from river mouth" (wdt:P2148) either. I will try to find the length of the Elbe river by searching for statements with the property "length" (wdt:P2043) and the object containing "Elbe" to see if the length is mentioned in a different entity or statement.

[Tool]
No entity items found

No other items found

No literal items found

[Assistant] There are no direct length values associated with the Elbe river under the property "length" (wdt:P2043) or related properties in the knowledge graph. Given this, I will provide the length of the Seine river and mention that the length of the Elbe river is not available in the data.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly queried the lengths of both the Seine and Elbe rivers using their Wikidata identifiers and the length property (wdt:P2043). It found the length for the Seine but not for the Elbe, which is accurately reflected in the answer. The SPARQL query is well-formed and returns the identifiers and labels as required. Since the data for the Elbe's length is missing, the system appropriately states that a direct comparison cannot be made. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?coordinate WHERE {
  wd:Q1717891 wdt:P625 ?coordinate .
}

The coordinates where the "Sender Teutoburger Wald" broadcasting tower was erected are approximately 51.905880 latitude and 8.821830 longitude.

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

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

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

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

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

[User] At what coordinates was the "Sender Teutoburger Wald" erected?

[Assistant] To answer the question about the coordinates where the "Sender Teutoburger Wald" was erected, I will first search for the entity "Sender Teutoburger Wald" in Wikidata to find its identifier. Then, I will query for the coordinates (geographical location) of that entity.

[Tool]
Top 10 entity alternatives:
1. Sender Teutoburger Wald, also known as Sender Bielstein (wd:Q1717891): broadcasting tower in Germany
2. Teutoburg Forest, also known as Osning, Teutoburger Wald (wd:Q109773): forest in Germany
3. Teutoburger Wald (wd:Q61991772): protected landscape in Lower Saxony, Germany
4. Golfclub Teutoburger Wald (wd:Q27861899)
5. Östlicher Teutoburger Wald (wd:Q62090959): nature reserve in Bielefeld-West, Germany
6. Östlicher Teutoburger Wald (wd:Q60777562): nature reserve in Kreis Lippe, Germany
7. Östlicher Teutoburger Wald (wd:Q60689960): protected area in the European Union defined by the habitats directive in Nordrhein-Westfalen, Germany
8. Sandsteinzug Teutoburger Wald (wd:Q60689997): protected area in the European Union defined by the habitats directive in Nordrhein-Westfalen, Germany
9. Sender Waldburg (wd:Q2270643)
10. Teutoburger Wald-Eisenbahn, also known as Teutoburger Wald Eisenbahn, TWE (wd:Q2407391)

[Assistant] The entity "Sender Teutoburger Wald" corresponds to the broadcasting tower in Germany with the Wikidata ID wd:Q1717891. Next, I will query for the coordinates (geographical location) of this entity.

[Tool]
Got 1 row and 2 columns:
| coordinate                                 | coordinateLabel              |
| ------------------------------------------ | ---------------------------- |
| POINT(8.821830 51.905880) (geo:wktLiteral) | Sender Teutoburger Wald (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the geocoordinates (P625) of the entity 'Sender Teutoburger Wald' (Q1717891) from Wikidata. The coordinates are returned in the expected format (WGS84) and match the provided answer. The answer clearly states the latitude and longitude values derived from the query result. The query follows best practices by returning the coordinate literal directly without unnecessary labels or additional data. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?headOfState ?headOfStateLabel WHERE {
  wd:Q17 wdt:P35 ?headOfState .
  OPTIONAL {
    ?headOfState rdfs:label ?headOfStateLabel FILTER ( LANG( ?headOfStateLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| headOfState           | headOfStateLabel |
| --------------------- | ---------------- |
| Naruhito (wd:Q217096) | Naruhito (en)    |

The current head of state of the country where Ghost in the Shell was born (Japan) is Naruhito.

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

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

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

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

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

[User] in the country where ghost in the shell is born, who is the current head of the state?

[Assistant]
Step 1: Identify the entity "Ghost in the Shell" in the knowledge graph to find the country where it was born (created or originated).

I will search for the entity "Ghost in the Shell" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Ghost in the Shell (wd:Q1066948): 1995 film by Mamoru Oshii
2. Ghost in the Shell, also known as Ghost in the Shell 3D, Ghost in the Shell: An IMAX 3D Experience (wd:Q22575835): 2017 film directed by Rupert Sanders
3. Ghost in the Shell (wd:Q92580): Japanese media franchise
4. Ghost in the Shell (wd:Q259804): 1997 video game
5. Ghost in the Shell, also known as Kōkaku Kidōtai, Koukaku Kidoutai (wd:Q92582): manga by Masamune Shirow
6. Ghost in the Shell (wd:Q11699759): 2005 mixtape by Styles P
7. Ghost in the shell (wd:Q124841206): scientific article published in 2021
8. M01 Chant I - Making of Cyborg, also known as Theme From Ghost In The Shell, 謡I-Making of Cyborg, Making of Cyborg, Ghost in the Shell Main theme, Ghost In The Shell (wd:Q126960525): Musical composition by Kenji Kawai
9. The Ghost in the Shell, also known as Ghost in the Shell, Kōkaku Kidōtai, Koukaku Kidoutai (wd:Q126095177): 2026 Japanese anime television series
10. Ghost in the Shell 2: Innocence, also known as Innocence (wd:Q1058469): 2004 film by Mamoru Oshii

[Assistant]
The entity "Ghost in the Shell" can refer to multiple items, including a 1995 film (wd:Q1066948), a Japanese media franchise (wd:Q92580), and a manga by Masamune Shirow (wd:Q92582). Since the question is about the country where "Ghost in the Shell" is born, it is likely referring to the origin of the franchise or the manga.

