PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?actor ?actorLabel WHERE {
  wd:Q38685497 wdt:P161 ?actor .
  wd:Q19347291 wdt:P161 ?actor .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel FILTER ( LANG( ?actorLabel ) = "en" )
  }
}

The actor starring in both Free Guy and Deadpool is Ryan Reynolds.

Which actor starring in Free Guy also starred in Deadpool?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 actor starring in Free Guy also starred in Deadpool?

[Assistant] Step 1: Identify the entities "Free Guy" and "Deadpool" in Wikidata to get their Q-IDs. Then find the actors starring in "Free Guy" and check which of them also starred in "Deadpool." I will start by searching for the entity "Free Guy."

[Tool]
Top 10 entity alternatives:
1. Free Guy (wd:Q38685497): 2021 film directed by Shawn Levy, instance of film
2. Free Guy (wd:Q125480984): 2021 soundtrack albums, instance of album
3. Ken E. Nwadike Jr, also known as Kenneth Nwadike, Kenneth Nwadike Jr., Ken Nwadike, Ken Nwadike Jr., The Free Hugs Guy (wd:Q24088903): American documentary filmmaker, motivational speaker, and peace activist, motivational speaker, television producer, instance of human, YouTuber
4. Guy Frederick Freemantle, also known as Guy Freemantle (wd:Q75976500): instance of human, (born 1983)
5. Guy Freeman (wd:Q102380080): Ph.D. University of Warwick 2011, instance of human, statistician
6. Guy Freeman (wd:Q79991807): instance of human, researcher
7. John Freeman Guy (wd:Q102194478): Ph.D. University of Pittsburgh 1923, instance of human
8. Tall Guys Free, also known as tallmenfree.com, tallguysfree.com, tall.guysfree.com, tallguyfree.com, Big Men Free (wd:Q30559981): Photo gallery website featuring tall men, instance of web application, instance of organization, instance of website
9. freedom of religion in Guyana, also known as Guyana freedom of religion, Guyana religious freedom, religious freedom in Guyana, religious freedom of Guyana (wd:Q5500767): instance of freedom of religion by country
10. Free Province of Guyaquil (wd:Q113396371): country that existed in modern day Ecuador

[Assistant] I found the entity for the 2021 film "Free Guy" as wd:Q38685497. Next, I will search for the entity "Deadpool" to get its Q-ID.

[Tool]
Top 10 entity alternatives:
1. Deadpool, also known as X-Men Origins: Deadpool (wd:Q19347291): 2016 film directed by Tim Miller, instance of film
2. Deadpool, also known as Wade Winston Wilson, Wade Wilson, Merc with a Mouth (wd:Q1631090): fictional character in Marvel Comics, instance of video game character, instance of animated character, instance of film character, instance of supersoldier, instance of mutate, mercenary, soldier
3. Deadpool (wd:Q2112423): instance of video game, 2013 video game
4. dead pool, also known as deadpool, death pool (wd:Q3397848): game of prediction which involves guessing when someone will die, instance of game of chance
5. Wade Wilson, also known as Weapon XI, Deadpool (wd:Q113485245): X-Men film series and Marvel Cinematic Universe character, instance of fictional vigilante, instance of film character, instance of mutant, martial artist, time traveller, mass murderer, swordfighter, vigilante, mercenary, assassin, soldier, outlaw
6. Deadpool (wd:Q5245706): instance of series of creative works, title of multiple comic book series, instance of comic book
7. Deadpool (wd:Q22696439): album by Junkie XL, instance of album
8. Deadpool (wd:Q60740482): unproduced US television series from 2018, instance of unproduced television series
9. Deadpool, also known as Deadpool film series (wd:Q29559108): film series based on Marvel Comics, instance of film series
10. Deadpool (wd:Q109285374): instance of pinball machine game, 2018 pinball machine

[Assistant] I found the entity for the 2016 film "Deadpool" as wd:Q19347291. Now I will find actors starring in "Free Guy" (wd:Q38685497) and check which of them also starred in "Deadpool" (wd:Q19347291). The property for cast member in a film is usually "wdt:P161". I will query for actors starring in both films.

[Tool] Got no rows and 2 columns

[Assistant] No actor was found starring in both "Free Guy" and "Deadpool" using the direct property wdt:P161 for cast member. I will try to check the cast members of "Free Guy" and "Deadpool" separately and then find the intersection manually. First, I will get the cast members of "Free Guy."

[Tool]
Got 24 rows and 2 columns, showing the first 5 and last 5 rows below:
| actor                          | actorLabel            |
| ------------------------------ | --------------------- |
| Lin Hultgren (wd:Q100593577)   | Lin Hultgren (en)     |
| Aaron W. Reed (wd:Q107922511)  | Aaron W. Reed (en)    |
| Eugene Nomura (wd:Q10856173)   | Eugene Nomura (en)    |
| Owen Burke (wd:Q11293100)      | Owen Burke (en)       |
| Jodie Comer (wd:Q16567346)     | Jodie Comer (en)      |
| ...                            | ...                   |
| Utkarsh Ambudkar (wd:Q7902890) | Utkarsh Ambudkar (en) |
| LazarBeam (wd:Q85324031)       | LazarBeam (en)        |
| Alex Trebek (wd:Q929985)       | Alex Trebek (en)      |
| Anabel Graetz (wd:Q96471814)   | Anabel Graetz (en)    |
| Jose Guns Alves (wd:Q99600160) | Jose Guns Alves (en)  |

[Assistant] I retrieved 24 actors starring in "Free Guy." Now I will retrieve the actors starring in "Deadpool" to find the intersection.

[Tool]
Got 17 rows and 2 columns, showing the first 5 and last 5 rows below:
| actor                             | actorLabel              |
| --------------------------------- | ----------------------- |
| T.J. Miller (wd:Q1148822)         | T.J. Miller (en)        |
| Stefan Kapičić (wd:Q1262154)      | Stefan Kapičić (en)     |
| Stan Lee (wd:Q181900)             | Stan Lee (en)           |
| Ryan Reynolds (wd:Q192682)        | Ryan Reynolds (en)      |
| Brianna Hildebrand (wd:Q19956159) | Brianna Hildebrand (en) |
| ...                               | ...                     |
| Ed Skrein (wd:Q5335413)           | Ed Skrein (en)          |
| Leslie Uggams (wd:Q534925)        | Leslie Uggams (en)      |
| Jed Rees (wd:Q6172620)            | Jed Rees (en)           |
| Randal Reeder (wd:Q7291478)       | Randal Reeder (en)      |
| Rob Hayter (wd:Q98755329)         | Rob Hayter (en)         |

[Assistant] I retrieved 17 actors starring in "Deadpool." Now I will find the intersection of actors who starred in both "Free Guy" and "Deadpool." I will do this by checking which actors from "Free Guy" are also in the cast of "Deadpool."

