PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?school ?schoolLabel WHERE {
  wd:Q40224 wdt:P69 ?school .
  OPTIONAL {
    ?school rdfs:label ?schoolLabel FILTER ( LANG( ?schoolLabel ) = "en" )
  }
}

Karl Benz attended the University of Karlsruhe.

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

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

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

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

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

[User] what school did karl benz go to?

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

[Tool]
Example 1:
Question:
what year did michael jordan started his career?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q41421 wdt:P2031 ?x .
}

Using entities:
Michael Jordan, also known as His Airness, Air Jordan (wd:Q41421): American basketball player and businessman (born 1963), basketball player, baseball player, autobiographer, spokesperson, entrepreneur

Using properties:
work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit

Example 2:
Question:
what currency do they accept in kenya?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q114 wdt:P38 ?x .
}

Using entities:
Kenya, also known as ke, Republic of Kenya, KEN, KE (wd:Q114): country in Eastern Africa

Using properties:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

Example 3:
Question:
who plays jacob black in twilight?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q160071 p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q716835 .
}

Using entities:
Twilight (wd:Q160071): 2008 American film directed by Catherine Hardwicke
Jacob Black (wd:Q716835): character from Twilight, vampire hunter, mechanic, student

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

[Assistant] The question is about the school Karl Benz attended. We need to find the entity for Karl Benz and then find a property related to education or school attended. Let's first search for the entity "Karl Benz" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Carl Benz, also known as Carl Friedrich Benz, Karl Friedrich Benz, Karl Benz, Karl Friedrich Michael Vaillant (wd:Q40224): automotive and engine designer and manufacturer (1844–1929), engineer, inventor
2. Carl Benz, also known as Karl Friedrich Michael Vaillant, Karl Friedrich Benz, Karl Benz, Carl Friedrich Benz (wd:Q40224): automotive and engine designer and manufacturer (1844–1929), inventor, engineer
3. Willibrord Benzler, also known as Karl Benzler, Karl Heinrich Johann Eugen Benzler (wd:Q91025): bishop of Metz (1853–1921), Catholic priest, Catholic bishop
4. Károly Benza, also known as Karl Benza (wd:Q20667635): Hungarian actor, singer and director, director, singer, actor
5. Karl Benz (Landrat) (wd:Q104163395): jurist
6. Karl Josef Benz (wd:Q51682510): liturgist
7. Karl Benziger (wd:Q1730468): Swiss politician and publisher (1799-1873), politician, publisher
8. Karl Benzon (wd:Q17370389): Swedish journalist, journalist, translator
9. Karl Benzino (wd:Q94858455): politician, jurist, judge
10. Karl Benzel (wd:Q60835293): (1778-1802), robber

[Assistant] The most relevant entity for Karl Benz is "Carl Benz" with the Wikidata ID wd:Q40224. Now, I will search for properties related to education or school attended for this entity.

[Tool]
Top 10 property alternatives:
1. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
2. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
3. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
4. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
5. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
6. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
7. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as p/wdt): the place where the person is or has been, resident, location
8. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
9. described at URL, also known as mentioned at URL, descURL, described on webpage, discussed at URL, d@url (wd:P973 as p/wdt): item is described at the following URL, URL
10. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as p/wdt): full name of a person at birth, if different from their current, generally used name, name

No other items found

[Assistant] The property "educated at" (wdt:P69) is the relevant property for the school or educational institution attended by Karl Benz. Now I will write a SPARQL query to find the school Karl Benz attended using this property.

[Tool]
Got 1 row and 2 columns:
| school                                 | schoolLabel                  |
| -------------------------------------- | ---------------------------- |
| University of Karlsruhe (wd:Q29426438) | University of Karlsruhe (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the educational institution attended by Karl Benz using the property 'educated at' (wdt:P69). The query returns the University of Karlsruhe as the school Karl Benz attended, which matches the provided answer. The query also includes an optional clause to get the English label of the school, which is helpful for readability. The output is accurate and complete for the user's question.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?genre ?genreLabel WHERE {
  wd:Q4700 wdt:P136 ?genre .
  OPTIONAL {
    ?genre rdfs:label ?genreLabel FILTER ( LANG( ?genreLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| genre                               | genreLabel               |
| ----------------------------------- | ------------------------ |
| impressionist music (wd:Q105697765) | impressionist music (en) |
| opera (wd:Q1344)                    | opera (en)               |
| classical music (wd:Q9730)          | classical music (en)     |

Claude Debussy played impressionist music, opera, and classical music.

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

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

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

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

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

[User] what type of music did claude debussy play?

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

[Tool]
Example 1:
Question:
what is there to do around austin texas?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q570116 ; wdt:P131 wd:Q16559 .
}

Using entities:
Austin, also known as Austin, Texas, Austin, TX (wd:Q16559): city in and county seat of Travis County, Texas, United States, that is also the capital of the State of Texas
tourist attraction, also known as attraction for tourists, POI for tourists, tourism attraction, touristic attraction, tourist place (wd:Q570116): place of interest where tourists visit

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
what to do in panama city beach fl?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q570116 ; wdt:P131 wd:Q1075852 .
}

Using entities:
Panama City Beach, also known as Panama City Beach, FL, Panama City Beach, Florida (wd:Q1075852): city in Bay County, Florida, United States
tourist attraction, also known as attraction for tourists, POI for tourists, tourism attraction, touristic attraction, tourist place (wd:Q570116): place of interest where tourists visit

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
what are major religions in the united states?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q30 wdt:P140 ?x .
}

Using entities:
United States, also known as the U.S. of A, United States of America, the US of America, United States of North America, U. S. (wd:Q30): country primarily located in North America

Using properties:
religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as wdt): religion of a person, organization or religious building, or associated with this subject

[Assistant] The examples did not directly relate to music or Claude Debussy, so I will now search for the entity "Claude Debussy" in Wikidata to get his identifier.