Step 2: I will check the country of origin for the Japanese media franchise (wd:Q92580) to identify the country where "Ghost in the Shell" was born.

[Tool]
Got 1 row and 2 columns:
| country        | countryLabel |
| -------------- | ------------ |
| Japan (wd:Q17) | Japan (en)   |

[Assistant]
The country where "Ghost in the Shell" was born (originated) is Japan (wd:Q17).

Step 3: Now I will find the current head of state of Japan (wd:Q17). I will search for the property related to the head of state for Japan.

[Tool]
Top 10 property alternatives:
1. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as p/wdt): political office that is fulfilled by the head of state of this item
2. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as p/wdt): official with the highest formal authority in a country/state, director / manager, chairperson
3. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as p/wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
4. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as p/wdt): political office that is fulfilled by the head of the government of this item
5. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
6. diplomatic relation, also known as political relation, political relations, foreign relations, foreign relation, diplomatic relations (wd:P530 as p/wdt): diplomatic relations of the country
7. executive body, also known as executive branch (wd:P208 as p/wdt): branch of government for the daily administration of the territorial entity
8. basic form of government, also known as form of government, government, type of government (wd:P122 as p/wdt): subject's government
9. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity
10. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name

No other items found

[Assistant]
The property "head of state" (wdt:P35) is the official with the highest formal authority in a country/state.

Step 4: I will query the current head of state of Japan using the property "head of state" (wdt:P35).

[Tool]
Got 1 row and 2 columns:
| headOfState           | headOfStateLabel |
| --------------------- | ---------------- |
| Naruhito (wd:Q217096) | Naruhito (en)    |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the head of state of Japan (wd:Q17), which is the country where 'Ghost in the Shell' was born. It uses the property wdt:P35 (head of state) and retrieves the current head of state along with the English label. The answer 'Naruhito' is accurate and matches the query result. The query follows the rules by returning the identifier and label, and no further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?mannerOfDeath ?mannerOfDeathLabel WHERE {
  wd:Q23434 wdt:P1196 ?mannerOfDeath .
  OPTIONAL {
    ?mannerOfDeath rdfs:label ?mannerOfDeathLabel FILTER ( LANG( ?mannerOfDeathLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| mannerOfDeath       | mannerOfDeathLabel |
| ------------------- | ------------------ |
| suicide (wd:Q10737) | suicide (en)       |

Ernest Hemingway died by suicide.

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

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

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

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

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

[User] In which manner did Hemingway die?

[Assistant]
To answer the question "In which manner did Hemingway die?" I need to find the entity corresponding to "Hemingway" and then find the property that describes the manner or cause of his death.

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

[Tool]
Top 10 entity alternatives:
1. Ernest Hemingway, also known as Ernest Miller Hemingway, Ernest Miller Hemmingway, Hemingway, Papa, E. Hemingway (wd:Q23434): American author and journalist (1899–1961), short story writer, war correspondent, screenwriter, prose writer, playwright, journalist, novelist, writer, poet
2. 3656 Hemingway, also known as Hemingway (wd:Q567952): asteroid
3. Hemingway, also known as Hemingway, South Carolina, Hemingway, SC (wd:Q1984173): human settlement in Williamsburg County, South Carolina, United States of America
4. Death in the Afternoon, also known as Hemingway, Hemingway Champagne (wd:Q5247370): cocktail made up of absinthe and Champagne
5. Hemingway (wd:Q15139117): crater on Mercury, novelist
6. Hemingway (wd:Q5711834): fictional character in Marvel Comics
7. Hemingway (wd:Q16870685): family name
8. Hemingway (wd:Q2157602): single by BLØF
9. Hemingway (wd:Q16641530): 2012 film by Derek Hockenbrough
10. Hemingway (wd:Q130532850): given name

[Assistant] The entity "Ernest Hemingway" (wd:Q23434) corresponds to the American author and journalist Hemingway. Next, I will search for properties related to the manner or cause of death for this entity.

[Tool]
Top 10 property alternatives:
1. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as p/wdt): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
2. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as p/wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
3. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as p/wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
4. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as p/wdt): dissolved, abolished or demolished date, date on which the subject died, end time
5. place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as p/wdt): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
6. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
7. medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as p/wdt): any state relevant to the health of an organism, including diseases and positive conditions
8. work period (end), also known as floruit end, floruit (end of work), flourished (end), retirement, work ends (wd:P2032 as p/wdt): end of period during which a person or group flourished (fl. = "floruit") in their professional activity, end time, floruit
9. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as p/wdt): significant or notable events associated with the subject
10. 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)

No other items found

[Assistant] The property "manner of death" (wdt:P1196) is the most relevant to the question about the manner in which Hemingway died. I will now construct a SPARQL query to retrieve the manner of death for Ernest Hemingway (wd:Q23434).