[Tool]
Got 1 row and 2 columns:
| actor                      | actorLabel         |
| -------------------------- | ------------------ |
| Ryan Reynolds (wd:Q192682) | Ryan Reynolds (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q6228 wdt:P47 wd:Q6224 .
}

Yes, the district of Höxter is next to the district of Paderborn as they share a border.

Is the district of Höxter next to the district of Paderborn?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] Is the district of Höxter next to the district of Paderborn?

[Assistant] To answer this question, I need to check if the district of Höxter shares a border with the district of Paderborn. First, I will identify the entities for the districts of Höxter and Paderborn in Wikidata. Then, I will check if there is a spatial or adjacency relation between them. I will start by searching for the entity of the district of Höxter.

[Tool]
Top 10 entity alternatives:
1. Höxter District, also known as District of Hoxter, District of Höxter, Hoxter District (wd:Q1229842): instance of former administrative territorial entity, former district in the Kingdom of Westphalia
2. Höxter, also known as Höxter (district) (wd:Q6228): instance of rural district of North Rhine-Westphalia, German district in North Rhine-Westphalia
3. Höxter District (wd:Q1351319): former (1816–1974) rural district of Germany, instance of district of Germany
4. Washington, D.C., also known as D.C. Washington, District of Columbia, The District, Washington, District of Columbia (wd:Q61): capital city of the United States of America, instance of federal capital
5. district of Germany, also known as Landkreis, Kreis (wd:Q106658)
6. Setúbal, also known as Setúbal District, District of Setúbal, Setubal District, Setubal (wd:Q274109): instance of district of Portugal, instance of electoral unit, district of Portugal
7. Beja, also known as Beja District, District of Beja (wd:Q321455): instance of district of Portugal, district in southern Portugal
8. Emsland, also known as District of Emsland, Landkreis Emsland (wd:Q5936): German district (Landkreis) in Lower Saxony, instance of district of Lower Saxony, instance of Option municipality
9. Lezhë District, also known as District of Lezhë (wd:Q194185): instance of former administrative territorial entity, former geographic subdivision of Albania, instance of district of Albania
10. Waldshut, also known as District of Waldshut, Waldshut (district) (wd:Q8200): instance of rural district of Baden-Württemberg, district of Baden-Württemberg, Germany, instance of Option municipality

[Assistant] The district of Höxter is represented by the entity wd:Q6228 in Wikidata. Next, I will search for the entity representing the district of Paderborn.

[Tool]
Top 10 entity alternatives:
1. Paderborn District, also known as District of Paderborn (wd:Q1230010): instance of former administrative territorial entity, former district in the Kingdom of Westphalia
2. Paderborn, also known as Paderborn (district) (wd:Q6224): instance of rural district of North Rhine-Westphalia, German district of North Rhine-Westphalia
3. Washington, D.C., also known as D.C. Washington, District of Columbia, The District, Washington, District of Columbia (wd:Q61): capital city of the United States of America, instance of federal capital
4. district of Germany, also known as Landkreis, Kreis (wd:Q106658)
5. Setúbal, also known as Setúbal District, District of Setúbal, Setubal District, Setubal (wd:Q274109): instance of district of Portugal, instance of electoral unit, district of Portugal
6. Beja, also known as Beja District, District of Beja (wd:Q321455): instance of district of Portugal, district in southern Portugal
7. Emsland, also known as District of Emsland, Landkreis Emsland (wd:Q5936): German district (Landkreis) in Lower Saxony, instance of district of Lower Saxony, instance of Option municipality
8. Lezhë District, also known as District of Lezhë (wd:Q194185): instance of former administrative territorial entity, former geographic subdivision of Albania, instance of district of Albania
9. Waldshut, also known as District of Waldshut, Waldshut (district) (wd:Q8200): instance of rural district of Baden-Württemberg, district of Baden-Württemberg, Germany, instance of Option municipality
10. Grevenmacher District, also known as District of Grevenmacher (wd:Q208284): one of three former districts of Luxembourg, instance of district of Luxembourg

[Assistant] The district of Paderborn is represented by the entity wd:Q6224 in Wikidata. Now, I will check if the district of Höxter (wd:Q6228) is adjacent to the district of Paderborn (wd:Q6224). I will look for properties that indicate adjacency or neighboring districts.

[Tool]
Top 10 property alternatives:
1. shares border with, also known as adjacent to, border, bordered by, borders clockwise, next to (wd:P47 as wdt/p): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.
2. located in the administrative territorial entity, also known as is in the shire of, is in the voivodeship of, is in the state of, is in the territory of, is in the town of (wd:P131 as wdt/p): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., subproperty of location, subproperty of part of
3. population, also known as human population, inhabitants (wd:P1082 as wdt/p): number of people inhabiting the place; number of people of subject
4. contains the administrative territorial entity, also known as has states, has shires, has rural cities, has regions, has municipalities (wd:P150 as wdt/p): (list of) direct subdivisions of an administrative territorial entity, subproperty of has part(s)
5. member of, also known as of organization, membership, member of musical group, in musical group, band member of (wd:P463 as wdt/p): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), subproperty of part of
6. named after, also known as named in honor of, toponym, namesake, name after, etymology (wd:P138 as wdt/p): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
7. capital, also known as principal place, seat of government, seat, location of capital, has capital (wd:P36 as wdt/p): seat of government of a country, province, state or other type of administrative territorial entity
8. country, also known as state, sovereign state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), subproperty of located in the administrative territorial entity
9. area, also known as acreage, total area, surface area, surface, size (wd:P2046 as wdt/p): area occupied by an object
10. OpenStreetMap relation ID, also known as OpenStreetMap relation, relation ID (OSM), relation ID (OpenStreetMap), osm rel id, OSM relation ID (wd:P402 as wdt/p/wdtn): identifier for a relation in OpenStreetMap

No other items found

[Assistant] The property "shares border with" (wdt:P47) is used to indicate adjacency or neighboring districts. I will now check if the district of Höxter (wd:Q6228) shares a border with the district of Paderborn (wd:Q6224) using this property.

[Tool] True

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?actor ?actorLabel ( COUNT( DISTINCT ?movie ) AS ?movieCount ) WHERE {
  VALUES ?actor {
    wd:Q166389 wd:Q343616
  }
  ?movie wdt:P31 wd:Q11424 ; wdt:P161 ?actor .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel FILTER ( LANG( ?actorLabel ) = "en" )
  }
}
GROUP BY ?actor ?actorLabel
ORDER BY DESC ( ?movieCount )

Paul Dano acted in 34 movies, while Daniel Day-Lewis acted in 23 movies. Therefore, Paul Dano was an actor in more movies than Daniel Day-Lewis.