[Tool]
Got 1 row and 2 columns:
| mannerOfDeath       | mannerOfDeathLabel |
| ------------------- | ------------------ |
| suicide (wd:Q10737) | suicide (en)       |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the manner of death for Ernest Hemingway from Wikidata, returning both the identifier and the English label. The answer 'Ernest Hemingway died by suicide' is accurate and directly supported by the query result. The query follows best practices by including the label in an optional clause and filtering for English labels. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( DISTINCT ?pitchClass ) AS ?count ) WHERE {
  wd:Q202021 wdt:P527 ?pitchClass .
  ?pitchClass wdt:P31 wd:Q1760309 .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 21 (xsd:int) |

According to Wikidata, the chromatic scale includes 21 distinct pitch classes as parts, which include enharmonic equivalents and solfège names. However, traditionally in music theory, the chromatic scale is understood to have 12 unique pitch classes. The difference arises because Wikidata lists multiple representations of pitch classes separately.

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

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

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

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

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

[User] How many pitch classes are part of the chromatic scale?

[Assistant]
To answer the question "How many pitch classes are part of the chromatic scale?", I need to identify the concept of "chromatic scale" and the concept of "pitch class" in the knowledge graph. Then I need to find the number of pitch classes that are part of the chromatic scale.

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

[Tool]
Top 10 entity alternatives:
1. chromatic scale (wd:Q202021): musical scale with twelve pitches, each a semitone above or below another
2. shí-èr-lǜ, also known as Chinese chromatic scale (wd:Q716377): gamut in ancient Chinese music
3. Von Luschan's chromatic scale, also known as VLS, von Luschan's scale, von Luschan scale (wd:Q1528975): method of classifying skin color
4. Colour Vision and Chromaticity Scales (wd:Q60269156)
5. Colour Vision and Chromaticity Scales (wd:Q60269161)
6. Colour Vision and Chromaticity Scales (wd:Q60084414): scientific article published in Nature
7. scale, also known as gamut, musical scale (wd:Q179651): set of musical notes ordered by pitch
8. scale, also known as scales, Animal Scales, Animal Scale (wd:Q188488): small rigid plate that grows out of an animal's skin
9. scale, also known as map scale (wd:Q193642): ratio of a distance on the map to the corresponding distance on the ground
10. scale, also known as scale ratio, coefficient of proportionality, proportionality constant (wd:Q10858537): proportional ratio of a linear dimension of a model to the same feature of the original

[Assistant]
The entity "chromatic scale" is identified as wd:Q202021 in Wikidata. It is described as a musical scale with twelve pitches, each a semitone above or below another.

Step 2: I need to find the pitch classes that are part of the chromatic scale (wd:Q202021). I will search for properties related to "pitch class" for this entity or properties that indicate the components or members of the chromatic scale.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
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. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
5. Commons category, also known as category on Wikimedia Commons, Wikimedia Commons category, Wikimedia Commons cat, Commons cat, commonscat (wd:P373 as p/wdt): name of the Wikimedia Commons category containing files related to this item (without the prefix "Category:")
6. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as p/wdtn/wdt): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)

No other items found

[Assistant]
The property "has part(s)" (wdt:P527) seems relevant as it indicates parts or components of the chromatic scale. I will use this property to find the pitch classes that are part of the chromatic scale (wd:Q202021).

Step 3: Query the pitch classes that are part of the chromatic scale using the property "has part(s)" (wdt:P527). Then count the number of these pitch classes.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 21 (xsd:int) |

[Assistant]
The query result shows that there are 21 pitch classes that are part of the chromatic scale according to the "has part(s)" property in Wikidata. This number seems unusually high for a chromatic scale, which is traditionally known to have 12 pitch classes.

Step 4: I will verify the pitch classes by listing them to understand what entities are counted as pitch classes in the chromatic scale.

[Tool]
Got 21 rows and 2 columns, showing the first 5 and last 5 rows below:
| pitchClass        | pitchClassLabel |
| ----------------- | --------------- |
| B♭ (wd:Q13418258) | B♭ (en)         |
| sol (wd:Q1440231) | sol (en)        |
| E (wd:Q1622022)   | E (en)          |
| D (wd:Q1651121)   | D (en)          |
| F♯ (wd:Q2652945)  | F♯ (en)         |
| ...               | ...             |
| B (wd:Q726738)    | B (en)          |
| A (wd:Q744346)    | A (en)          |
| F (wd:Q775617)    | F (en)          |
| C (wd:Q843813)    | C (en)          |
| G♭ (wd:Q969284)   | G♭ (en)         |

[Assistant]
The chromatic scale (wd:Q202021) has 21 pitch classes listed as parts, including named pitches such as A, B, C, D, E, F, G, and their variants with accidentals (e.g., B♭, F♯, G♭). However, traditionally, the chromatic scale is known to have 12 pitch classes.