Who was an actor in more movies, Daniel Day Lewis or Paul Dano ?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Who was an actor in more movies, Daniel Day Lewis or Paul Dano ?

[Assistant]
To answer the question of who acted in more movies between Daniel Day Lewis and Paul Dano, I need to:

1. Identify the Wikidata entities for Daniel Day Lewis and Paul Dano.
2. Find the movies in which each actor has acted.
3. Count the number of movies for each actor.
4. Compare the counts to determine who acted in more movies.

I will start by searching for the entities of Daniel Day Lewis and Paul Dano in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Dan Lewis, also known as Daniel Lewis (wd:Q351615): football goalkeeper (1902-1965), association football player, instance of human
2. Daniel Lewis (wd:Q3701656): Canadian volleyball player, beach volleyball player, instance of human, volleyball player
3. Daniel Lewis (wd:Q23889119): instance of human, Australian boxer, boxer
4. Daniel Day (wd:Q5216938): English cricketer (1807-1887), instance of human, cricket umpire, cricketer
5. Dapper Dan, also known as Daniel Day (wd:Q56841635): American fashion designer, haberdasher and businessman, instance of human, fashion designer, haberdasher
6. Daniel Lewis, also known as Daniel Paul Lewis (wd:Q5217933): English association football player (born 1982), association football player, instance of human
7. Daniel Lewis (wd:Q5217931): American choreographer, instance of human, choreographer
8. Daniel Lewis, also known as Daniel George Lewis (wd:Q5217932): American conductor (1925-2017), instance of human, music educator, conductor
9. Daniel Day (wd:Q5216936): American woolen manufacturer, instance of human, manager
10. Daniel Day (wd:Q47476854): English darts player, instance of human, darts player

[Tool]
Top 10 entity alternatives:
1. Daniel Day-Lewis, also known as Sir Daniel Michael Blake Day-Lewis, Daniel Michael Blake Day-Lewis (wd:Q166389): British-Irish actor, instance of human, television actor, stage actor, film actor, artist, actor
2. Book of Daniel, also known as Daniel (wd:Q80115): instance of book of the Bible, instance of religious text, book of the Bible
3. Daniel, also known as Beltshazzar (wd:Q171724): biblical figure associated to the Book of Daniel, instance of human biblical figure, religious leader, prophet
4. Daniel, also known as Danny (wd:Q14516546): instance of male given name, male given name
5. Daniel, also known as Daniel, UT, Daniel, Utah (wd:Q483162): town in Wasatch County, Utah, United States, instance of town in the United States
6. Daniel, also known as Daniel, WY, Daniel, Wyoming (wd:Q1159854): human settlement in Sublette County, Wyoming, United States of America, instance of census-designated place in the United States
7. Daniel, also known as Mount Daniel (wd:Q365773): mountain of the Ammergau Alps in Tyrol, Austria, instance of mountain
8. Daniel (wd:Q2731738): song and pop ballad by Elton John, instance of single
9. Daniel, also known as Milan Popović, Danijel Popović (wd:Q969015): Montenegrin-Croatian pop singer, instance of human, songwriter, guitarist, lyricist, composer, singer
10. Daniel (wd:Q4172098): 1983 film by Sidney Lumet, instance of film

[Tool]
Top 10 entity alternatives:
1. Paul Dano, also known as Paul Franklin Dano (wd:Q343616): American actor (born 1984), instance of human, television actor, film director, film producer, screenwriter, voice actor, stage actor, film actor, musician, actor
2. Danomarus (Pauly-Wissowa) (wd:Q60319724): encyclopedic article in Paulys Realencyclopädie der classischen Altertumswissenschaft (RE), instance of encyclopedia article
3. Danova (Pauly-Wissowa) (wd:Q60320689): cross-reference in Paulys Realencyclopädie der classischen Altertumswissenschaft (RE), instance of cross-reference
4. Alan Paul Danovitch, also known as A. P. Danovitch, Alan P. Danovitch, Alan Danovitch (wd:Q105233837): politician in Massachusetts, US, instance of human, politician
5. Paul Peter Danos (wd:Q102881243): Ph.D. University of Texas at Austin 1974, instance of human
6. Paul L. Danove (wd:Q93221138): instance of human, biblical scholar
7. Paul the Apostle, also known as Saul of Tarsus, Šā'ûl, Saulus, Saul, Saint Paulus (wd:Q9200): Early Christian apostle and missionary (c. AD 5 – c. 64/65), instance of human, religious figure, missionary, theologian, traveler, artisan, writer, rabbi
8. Paul I, also known as Pope Paul, Pope Paul I, Paulus I, Paul (wd:Q103404): instance of human, Catholic priest, Catholic bishop, pope (700-767), writer
9. Paul, also known as Paul, USA, Paul, Idaho, Paul, ID (wd:Q1518011): instance of city in the United States, city in Idaho, United States
10. Paul (wd:Q1164753): 2011 film by Greg Mottola, instance of film

[Assistant]
I have identified the entities for the actors:
- Daniel Day-Lewis: wd:Q166389
- Paul Dano: wd:Q343616

Next, I will find the movies in which each actor has acted and count the number of movies for each. I will use the property "cast member" (wdt:P161) to find movies where the actor was a cast member. I will also filter for instances of movies (wd:Q11424) to ensure we count only movies.

I will start by counting the movies for Daniel Day-Lewis.

[Tool]
Got 1 row and 1 column:
| movieCount   |
| ------------ |
| 23 (xsd:int) |

[Tool]
Got 1 row and 1 column:
| movieCount   |
| ------------ |
| 34 (xsd:int) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( SUM( ?revenue ) AS ?combinedRevenue ) WHERE {
  VALUES ?company {
    wd:Q3884 wd:Q2283 wd:Q20800404
  }
  ?company wdt:P2139 ?revenue .
}

The combined total revenue of the three largest Big Tech companies by number of employees (Amazon, Microsoft, and Alphabet Inc.) is 1,127,279,000,000 (approximately 1.13 trillion).

What is the combined total revenue of three largest Big Tech companies ordered by number of employees?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the combined total revenue of three largest Big Tech companies ordered by number of employees?

[Assistant]
To answer this question, I need to follow these steps:

1. Identify the three largest Big Tech companies by number of employees.
2. Retrieve the total revenue for each of these companies.
3. Calculate the combined total revenue of these three companies.

First, I will identify the three largest Big Tech companies by number of employees. I will start by searching for Big Tech companies.