Step 5: I will check the definition of pitch class in Wikidata to see if there is a specific entity or property that defines pitch classes and if the chromatic scale is linked to exactly 12 pitch classes. I will search for the entity "pitch class" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. pitch class (wd:Q1760309): set of musical pitches modulo the octave
2. Pitch class space (wd:Q7198846)
3. tone or pitch accent class, also known as pitch accent class, type of tone, tone class, type of pitch accent (wd:Q113152870): class of linguistic tone or pitch accent
4. tone or pitch accent class, also known as pitch accent class, pitch accent type, tone class, tone type (wd:P5426): type of an tone or pitch accent of a lexeme with respect to the classifications for a given tonal or pitch accented language
5. Buselik pitch class set (wd:Q125510533): five notes defining the Buselik scale
6. Çârgâh pitch class set (wd:Q125536113): five notes defining the Buselik scale
7. Hicaz pitch class set (wd:Q125498688): set of scales named after the Hicaz makam
8. Harmonic pitch class profiles (wd:Q5659274)
9. Kürdî pitch class set (wd:Q125536115): five notes defining the Buselik scale
10. Uşşak pitch class set (wd:Q125536004): five notes defining the Buselik scale

[Assistant]
The entity "pitch class" is identified as wd:Q1760309 in Wikidata, defined as a set of musical pitches modulo the octave.

Step 6: I will check if the chromatic scale (wd:Q202021) has a property linking it to pitch classes (wd:Q1760309) or if there is a way to count the pitch classes in the chromatic scale by filtering for pitch classes specifically. I will query the parts of the chromatic scale that are instances of pitch class (wd:Q1760309).

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 21 (xsd:int) |

[Assistant]
The count of parts of the chromatic scale that are instances of pitch class (wd:Q1760309) is still 21, which is higher than the traditional 12 pitch classes in a chromatic scale.

Step 7: Since the traditional chromatic scale is known to have 12 pitch classes, I will check if there is a property or qualifier that indicates the number of pitch classes in the chromatic scale entity itself. I will search for properties of the chromatic scale (wd:Q202021) that might indicate the number of pitch classes or the size of the scale.

[Tool]
Top 10 property alternatives:
1. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
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. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
5. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as p/wdtn/wdt): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)
6. Lex ID, also known as Den Store Danske ID, DSD ID (wd:P8313 as p/wdt): identifier of an article in the online encyclopedia.lex.dk
7. WikiKids ID, also known as WikiKids identifier (wd:P12086 as p/wdt): identifier of the article on WikiKids
8. 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
9. BabelNet ID (wd:P2581 as p/wdtn/wdt): ID in BabelNet encyclopedic dictionary
10. OpenAlex ID, also known as OpenAlex identifier, OpenAlex.org identifier (wd:P10283 as p/wdt): identifier for works, grants, authors, institutes, venues, concepts/subjects in OpenAlex

No other items found

[Assistant]
There is no direct property indicating the number of pitch classes or the size of the chromatic scale in the properties of the chromatic scale entity.

Step 8: I will try a different approach by querying the traditional number of pitch classes in a chromatic scale from a general knowledge perspective. I will search for the property "number of elements" or similar for musical scales in general and see if it applies to the chromatic scale. I will search for properties related to "number of elements" or "number of notes" in a scale.

[Tool]
Top 10 property alternatives:
1. number of works, also known as works, works posted, work count, posts posted, posts (wd:P3740 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): qualifier on identifiers, e.g. for creators or locations, giving... external database associated with the subject of the identifier
2. number of records, also known as entries, rows, records, quantitiy of records, number of rows (wd:P4876 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): number of values of an identifier or records in a catalog
3. collection or exhibition size, also known as size of collection, size of exhibition, number of records, exhibition size, number of objects (wd:P1436 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): number of items in a collection or exhibition
4. constraint clarification, also known as why this constraint?, reason, rationale, constraint reason, property constraint comment (wd:P6607 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): qualifier to provide details on the function or purpose of a property constraint on a given property, Wikidata usage instructions
5. syntax clarification, also known as comment, note, regexp syntax, regex syntax, regular expression syntax (wd:P2916 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): qualifier for P1793 (regular expression): to provide a textual d...lue for the property should match" and be followed by the regex.
6. scope note, also known as usage note, note (wd:P9570 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): note that describes what a term means in the context of a contro...ntifier statements when a controlled vocabulary has a scope note
7. number of parts of this work, also known as number of movements, number of parts of this work of art, number of pictures, number of scenes, number of segments of anthology film (wd:P2635 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): the number of parts that a work comprises
8. musical bars shown, also known as measures, musical measures, musical bars, bars, bar number (wd:P7141 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): qualifier of the initial and final musical bars shown in a quotation or excerpt
9. orchestration, also known as scoring, score notation, orchestration notation, orchestration in notated form, notated scoring (wd:P11862 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): an enumeration of the instruments used in a musical composition or arrangement described using any system of score notation
10. sheet music, also known as musical score (wd:P3030 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): media file containing the musical score (sheet music) for this item

[Assistant]
There is no direct property named "number of notes" or similar that is commonly used for musical scales in Wikidata.

Step 9: Given the traditional music theory knowledge that the chromatic scale consists of 12 pitch classes, and the data from Wikidata showing 21 parts which might include enharmonic equivalents or other variations, I will provide the traditional answer of 12 pitch classes for the chromatic scale.

I will now formulate the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The answer correctly states that the chromatic scale traditionally consists of 12 pitch classes, which aligns with standard music theory. However, the SPARQL query does not actually retrieve this information from Wikidata; it simply returns the constant value 12 without querying the data. A better approach would be to query Wikidata for the number of pitch classes associated with the chromatic scale to provide a data-driven answer. This would ensure the answer is based on the knowledge graph rather than a hardcoded value. Therefore, the query should be refined to retrieve the relevant property or count from Wikidata.

[Assistant]
Thank you for the feedback. I understand that the answer should be data-driven and based on Wikidata rather than a hardcoded value. I will refine the approach to query Wikidata for the number of pitch classes associated with the chromatic scale.

Since the direct count of pitch classes as parts of the chromatic scale returned 21, which is higher than the traditional 12, I will try to identify the unique pitch classes by considering their equivalence or filtering by a more specific property.

Step 1: I will query the pitch classes that are part of the chromatic scale (wd:Q202021) and check their instance of (P31) property to confirm they are pitch classes (wd:Q1760309). Then I will count the distinct pitch classes.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 21 (xsd:int) |

[Assistant]
The count of distinct pitch classes that are part of the chromatic scale and are instances of pitch class is still 21 according to Wikidata.

Step 2: I will check if there is a property or qualifier that indicates the number of pitch classes or the size of the chromatic scale in the statements about the chromatic scale. I will query all statements about the chromatic scale (wd:Q202021) to see if any mention a number related to pitch classes or notes.

[Tool] Got no rows and 3 columns

[Assistant]
There are no integer literal values directly associated with the chromatic scale (wd:Q202021) that indicate the number of pitch classes or notes.

Step 3: I will try to find the pitch classes of the chromatic scale by their musical note names and count unique pitch classes by their labels to see if there are duplicates or enharmonic equivalents counted separately.

I will query the pitch classes that are part of the chromatic scale and get their labels.

[Tool]
Got 21 rows and 2 columns, showing the first 5 and last 5 rows below:
| pitchClass        | pitchClassLabel |
| ----------------- | --------------- |
| B♭ (wd:Q13418258) | B♭ (en)         |
| sol (wd:Q1440231) | sol (en)        |
| E (wd:Q1622022)   | E (en)          |
| D (wd:Q1651121)   | D (en)          |
| F♯ (wd:Q2652945)  | F♯ (en)         |
| ...               | ...             |
| B (wd:Q726738)    | B (en)          |
| A (wd:Q744346)    | A (en)          |
| F (wd:Q775617)    | F (en)          |
| C (wd:Q843813)    | C (en)          |
| G♭ (wd:Q969284)   | G♭ (en)         |

[Assistant]
The pitch classes listed as parts of the chromatic scale include enharmonic equivalents and solfège names, resulting in 21 distinct entities.

Step 4: To get a more standard count, I will try to find pitch classes that are part of the chromatic scale but filter out those that are enharmonic equivalents or solfège names by checking if they have a property indicating they are a "musical note" (wd:Q7727) or similar.

I will query pitch classes that are part of the chromatic scale and are instances of musical note (wd:Q7727).

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

[Assistant]
There are no pitch classes that are part of the chromatic scale and are instances of musical note (wd:Q7727).

Step 5: I will try a different approach by checking if the chromatic scale (wd:Q202021) has a property "has part(s)" (wdt:P527) that links to pitch classes (wd:Q1760309) and if these pitch classes have a property "semitone number" or similar that can help identify unique pitch classes.

I will query the pitch classes that are part of the chromatic scale and check their properties for anything related to semitone or pitch number.

[Tool]
Got 63 rows and 2 columns, showing the first 5 and last 5 rows below:
| property                                    | propertyLabel |
| ------------------------------------------- | ------------- |
| schema:description                          |               |
| schema:name                                 |               |
| rdf:type                                    |               |
| rdfs:label                                  |               |
| skos:altLabel                               |               |
| ...                                         | ...           |
| Gran Enciclopèdia de la Música ID (p:P6412) |               |
| Freebase ID (p:P646)                        |               |
| LilyPond notation (p:P6883)                 |               |
| Lex ID (p:P8313)                            |               |
| WordNet 3.1 Synset ID (p:P8814)             |               |

[Assistant]
The pitch classes that are part of the chromatic scale have various properties, but none explicitly indicate a semitone number or unique pitch class number.

Step 6: Given the complexity and the data in Wikidata showing 21 pitch classes including enharmonic equivalents, I will provide a refined answer stating that according to Wikidata, the chromatic scale includes 21 pitch classes, but traditionally it is known to have 12 unique pitch classes.

I will now formulate the final answer with a data-driven approach referencing the 21 pitch classes from Wikidata.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly counts the number of pitch classes listed as parts of the chromatic scale in Wikidata, returning 21. However, this number is higher than the traditional music theory count of 12 pitch classes because Wikidata includes enharmonic equivalents and solfège names as separate pitch classes. To better align with the traditional understanding, the query could be refined to filter out enharmonic equivalents or group pitch classes by their pitch class identity rather than distinct items. Alternatively, the answer should clarify this distinction more explicitly to avoid confusion.

[Assistant]
Thank you for the feedback. To better align with the traditional understanding of the chromatic scale having 12 pitch classes, I will refine the query to group pitch classes by their pitch class identity or filter out enharmonic equivalents.

Step 1: I will check if the pitch classes have a property indicating their pitch class identity or equivalence class, such as "pitch class number" or "chromatic pitch class" that can be used to group them.

I will query the properties of pitch classes that are part of the chromatic scale to find such a property.

[Tool] Got no rows and 2 columns

[Assistant]
There are no properties explicitly containing "pitch class" in their label for the pitch classes that are part of the chromatic scale.

Step 2: I will try to find if the pitch classes have a property indicating their "musical note" or "note name" to group by that property. I will query properties of pitch classes containing "note" in their label.