[Tool]
Top 10 entity alternatives:
1. Big Tech, also known as Tech Giants, Big Five, GAFAM, GAFA, big tech companies (wd:Q3122864): label for large technology companies, instance of acronym
2. Big Tech (wd:Q118903924): largest technology companies in India
3. Big Tech: a ascensão dos dados e a morte da política, also known as Big Tech (wd:Q107359185): instance of version, edition or translation, book published in 2018
4. Big Tech (web), also known as GAFAM, Google/Amazon/Facebook/Apple/Microsoft, Google, Amazon, Facebook, Apple, Microsoft, Facebook/Amazon/Apple/Netflix/Google, Facebook, Amazon, Apple, Netflix, Google (wd:Q30748112): companies that dominate the World Wide Web, instance of group
5. Corporate Memphis, also known as Humans of Flat, globohomo, flat art, Corporate Art Style, Big Tech art style (wd:Q105676972): flat, geometric art style, widely used in Big Tech illustrations, instance of art style
6. Riot Sydney, also known as Wargaming Sydney, BigWorld Technologies, BigWorld (wd:Q3456271): instance of video game developer, video game engine developer, instance of game engine
7. Big Trouble for Big Tech (wd:Q126556170): instance of scholarly article, scholarly article
8. Big Technology Podcast (wd:Q131471285): instance of organization, instance of podcast show
9. BIGO Technology, also known as BIGO TECHNOLOGY PTE. LTD. (wd:Q125458107): instance of software company, instance of business
10. The Ben Shapiro Show - Big Brother Meets Big Tech, also known as Big Brother Meets Big Tech, Big Brother Meets Big Tech | Ep. 753, Ep. 753 - Big Brother Meets Big Tech (wd:Q110073466): episode of the Ben Shapiro Show, instance of podcast episode

[Assistant]
There is an entity for Big Tech companies as a label for large technology companies (wd:Q3122864). However, this is a general label and may not directly list the companies. I will instead identify the major Big Tech companies individually: Google (Alphabet), Amazon, Facebook (Meta), Apple, and Microsoft. Then I will find the three largest by number of employees among them.

Next, I will search for these companies in Wikidata to get their entities.

[Tool]
Top 10 entity alternatives:
1. Google, also known as google.com, Google Inc., Google, Inc., Google LLC, Big G (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc., instance of technology company, instance of identity provider, instance of public company, instance of online service, instance of business
2. Google Search, also known as www.google.com, Google Web Search, Google search engine, Google homepage, google.com (wd:Q9366): search engine by Google LLC, instance of search engine
3. Alphabet Inc., also known as Alphabet, Inc, abc.xyz, Alphabet, Inc., Alphabet Incorporated, Google (wd:Q20800404): American multinational technology conglomerate, instance of holding company, instance of public company, instance of organization, instance of business
4. Google+, also known as Google Plus, G+ (wd:Q356): instance of application programming interface, instance of social networking service, instance of service on Internet, instance of computing platform, instance of online community, instance of cloud computing, social networking service, instance of software
5. .google, also known as dot google (wd:Q20573262): instance of generic top-level domain, top-level Internet domain
6. google, also known as googling, to google (wd:Q1156923): transitive verb, meaning to search for something using the Google search engine, instance of verb
7. Google Google (wd:Q123412777): instance of musical work/composition, Tamil song from Thuppakki movie
8. Google (wd:Q125851407): instance of mobile app, mobile app
9. google (wd:Q107382801): instance of Python package, Python library
10. Google (wd:Q110997421): instance of male given name, given name

[Tool]
Top 10 entity alternatives:
1. Amazon, also known as The Amazon River, The Amazon, River Amazon, Amazon River, Amazonian River (wd:Q3783): river in South America, instance of river
2. Amazon, also known as Amazon.com, Inc., Amazon.com (wd:Q3884): American multinational technology company, instance of very large online platform, instance of public company, instance of enterprise, instance of business
3. Amazons, also known as Amazones, Amazon (wd:Q134154)
4. The Pussycat Dolls, also known as Pussycat Dolls, Amazon (wd:Q102385): American girl group and dance ensemble, instance of musical group
5. Mary Celeste, also known as Amazon, Marie Céleste, Marie Celeste (wd:Q33209): Ship found abandoned in the Atlantic Ocean in 1872, instance of merchant vessel, instance of brigantine
6. amazon, also known as elephant, superqueen, queen-knight compound, amazon (chess), chess amazon (wd:Q647433)
7. Amazon (wd:Q771908): 2000 film by Philippe de Broca, instance of film
8. .amazon (wd:Q65073147): instance of generic top-level domain, disputed top-level domain
9. Amazon (wd:Q2841435): 1990 film by Mika Kaurismäki, instance of film
10. Amazon (wd:Q688422): syndicated television show created by Peter Benchley, instance of television series

[Tool]
Top 10 entity alternatives:
1. Facebook, also known as FB (wd:Q355): American online social media and social networking service, instance of user-generated content platform, instance of very large online platform, instance of social networking service, instance of online community, instance of social media, instance of website
2. facebook (wd:Q65960697): instance of Wikipedia article covering multiple topics, Formula One activities of Alfa Romeo
3. FACEBOOK (wd:Q108926046): scholarly article by Andréa Karla Ferreira Nunes et al published 8 July 2021 in Revista Extensão em Ação, instance of scholarly article
4. Facebook, also known as xkcd 300 (wd:Q18613161): 300th strip of the webcomic xkcd, instance of comic strip
5. Facebook (wd:Q125685626): journal article from 'The Global South' published in 2022, instance of scholarly article
6. Facebook (wd:L1378877-F1)
7. Facebook (wd:L1420807-S1)
8. Facebook (wd:L477912): instance of endocentric compound, instance of brand name
9. Facebook (wd:L477912-F1)
10. Facebook (wd:L1378877)

[Tool]
Top 10 entity alternatives:
1. Meta Platforms, also known as TheFacebook, Meta Platforms, Inc., TheFacebook, Inc., Facebook, Inc., Meta (wd:Q380): American multinational technology corporation, instance of online service provider, instance of technology company, instance of public company, instance of business
2. Meta Department, also known as Department of Meta, Meta (wd:Q238629): instance of department of Colombia, department of Colombia
3. Meta (wd:Q72265): instance of commune of Italy, Italian comune in Campania
4. Wikimedia Meta-Wiki, also known as Meta Wiki, Meta-Wiki, Meta, meta.wikimedia.org, metawiki (wd:Q1063116): wiki that serves as the global coordination hub for the Wikimedia Foundation's wikis, instance of multi-languoid Wikimedia site, instance of multi-script Wikimedia site, instance of wiki with script conversion, instance of Wikimedia special project
5. Meta, also known as Meta, MO, Meta, Missouri (wd:Q966170): instance of city in the United States, city in Missouri
6. meta-, also known as met- (wd:Q1045105): Greek prefix: prefix of abstraction, instance of prefix
7. meta, also known as meta HTML tag, <meta>, meta element, <meta> element, <meta> tag (wd:Q251684): instance of metadata element, instance of phrasing element, instance of flow element, HTML element
8. Meta (wd:Q140566): genus of arachnids, instance of taxon
9. Meta', also known as Meta' language (wd:Q36054)
10. Meta (wd:Q18426818): frazione of Civitella Roveto, Italy, instance of frazione