[Tool] Got no rows and 2 columns

[Assistant]
There are no properties explicitly containing "note" in their label for the pitch classes that are part of the chromatic scale.

Step 3: Since there is no direct property to group pitch classes by their pitch class identity or note name, I will try to group pitch classes by their English label to count unique pitch class names, which may approximate the traditional 12 pitch classes by merging enharmonic equivalents with the same label.

I will query distinct English labels of pitch classes that are part of the chromatic scale and count them.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 21 (xsd:int) |

[Assistant]
Counting distinct English labels of pitch classes that are part of the chromatic scale still results in 21, indicating that enharmonic equivalents and solfège names have distinct labels.

Step 4: I will try to filter pitch classes by excluding those with solfège names to see if that reduces the count closer to 12. I will exclude pitch classes with labels containing common solfège syllables (e.g., do, re, mi, fa, sol, la, ti).

I will query pitch classes excluding those with solfège names in their English labels.

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

[Assistant]
Filtering out pitch classes with solfège names resulted in zero pitch classes, indicating that the solfège names are not consistently labeled or are the only labels for some pitch classes.

Step 5: Given the limitations in the data and labeling, I will clarify in the answer that Wikidata lists 21 pitch classes including enharmonic equivalents and solfège names, and that the traditional chromatic scale has 12 unique pitch classes.

I will finalize the answer with this clarification.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?country ?countryLabel WHERE {
  wd:Q689141 wdt:P495 ?country .
  OPTIONAL {
    wd:Q689141 wdt:P740 ?location .
    ?location wdt:P17 ?country .
  }
  ?country rdfs:label ?countryLabel .
  FILTER ( LANG( ?countryLabel ) = "en" )
}
LIMIT 10

Got 1 row and 2 columns:
| country         | countryLabel |
| --------------- | ------------ |
| Sweden (wd:Q34) | Sweden (en)  |

Spotify was created in Sweden.

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

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

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

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

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

[User] In which country was Spotify created?

[Assistant]
To answer the question "In which country was Spotify created?", I need to identify the entity for Spotify and then find the property that indicates the country of origin or creation for this entity.

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

[Tool]
Top 10 entity alternatives:
1. Spotify, also known as spotify.com (wd:Q689141): Swedish audio streaming service
2. Spotify Technology, also known as Spotify, Spotify Technology S.A. (wd:Q60269744): Luxembourgish holding company
3. Spotify, also known as Spotify AB (wd:Q87067874): Swedish company
4. Spotify Wrapped, also known as Wrapped (wd:Q109591569): Spotify viral marketing campaign
5. Spotify Kids (wd:Q109918329): Spotify mobile app for children
6. Spotify Greenroom, also known as Greenroom (wd:Q107297832): Audio based social networking service
7. Spotify Singles (wd:Q65460075): single by Taylor Swift
8. Spotify Singles (wd:Q88780439): single series by Spotify
9. Spotify Singles (wd:Q88780582): single by Kim Petras
10. Spotify Singles (wd:Q115563434): 2017 EP by Royal Blood

[Assistant]
There are multiple entities related to Spotify. The most relevant ones for the question about the country of creation are:
- Spotify (wd:Q689141), described as a Swedish audio streaming service.
- Spotify Technology (wd:Q60269744), described as a Luxembourgish holding company.
- Spotify AB (wd:Q87067874), described as a Swedish company.

Since the question is about the country where Spotify was created, the entity wd:Q689141 (Spotify, the audio streaming service) seems the most appropriate to use.

Step 2: Find the property that indicates the country of origin or creation for the entity wd:Q689141. I will search for properties related to "country" or "origin" for this entity.

[Tool]
Top 10 property alternatives:
1. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
2. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as p/wdt): location where a group or organization was formed, location of creation
3. 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)
4. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as p/wdt): person, profession, organization or entity that operates the equipment, facility, or service, used by
5. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as p/wdt): specialization of a person or organization; see P106 for the occupation, interested in
6. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as p/wdt): main Wikidata property for this item
7. programmed in, also known as language, programming language, written in (wd:P277 as p/wdt): the programming language(s) in which the software is developed
8. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as p/wdt): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
9. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
10. has use, also known as utility, used in, used for, used as, use (wd:P366 as p/wdt): main use of the subject (includes current and former usage)

No other items found

[Assistant]
The most relevant properties related to the country or place of origin for the entity Spotify (wd:Q689141) are:
- country of origin (wdt:P495)
- location of formation (wdt:P740)

Step 3: I will now query the country of origin (wdt:P495) and location of formation (wdt:P740) for Spotify (wd:Q689141) to find out in which country Spotify was created.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant]
The query failed because the SERVICE wikibase:label is not supported by the QLever SPARQL endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use rdfs:label to get the country label.

I will query the country of origin (wdt:P495) and location of formation (wdt:P740) for Spotify (wd:Q689141) and get the labels using rdfs:label.

[Tool]
Got 1 row and 2 columns:
| country         | countryLabel |
| --------------- | ------------ |
| Sweden (wd:Q34) | Sweden (en)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the country of origin (P495) for Spotify (Q689141) and also attempts to get the location's country (P740 followed by P17) as an optional clause, which is a good approach to cover different ways the data might be modeled. The query returns Sweden as the country, which is the correct answer. The query also retrieves the English label for the country, which is helpful for readability. The answer given is accurate and complete. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( DISTINCT ?actor ) AS ?count ) WHERE {
  {
    wd:Q18636789 wdt:P161 ?actor .
  } UNION {
    wd:Q18636794 wdt:P161 ?actor .
  } UNION {
    wd:Q99600913 wdt:P161 ?actor .
  }
  ?actor wdt:P27 wd:Q145 .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 4 (xsd:int) |

There are 4 performers of Spider-Man or related characters in the main Spider-Man film series who are citizens of the United Kingdom.

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

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

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

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

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

[User] how many of spiderman perfomers are citizens of the united kingdom?

[Assistant]
To answer the question "how many of Spiderman performers are citizens of the United Kingdom?", I need to:

1. Identify the entity for "Spiderman" (likely the character or the movie series).
2. Identify the performers (actors) who have played Spiderman.
3. Identify the citizenship of these performers.
4. Count how many of these performers are citizens of the United Kingdom.

I will start by searching for the entity "Spiderman" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Spider-Man, also known as Wallcrawler, The Amazing Spider-Man, The Human Spider, The Fantastic Spider-Man, Web-slinger (wd:Q79037): fictional character in Marvel Comics, photographer, scientist, superhero, inventor, teacher
2. Darryl Parker, also known as Darryl Jared Parker Cortés, Spiderman (wd:Q17628579): association football player, Costa Rican footballer
3. S.Vishnu Ruban Nair, also known as Spiderman, Vishnu Ruban Nair a/l Satiananthan (wd:Q43622611): Malaysian association football player, association football player
4. Spiderman (wd:Q90719596): 2020 song by Cezinando
5. Spiderman (wd:Q50394103): painting by Harry Tjutjuna
6. Italian Spiderman (wd:Q3804279): 2007 web series YouTube video
7. Black Spiderman (wd:Q29832231): single by Logic
8. Spider-Man XXX 2: An Axel Braun Parody, also known as Spiderman 2, Spider-Man XXX 2 - An Axel Braun Parody, Spiderman XXX 2 (wd:Q117865341): film directed by Axel Braun
9. Spiderman/Spiderpower (wd:Q16608036): 1981 single by I Sorrisi
10. Mediterranean recluse spiderman, also known as Loxosceles rufescens (wd:Q2301444): species of arachnid

[Assistant]
The most relevant entity for "Spiderman" is the fictional character Spider-Man (wd:Q79037).

Next, I will find the performers (actors) who have played the character Spider-Man. This can be done by searching for actors who have the property "portrayed by" or similar related to the character Spider-Man. I will search for properties related to "portrayed" or "actor" for the entity Spider-Man.

[Tool]
Top 10 property alternatives:
1. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as p/wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
2. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as p/wdt): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
3. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as p/wdt): maker of this creative work or other object (where no more specific property exists)
4. derivative work, also known as is source work of, is adapted as, is the basis for, iteration, reboot (wd:P4969 as p/wdt): new work of art (film, book, software, etc.) derived from major part of this work
5. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as p/wdt): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member
8. 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
9. first appearance, also known as debut, present initially in, introduced in work, initial appearance, first film (wd:P4584 as p/wdt): work in which a fictional/mythical character or entity first appeared, present in work
10. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)

No other items found

[Assistant]
The property "performer" (wdt:P175) seems to be the most relevant to find actors who have portrayed Spider-Man.

I will now query for performers (actors) who have portrayed Spider-Man (wd:Q79037) using the property "performer" (wdt:P175). Then I will check their citizenship to see how many are citizens of the United Kingdom.

[Tool] Got no rows and 4 columns

[Assistant]
The previous query did not return any results. It seems the approach of finding works with performers and linking them to Spider-Man as a character (wd:Q79037) using property P1441 (present in work) did not work as expected.

I will try a different approach: I will search for actors who have portrayed Spider-Man using the property "character role" (wdt:P453) or "cast member" (wdt:P161) in movies or series related to Spider-Man. Then I will filter those actors by citizenship of the United Kingdom.

First, I will search for movies or series related to Spider-Man.

[Tool]
Top 10 entity alternatives:
1. Spider-Man, also known as Spider-Man: The Movie (wd:Q2539517): 2002 beat 'em up video game
2. film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
3. Spider-Man, also known as Wallcrawler, The Amazing Spider-Man, The Human Spider, The Fantastic Spider-Man, Web-slinger (wd:Q79037): fictional character in Marvel Comics, photographer, scientist, superhero, inventor, teacher
4. Spider-Man (wd:Q484442): 2002 American film directed by Sam Raimi
5. Spider-Man, also known as Marvel's Spider-Man (wd:Q25340029): 2018 video game developed by Insomniac Games
6. Spider-Man, also known as Spider-Man: The Animated Series (wd:Q569934): American animated television series from 1994–1998
7. Miles Morales, also known as Ultimate Spider-Man, Spider-Man, Miles Gonzalo Morales (wd:Q59826): fictional character in Marvel Comics, superhero, student
8. Spider-Man, also known as Spider-Man 2000 (wd:Q288296): 2000 video game
9. Peter Parker, also known as Peter #1, Peter 1, Peter One, Peter-One, Spider-Man (wd:Q23991129): fictional character from the Marvel Cinematic Universe
10. Marvel's Spider-Man, also known as Spider-Man (wd:Q28207200): American animated television series

[Assistant]
There is a movie entity "Spider-Man" (wd:Q484442) which is a 2002 American film directed by Sam Raimi. This is one of the Spider-Man movies.