[Tool]
Top 10 entity alternatives:
1. apple, also known as apple fruit (wd:Q89)
2. Apple, also known as Apple, Inc, Apple Computer Inc., Apple Incorporated, Apple Computer Inc (wd:Q312): American multinational technology company based in Cupertino, California, instance of computer manufacturer, instance of technology company, instance of public company, instance of organization, instance of corporation, instance of enterprise, instance of business, instance of brand
3. Malus, also known as crabapple, apples, apple (wd:Q104819)
4. Apple Records, also known as Apple (label), Apple (wd:Q213710): instance of record label, instance of enterprise, instance of trademark, UK record label
5. Muggsy Bogues, also known as Muggs, Tyrone Curtis Bogues, Tyrone Bogues, Billy, Apple (wd:Q150502): American basketball player-coach, instance of human, basketball player, basketball coach
6. Malus pumila, also known as domestic apple, apple (wd:Q158657): species of apple tree, instance of taxon
7. The Apple, also known as Apple, Sib (wd:Q595660): 1998 film by Samira Makhmalbaf, instance of film
8. Apple (wd:Q1754545): 1990 debut studio album by Mother Love Bone, instance of album
9. Ariane Passenger Payload Experiment, also known as APPLE (wd:Q2248280): instance of communications satellite, communication satellite
10. Apple (wd:Q128117967): instance of musical work/composition, 2024 song by Charli XCX

[Tool]
Top 10 entity alternatives:
1. Microsoft, also known as Micro-Soft, MS, Microsoft Corp. (wd:Q2283): American multinational technology corporation, instance of technology company, instance of software company, instance of public company, instance of organization, instance of business
2. .microsoft, also known as dot microsoft (wd:Q20574990): instance of sponsored top-level domain, sponsored top-level Internet domain
3. Microsoft, also known as xkcd 1118 (wd:Q18615057): 1118th strip of the webcomic xkcd, instance of comic strip
4. Microsoft s.r.o., also known as Microsoft, MICROSOFT s.r.o. (wd:Q31327320): Czech company, subsidiary of Microsoft Corporation, instance of enterprise, instance of business
5. Microsoft, also known as Microsoft (brand), Microsoft brand (wd:Q124993733): brand of computers, computer accessories, and software owned by Microsoft Corporation, instance of trademark, instance of brand
6. Microsoft (wd:L476749-F1)
7. Microsoft (wd:L476749): instance of blend word
8. Microsoft Windows, also known as Windows systems, MSFT Win, Windows, Win, MS Windows (wd:Q1406)
9. C#, also known as CSharp, C Sharp, C-Sharp, Microsoft Java, c# (wd:Q2370): multi-paradigm (object-oriented) programming language, instance of multi-paradigm programming language, instance of event-driven programming language, instance of class-based programming language, instance of imperative programming language, instance of functional programming language, instance of high-level programming language, instance of generic programming language, instance of strict programming language
10. MS-DOS, also known as Microsoft DOS, MS DOS, MSDOS, DOS, Microsoft Disk Operating System (wd:Q47604)

[Assistant]
I have identified the Wikidata entities for the major Big Tech companies:
- Alphabet Inc. (Google's parent company): wd:Q20800404
- Amazon.com, Inc.: wd:Q3884
- Meta Platforms, Inc. (Facebook's parent company): wd:Q380
- Apple Inc.: wd:Q312
- Microsoft Corporation: wd:Q2283

Next, I will retrieve the number of employees for each of these companies to find the three largest by number of employees.

[Tool]
Got 5 rows and 3 columns:
| company                      | companyLabel        | employees             |
| ---------------------------- | ------------------- | --------------------- |
| Amazon (wd:Q3884)            | Amazon (en)         | 1608000 (xsd:decimal) |
| Microsoft (wd:Q2283)         | Microsoft (en)      | 228000 (xsd:decimal)  |
| Alphabet Inc. (wd:Q20800404) | Alphabet Inc. (en)  | 190234 (xsd:decimal)  |
| Apple (wd:Q312)              | Apple (en)          | 164000 (xsd:decimal)  |
| Meta Platforms (wd:Q380)     | Meta Platforms (en) | 58604 (xsd:decimal)   |

[Assistant]
The three largest Big Tech companies by number of employees are:
1. Amazon with 1,608,000 employees
2. Microsoft with 228,000 employees
3. Alphabet Inc. (Google's parent company) with 190,234 employees

Next, I will retrieve the total revenue for these three companies.

[Tool]
Got 3 rows and 3 columns:
| company                      | companyLabel       | revenue                    |
| ---------------------------- | ------------------ | -------------------------- |
| Alphabet Inc. (wd:Q20800404) | Alphabet Inc. (en) | 307394000000 (xsd:decimal) |
| Microsoft (wd:Q2283)         | Microsoft (en)     | 245100000000 (xsd:decimal) |
| Amazon (wd:Q3884)            | Amazon (en)        | 574785000000 (xsd:decimal) |

[Assistant]
The total revenues for the three largest Big Tech companies by number of employees are:
- Amazon: 574,785,000,000
- Microsoft: 245,100,000,000
- Alphabet Inc.: 307,394,000,000

I will now calculate the combined total revenue of these three companies.

[Tool]
Got 1 row and 1 column:
| combinedRevenue             |
| --------------------------- |
| 1127279000000 (xsd:decimal) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?language ?languageLabel WHERE {
  wd:Q230141 wdt:P103 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

The mother tongue (native language) of the author Chimamanda Ngozi Adichie is Igbo.

What is the mother tongue of the author Chimamanda Ngozi Adichie ?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the mother tongue of the author Chimamanda Ngozi Adichie ?

[Assistant]
Step 1: Identify the entity "Chimamanda Ngozi Adichie" in Wikidata to get her unique identifier. Then, find the property that corresponds to "mother tongue" or "native language" for a person.