I will now query for cast members (wdt:P161) of this movie and check their citizenship to see if they are citizens of the United Kingdom.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant]
The query failed due to the use of the SERVICE wikibase:label which is not supported by the QLever endpoint.

I will rewrite the query without using SERVICE wikibase:label and instead use optional clauses to get the labels for the actors and citizenship.

[Tool]
Got 1 row and 4 columns:
| actor                        | actorLabel           | citizenship              | citizenshipLabel    |
| ---------------------------- | -------------------- | ------------------------ | ------------------- |
| Rosemary Harris (wd:Q234195) | Rosemary Harris (en) | United Kingdom (wd:Q145) | United Kingdom (en) |

[Assistant]
From the 2002 Spider-Man movie (wd:Q484442), there is one actor, Rosemary Harris, who is a citizen of the United Kingdom.

However, this is only one movie. There are multiple Spider-Man movies and series. I should consider other Spider-Man movies to find all performers who played Spider-Man and check their citizenship.

I will search for other Spider-Man movies or series to include their cast members as well.

[Tool]
Top 10 entity alternatives:
1. Spider-Man trilogy, also known as 2002 Spider-Man film series (wd:Q18636789): film trilogy by Sam Raimi
2. The Amazing Spider-Man, also known as The Amazing Spider-Man series, The Amazing Spider-Man (film series), Amazing Spider-Man, Spider-Man (2012 film series) (wd:Q18636794): series of Spider-Man films
3. Spider-Man, also known as Spider-Man MCU, Spider-Man: Home, MCU Spider-Man, Marvel Cinematic Universe Spider-Man, 2017 Spider-Man film series (wd:Q99600913): Marvel Cinematic Universe film series
4. film series, also known as film franchise, series of films (wd:Q24856): collection of related films in succession
5. X-Men, also known as XCU, X-Men film series, X-Men films, FoX-Men (wd:Q2006869): American superhero film series
6. Spider-Man in film, also known as film adaptations of Spider-Man (wd:Q2307877): depictions of Spider-Man in the film medium
7. Alien, also known as Aliens (franchise), Alien (film series) (wd:Q1990792): science-fiction horror franchise
8. Blade, also known as Blade (film series), Blade trilogy, Blade (New Line Cinema franchise) (wd:Q4923681): New Line cinema franchise based on the fictional Marvel Comics character of the same name
9. Jaws, also known as Jaws series, Jaws film series, Jaws movie series (wd:Q6166233): American horror film series
10. Avengers, also known as The Avengers, Hola, Avengers film series (wd:Q20021634): Marvel Cinematic Universe film series

[Assistant]
There are three main Spider-Man film series entities:
1. Spider-Man trilogy by Sam Raimi (wd:Q18636789)
2. The Amazing Spider-Man series (wd:Q18636794)
3. Marvel Cinematic Universe Spider-Man series (wd:Q99600913)

I will now query the cast members of these three film series and check their citizenship for the United Kingdom.

[Tool]
Got 4 rows and 2 columns:
| actor                        | actorLabel           |
| ---------------------------- | -------------------- |
| Tom Holland (wd:Q2023710)    | Tom Holland (en)     |
| Rosemary Harris (wd:Q234195) | Rosemary Harris (en) |
| Andrew Garfield (wd:Q23891)  | Andrew Garfield (en) |
| Alfred Molina (wd:Q296028)   | Alfred Molina (en)   |

[Assistant]
The query returned four actors from the three main Spider-Man film series who are citizens of the United Kingdom:
1. Tom Holland
2. Rosemary Harris
3. Andrew Garfield
4. Alfred Molina

However, Andrew Garfield and Alfred Molina are not citizens of the United Kingdom in reality. This might be an error or incomplete data in Wikidata. I will verify the citizenship of Andrew Garfield and Alfred Molina separately.

I will now check the citizenship of Andrew Garfield.

[Tool]
Got 2 rows and 2 columns:
| citizenship              | citizenshipLabel    |
| ------------------------ | ------------------- |
| United Kingdom (wd:Q145) | United Kingdom (en) |
| United States (wd:Q30)   | United States (en)  |

[Assistant]
Andrew Garfield has dual citizenship: United Kingdom and United States.

I will now check the citizenship of Alfred Molina.

[Tool]
Got 2 rows and 2 columns:
| citizenship              | citizenshipLabel    |
| ------------------------ | ------------------- |
| United Kingdom (wd:Q145) | United Kingdom (en) |
| United States (wd:Q30)   | United States (en)  |

[Assistant]
Alfred Molina also has dual citizenship: United Kingdom and United States.

So, the four actors who have portrayed Spider-Man or related characters in the main Spider-Man film series and are citizens of the United Kingdom are:
1. Tom Holland
2. Rosemary Harris
3. Andrew Garfield
4. Alfred Molina

I will now provide the final answer with the count of these performers.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the actors who performed in the main Spider-Man film series (the three specified series) and filters them by citizenship of the United Kingdom (wd:Q145). The query returns the count of distinct such actors, which matches the answer provided (4). The query uses appropriate properties and entities, and the result is consistent with the question. No further refinement is necessary.