I will start by searching for the entity "Chimamanda Ngozi Adichie" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Chimamanda Ngozi Adichie, also known as Chimamanda Adichie, Ngozi Adichie, Adichie (wd:Q230141): Nigerian writer (born 1977), non-fiction writer, short story writer, instance of human, journalist, novelist, cook, poet
2. Chimamanda Ngozi Adichie bibliography (wd:Q132146878)
3. A Companion to Chimamanda Ngozi Adichie (wd:Q127903701): instance of scholarly article, scholarly article
4. Sejamos todos feministas. CHIMAMANDA Ngozi Adichie (wd:Q128712469): instance of scholarly article, scholarly article
5. Chimamanda Ngozi Adichie: claves para ser feministas (wd:Q129760155): scholarly article published on 28 February 2018, instance of scholarly article
6. Ep 284 - Americanah, by Chimamanda Ngozi Adichie (wd:Q116821552): instance of podcast episode, Overdue podcast episode
7. Chimamanda Ngozi Adichie: The danger of a single story (wd:Q22998796): instance of TED Global talk, TEDGlobal 2009
8. Christianity and patriarchy in C... Ngozi Adichie’s Purple Hibiscus (wd:Q129315661): instance of scholarly article, scholarly article
9. Affectations, Conformation and D...anah by Chimamanda Ngozi Adichie (wd:Q125908868): scientific article published in 2021, instance of scholarly article
10. Ownership of Language: Diglossia...tion of Chimamanda Ngozi Adichie (wd:Q127659157): instance of scholarly article, scholarly article

[Assistant] The entity for Chimamanda Ngozi Adichie is wd:Q230141. Next, I will search for properties related to "mother tongue" or "native language" for this entity to find the relevant property to use in the query.

[Tool]
Top 10 property alternatives:
1. native language, also known as first language, mother tongue, language native, L1 speaker of (wd:P103 as wdt/p): language or languages a person has learned from early childhood, subproperty of languages spoken, written or signed
2. languages spoken, written or signed, also known as language written, wrote language, writes language, uses language, used language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
3. writing language, also known as languages for writing, writing languages, language written, languages written, languages of writings (wd:P6886 as wdt/p): language in which the writer has written their work, subproperty of languages spoken, written or signed
4. ethnic group, also known as tribal affiliation, race, people, ethnicity, culture (wd:P172 as wdt/p): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
5. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, subproperty of country
6. sex or gender, also known as biological sex, gender, gender expression, gender identity, gender or sex (wd:P21 as wdt/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
7. audio recording of the subject's spoken voice, also known as voice recording, audio clip, spoken voice, speaking voice, recording of the subject's spoken voice (wd:P990 as wdt/p): audio file representing the speaking voice of a person; or of an animated cartoon or other fictitious character, subproperty of audio
8. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as wdt/p): the place where the person is or has been, resident, subproperty of location
9. place of birth, also known as location born, POB, location of birth, born in, born at (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, subproperty of location
10. instance of, also known as example of, has type, is a, is an, is of type (wd:P31 as wdt/p): type to which this subject corresponds/belongs. Different from P...tains, and the volcano is a type (instance) of volcanic landform

No other items found

[Assistant] The property "native language" (wdt:P103) corresponds to mother tongue or first language. Now I will write a SPARQL query to get the native language(s) of Chimamanda Ngozi Adichie (wd:Q230141).

[Tool]
Got 1 row and 2 columns:
| language         | languageLabel |
| ---------------- | ------------- |
| Igbo (wd:Q33578) | Igbo (en)     |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?album ?albumLabel ?releaseDate WHERE {
  ?album wdt:P31 wd:Q482994 ; wdt:P175 wd:Q7861093 ; wdt:P577 ?releaseDate .
  OPTIONAL {
    ?album rdfs:label ?albumLabel FILTER ( LANG( ?albumLabel ) = "en" )
  }
}
ORDER BY ?releaseDate
LIMIT 1

The first album of the American band Typhoon is "Hunger and Thirst," which was released in 2010.

When was the first album of the American band Typhoon released?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] When was the first album of the American band Typhoon released?

[Assistant]
Step 1: Identify the entity "Typhoon" as an American band and find its corresponding entity in Wikidata. Then identify the property for "first album" and its release date.

I will start by searching for the entity "Typhoon" with the context of being an American band.

[Tool]
Top 10 entity alternatives:
1. American Band (wd:Q28452209): album by Drive-By Truckers, instance of album
2. American band (wd:L323438-S1)
3. American Bandstand, also known as AB (wd:Q463447): American TV program featured music-performances and dance television show, instance of television series
4. Swinford Bandog, also known as American Bandogge, American Bandog (wd:Q11044643)
5. Cain, also known as Cain (American band) (wd:Q106707194): instance of musical group, Christian country group
6. Native American tribe, also known as Native American band, Native American nation, Indian tribe, tribe (Native American), American Indian tribe (wd:Q12885585)
7. Weekend, also known as Abe Pedroza, Kevin Johnson, Shaun Durkan, Weekend (American band) (wd:Q7979408): instance of musical group, American band
8. The American Band (wd:Q16147404): instance of musical group, US musical group
9. American Bandstand (wd:Q4743125): album by Wayne Horvitz, instance of album
10. Culture, also known as X culture X, xCulturex, Culture (American band) (wd:Q94579151): American vegan/straight-edge metalcore band, instance of musical group

[Tool]
Top 10 entity alternatives:
1. Eurofighter Typhoon, also known as Eurofighter EF-2000, Typhoon, EF2000, Typhoon aircraft, EF-2000 (wd:Q151384)
2. musical group, also known as band, music group, music band, musical project, musical band (wd:Q215380)
3. typhoon (wd:Q140588)
4. The Band, also known as The Ron Hawkins Quartet, The Levon Helm Sextet, The Honkies, The Crackers, The Hawks (wd:Q600344): Canadian-American musical group; rock band, instance of musical group
5. ribbon, also known as ribbon (material), riband (ribbon), riband ribbon, ribbon material, narrowware (wd:Q6918773)
6. Typhoon, also known as Typhoon aircraft, Typhoon fighter-bomber, Typhoon IB, Tiffy, Hawker Typhoon (wd:Q662123)
7. Band (wd:Q12080772): commune in Mureş County, Romania, instance of commune of Romania
8. Band, also known as Rede Bandeirantes (wd:Q2713068): Brazilian commercial broadcast television network, instance of television network
9. Bánd, also known as Band (wd:Q580946): instance of municipality of Hungary, village in Hungary
10. chambranle, also known as band, window-frame, mantle-tree, frame, door-case (wd:Q1753397)

[Tool]
Top 10 entity alternatives:
1. American Band (wd:Q28452209): album by Drive-By Truckers, instance of album
2. American band (wd:L323438-S1)
3. American Bandstand, also known as AB (wd:Q463447): American TV program featured music-performances and dance television show, instance of television series
4. Swinford Bandog, also known as American Bandogge, American Bandog (wd:Q11044643)
5. Cain, also known as Cain (American band) (wd:Q106707194): instance of musical group, Christian country group
6. Native American tribe, also known as Native American band, Native American nation, Indian tribe, tribe (Native American), American Indian tribe (wd:Q12885585)
7. Weekend, also known as Abe Pedroza, Kevin Johnson, Shaun Durkan, Weekend (American band) (wd:Q7979408): instance of musical group, American band
8. The American Band (wd:Q16147404): instance of musical group, US musical group
9. American Bandstand (wd:Q4743125): album by Wayne Horvitz, instance of album
10. Culture, also known as X culture X, xCulturex, Culture (American band) (wd:Q94579151): American vegan/straight-edge metalcore band, instance of musical group

[Tool]
Top 10 entity alternatives:
1. Eurofighter Typhoon, also known as Eurofighter EF-2000, Typhoon, EF2000, Typhoon aircraft, EF-2000 (wd:Q151384)
2. musical group, also known as band, music group, music band, musical project, musical band (wd:Q215380)
3. typhoon (wd:Q140588)
4. The Band, also known as The Ron Hawkins Quartet, The Levon Helm Sextet, The Honkies, The Crackers, The Hawks (wd:Q600344): Canadian-American musical group; rock band, instance of musical group
5. ribbon, also known as ribbon (material), riband (ribbon), riband ribbon, ribbon material, narrowware (wd:Q6918773)
6. Typhoon, also known as Typhoon aircraft, Typhoon fighter-bomber, Typhoon IB, Tiffy, Hawker Typhoon (wd:Q662123)
7. Band (wd:Q12080772): commune in Mureş County, Romania, instance of commune of Romania
8. Band, also known as Rede Bandeirantes (wd:Q2713068): Brazilian commercial broadcast television network, instance of television network
9. Bánd, also known as Band (wd:Q580946): instance of municipality of Hungary, village in Hungary
10. chambranle, also known as band, window-frame, mantle-tree, frame, door-case (wd:Q1753397)

[Tool]
Top 10 entity alternatives:
1. Eurofighter Typhoon, also known as Eurofighter EF-2000, Typhoon, EF2000, Typhoon aircraft, EF-2000 (wd:Q151384)
2. musical group, also known as band, music group, music band, musical project, musical band (wd:Q215380)
3. typhoon (wd:Q140588)
4. The Band, also known as The Ron Hawkins Quartet, The Levon Helm Sextet, The Honkies, The Crackers, The Hawks (wd:Q600344): Canadian-American musical group; rock band, instance of musical group
5. ribbon, also known as ribbon (material), riband (ribbon), riband ribbon, ribbon material, narrowware (wd:Q6918773)
6. Typhoon, also known as Typhoon aircraft, Typhoon fighter-bomber, Typhoon IB, Tiffy, Hawker Typhoon (wd:Q662123)
7. Band (wd:Q12080772): commune in Mureş County, Romania, instance of commune of Romania
8. Band, also known as Rede Bandeirantes (wd:Q2713068): Brazilian commercial broadcast television network, instance of television network
9. Bánd, also known as Band (wd:Q580946): instance of municipality of Hungary, village in Hungary
10. chambranle, also known as band, window-frame, mantle-tree, frame, door-case (wd:Q1753397)

[Tool]
Top 10 entity alternatives:
1. indie rock, also known as independent rock, indie rock music (wd:Q183504)
2. rock band, also known as rock music group, rock music band, rock group (wd:Q5741069)
3. Rock Band (wd:Q1195153): instance of video game, 2007 video game
4. Rock Band (wd:Q2323659): instance of video game series, series of music video games
5. American rock, also known as American rock music (wd:Q3437802)
6. American Band (wd:Q28452209): album by Drive-By Truckers, instance of album
7. Rock Band (wd:Q7354280): instance of video game, 2009 video game
8. American Rock (wd:Q22404180): shoal in Newfoundland and Labrador, Canada, instance of shoal
9. Band Rock (wd:Q49010609): mountain in Pennsylvania, United States of America, instance of mountain
10. American rock (wd:Q58985096): scientific article published in Nature, instance of scholarly article

[Tool]
Top 10 entity alternatives:
1. indie rock, also known as independent rock, indie rock music (wd:Q183504)
2. rock band, also known as rock music group, rock music band, rock group (wd:Q5741069)
3. Rock Band (wd:Q1195153): instance of video game, 2007 video game
4. Rock Band (wd:Q2323659): instance of video game series, series of music video games
5. Rock Band (wd:Q7354280): instance of video game, 2009 video game
6. Band Rock (wd:Q49010609): mountain in Pennsylvania, United States of America, instance of mountain
7. Rock Band, also known as xkcd 359 (wd:Q18613846): 359th strip of the webcomic xkcd, instance of comic strip
8. Rock Band (wd:Q131115226): scientific article published on 25 September 2009, instance of scholarly article
9. indie rock (wd:L1218127-S1)
10. indie rock (wd:L1218128-S1)

[Tool]
Top 10 entity alternatives:
1. Portland, also known as Portland, OR, Portland, Oregon, City of Roses, Rip City, Rose City (wd:Q6106): city and county seat of Multnomah County, Oregon, United States, instance of city of Oregon, instance of county seat, instance of big city
2. Portland, also known as Portland Maine, Portland, Maine, Portland, ME (wd:Q49201): county seat of Cumberland County, Maine, United States, instance of city in the United States, instance of county seat
3. Eurofighter Typhoon, also known as Eurofighter EF-2000, Typhoon, EF2000, Typhoon aircraft, EF-2000 (wd:Q151384)
4. musical group, also known as band, music group, music band, musical project, musical band (wd:Q215380)
5. typhoon (wd:Q140588)
6. The Band, also known as The Ron Hawkins Quartet, The Levon Helm Sextet, The Honkies, The Crackers, The Hawks (wd:Q600344): Canadian-American musical group; rock band, instance of musical group
7. Portland, also known as Portland, Indiana, Portland, IN (wd:Q1807259): city and county seat of Jay County, State of Indiana, United States, instance of city in the United States, instance of county seat
8. Portland, also known as Portland, AR, Portland, Arkansas (wd:Q80163): instance of city in the United States, city in Arkansas, USA
9. Portland, also known as Portland, Texas, Portland, TX (wd:Q980152): instance of city in the United States, city in Texas, United States
10. ribbon, also known as ribbon (material), riband (ribbon), riband ribbon, ribbon material, narrowware (wd:Q6918773)

[Tool] Got no rows and 1 columns

[Tool]
Got 10 rows and 2 columns:
| band                  | bandLabel     |
| --------------------- | ------------- |
| Typhoon (wd:Q7861093) | Typhoon (ast) |
| Typhoon (wd:Q7861093) | Typhoon (ca)  |
| Typhoon (wd:Q7861093) | Typhoon (da)  |
| Typhoon (wd:Q7861093) | Typhoon (de)  |
| Typhoon (wd:Q7861093) | Typhoon (en)  |
| Typhoon (wd:Q7861093) | Typhoon (es)  |
| Typhoon (wd:Q7861093) | Typhoon (eu)  |
| Typhoon (wd:Q7861093) | Typhoon (fi)  |
| Typhoon (wd:Q7861093) | Typhoon (fr)  |
| Typhoon (wd:Q7861093) | Typhoon (ga)  |

[Assistant] I found the entity for the American band Typhoon: wd:Q7861093. Now I will look for the albums of this band and their release dates to find the first album and its release date.

[Tool]
Got 1 row and 3 columns:
| album                            | albumLabel             | releaseDate                         |
| -------------------------------- | ---------------------- | ----------------------------------- |
| Hunger and Thirst (wd:Q48967126) | Hunger and Thirst (en) | 2010-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?property ?propertyLabel WHERE {
  wd:Q143276 ?property ?value .
  ?property rdfs:label ?propertyLabel
  FILTER ( LANG( ?propertyLabel ) = "en" ) FILTER ( CONTAINS( LCASE( ?propertyLabel ) , "based on" ) || CONTAINS( LCASE( ?propertyLabel ) , "adaptation" ) || CONTAINS( LCASE( ?propertyLabel ) , "derivative" ) )
}
LIMIT 10

Samurai Champloo (wd:Q143276) does not have any properties indicating it is based on or adapted from another work in Wikidata. Therefore, it is a piece of original work.

Is samurai champloo a piece of original work or an adaptation?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] Is samurai champloo a piece of original work or an adaptation?

[Assistant]
To answer whether "Samurai Champloo" is a piece of original work or an adaptation, I need to find the entity for "Samurai Champloo" in Wikidata and then check its properties related to origin or adaptation. Typically, properties like "based on" (P144) or "adaptation of" can indicate if it is an adaptation. If these properties are absent, it is likely an original work.

Step 1: Search for the entity "Samurai Champloo" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Samurai Champloo (wd:Q143276): instance of anime television series, Japanese anime television series
2. Samurai Champloo (wd:Q66138325): instance of manga series, Japanese manga series
3. Samurai Champloo: Sidetracked, also known as Samurai Champloo HIPHOP Samurai Action (wd:Q3548610): instance of video game, 2006 video game
4. Samurai Champloo soundtrack releases, also known as Music of Samurai Champloo (wd:Q106856784): instance of Wikipedia article covering multiple soundtrack releases, Wikipedia article covering multiple soundtrack releases
5. Samurai Champloo Music Record: Departure, also known as Departure (wd:Q7413091): 2004 soundtrack album by Nujabes / Fat Jon, instance of album
6. Samurai Champloo Music Record: Playlist (wd:Q104829743): 2004 soundtrack album by tsutchie, instance of album
7. Samurai Champloo Music Record: Masta, also known as Masta (wd:Q104829750): 2004 soundtrack album by FORCE OF NATURE / tsutchie, instance of album
8. Samurai Champloo Music Record: Impression, also known as Impression (wd:Q3149468): 2004 soundtrack album by Force of Nature / Nujabes / Fat Jon, instance of album
9. Postmodern Is Old Hat: Samurai Champloo (wd:Q56608596): instance of scholarly article, article
10. samurai, also known as buke, bushi (wd:Q38142)

[Assistant] I found the entity for "Samurai Champloo" as an anime television series with the identifier wd:Q143276. Next, I will check if this entity has any properties indicating it is based on or adapted from another work. Specifically, I will look for properties like "based on" (P144) or similar.

[Tool] Got no rows and 3 columns

[Assistant] The entity for "Samurai Champloo" (wd:Q143276) does not have a "based on" (P144) property, which suggests it is not an adaptation of another work. To further confirm, I will check if there are any other properties indicating it is an adaptation or based on another work. I will search for properties related to adaptation or original work for this entity.

[Tool]
Top 10 property alternatives:
1. derivative work, also known as is source work of, is the basis for, iteration, reboot, remake (wd:P4969 as wdt/p): new work of art (film, book, software, etc.) derived from major part of this work
2. end time, also known as ends, to, endtime, fall date, ineffective (wd:P582 as wdt/p): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, subproperty of point in time
3. set in period, also known as set in, set in era, set in time, setting, significant event (wd:P2408 as wdt/p): historical, contemporary, or future period, year, century or day...rk or genre is set in or event featured in the story of the work
4. start time, also known as start date, since, join time, joined, join date (wd:P580 as wdt/p): time an entity begins to exist or a statement starts being valid, subproperty of point in time
5. has characteristic, also known as trait, has quality, inherent property, object has characteristic, parameter (wd:P1552 as wdt/p): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
6. distribution format, also known as media format, media type, medium, method of distribution, publication format (wd:P437 as wdt/p): method (or type) of distribution for the subject
7. duration, also known as timespan, era, time span, time length, time interval (wd:P2047 as wdt/p): length of time of an event or process
8. Freebase ID, also known as FID, Freebase, Freebase identifier, MID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
9. genre, also known as type of music, type of film, music genre, literary genre, kind of music (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
10. title, also known as page name, titled, original title, name, known as (wd:P1476 as wdt/p): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, subproperty of name

No other items found

[Assistant] There are no properties directly indicating that "Samurai Champloo" is an adaptation or derivative work. To be thorough, I will also check if there is a property "original work" or something similar that might indicate it is an original creation. I will search for properties related to "original" for this entity.

[Tool]
Top 10 property alternatives:
1. original language of film or TV show, also known as original language, language of the original work, media language, created on language (wd:P364 as wdt/p): language in which a film or a performance work was originally cr... works and songs; use P407 ("language of work or name") instead., subproperty of language of work or name
2. title, also known as page name, titled, original title, name, known as (wd:P1476 as wdt/p): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, subproperty of name
3. original broadcaster, also known as original channel, original network, radio network, radio station, television channel (wd:P449 as wdt/p): network(s) or service(s) that originally broadcast a radio or television program, subproperty of broadcast by
4. derivative work, also known as is source work of, is the basis for, iteration, reboot, remake (wd:P4969 as wdt/p): new work of art (film, book, software, etc.) derived from major part of this work
5. country of origin, also known as comes from, place of origin, origin country, originates from, country (wd:P495 as wdt/p): country of origin of this item (creative work, food, phrase, product, etc.), subproperty of significant place, subproperty of country
6. distribution format, also known as media format, media type, medium, method of distribution, publication format (wd:P437 as wdt/p): method (or type) of distribution for the subject
7. instance of, also known as example of, has type, is a, is an, is of type (wd:P31 as wdt/p): type to which this subject corresponds/belongs. Different from P...tains, and the volcano is a type (instance) of volcanic landform
8. has part(s), also known as has ingredient, has ingredients, had part, has member, has part (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
9. start time, also known as start date, since, join time, joined, join date (wd:P580 as wdt/p): time an entity begins to exist or a statement starts being valid, subproperty of point in time
10. genre, also known as type of music, type of film, music genre, literary genre, kind of music (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic

No other items found

[Assistant]
There are no properties indicating that "Samurai Champloo" is an adaptation or derivative work. The absence of a "based on" or similar property suggests that "Samurai Champloo" is an original work.

I will now finalize the answer.

[Tool] Stopped generation process