[Tool]
Top 10 entity alternatives:
1. Claude Debussy, also known as C. Debussy, Achille-Claude, Claude Achille Debussy, Claude-Achille Debussy, Debussy (wd:Q4700): French classical composer (1862–1918), music critic, composer, pianist
2. Claude Debussy (wd:Q17491085): painting by Marcel Baschet
3. Musée Claude-Debussy, also known as Claude Debussy Museum, Maison Claude Debussy (wd:Q19387976): museum in France
4. Claude Debussylaan (wd:Q18980854): street in Amsterdam, the Netherlands
5. allée Claude Debussy (wd:Q121600379): alley of Châtillon, in Hauts-de-Seine
6. allée Claude Debussy (wd:Q116242003): alley in Châtenay-Malabry, France
7. allée Claude Debussy (wd:Q113455135): alley in Clichy-sous-Bois, France
8. allée Claude Debussy (wd:Q113413920): alley in Villetaneuse, en Seine-Saint-Denis
9. allée Claude Debussy (wd:Q112064008): alley in L'Haÿ-les-Roses, France
10. allée Claude Debussy (wd:Q111916504): alley in Valenton, France

[Assistant] Claude Debussy is identified as wd:Q4700 in Wikidata. Now I will search for the property that relates to the type or genre of music he played. I will search for properties related to "music genre" or "musical style" for this entity.

[Tool]
Top 10 property alternatives:
1. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
2. movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as p/wdt): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.
3. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as p/wdt): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
4. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as p/wdt): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
5. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as p/wdt): musical instrument that a person plays or teaches or used in a music occupation, uses
6. Apple Music artist ID (U.S. version), also known as iTunes author ID, music.apple.com/artist/, iTunes artist ID (American version), https://music.apple.com/artist/, Apple Music artist ID (American version) (wd:P2850 as p/wdt): identifier for a musical artist or author in the U.S. version of Apple Music
7. MusicBrainz artist ID, also known as MB artist ID, MBID artist (wd:P434 as wdt/p/wdtn): identifier for an artist in the MusicBrainz open music encyclopedia
8. Songfacts artist ID (wd:P5287 as p/wdt): identifier for an artist on the Songfacts website
9. Last.fm ID, also known as Lastfm ID, Last FM ID, LastFM music ID (wd:P3192 as p/wdt): identifier for an artist, group or work, on Last.fm
10. DR music artist ID, also known as DR ID, DR.dk ID (wd:P8041 as p/wdt): identifier for an artist on DR site

No other items found

[Assistant] The property "genre" (wdt:P136) is the most relevant property for the type or genre of music. I will now query the genre of music associated with Claude Debussy (wd:Q4700).

[Tool]
Got 3 rows and 2 columns:
| genre                               | genreLabel               |
| ----------------------------------- | ------------------------ |
| impressionist music (wd:Q105697765) | impressionist music (en) |
| opera (wd:Q1344)                    | opera (en)               |
| classical music (wd:Q9730)          | classical music (en)     |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the music genres associated with Claude Debussy using the property 'genre' (wdt:P136). The query returns the expected genres: impressionist music, opera, and classical music, which are accurate and relevant to the question. The inclusion of labels in English is helpful for readability. The answer is complete and correctly reflects the data from Wikidata. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?case ?caseLabel WHERE {
  ?case wdt:P31 wd:Q19692072 .
  ?case rdfs:label ?caseLabel .
  FILTER ( LANG( ?caseLabel ) = "en" )
}
LIMIT 50

Got 50 rows and 2 columns, showing the first 5 and last 5 rows below:
| case                                                                     | caseLabel                                                     |
| ------------------------------------------------------------------------ | ------------------------------------------------------------- |
| Trump v. New York (wd:Q100496432)                                        | Trump v. New York (en)                                        |
| New Hampshire v. Maine (wd:Q101093598)                                   | New Hampshire v. Maine (en)                                   |
| Roman Catholic Diocese of Brooklyn v. Cuomo (wd:Q102532067)              | Roman Catholic Diocese of Brooklyn v. Cuomo (en)              |
| EEOC v. Wyoming (wd:Q104672335)                                          | EEOC v. Wyoming (en)                                          |
| Bogan v. Scott-Harris (wd:Q104821362)                                    | Bogan v. Scott-Harris (en)                                    |
| ...                                                                      | ...                                                           |
| Ford Motor Co. v. Montana Eighth Judicial Dist. (wd:Q106609883)          | Ford Motor Co. v. Montana Eighth Judicial Dist. (en)          |
| New York State Rifle & Pistol Association, Inc. v. Bruen (wd:Q106626962) | New York State Rifle & Pistol Association, Inc. v. Bruen (en) |
| Nautilus, Inc. v. Biosig Instruments, Inc. (wd:Q106679587)               | Nautilus, Inc. v. Biosig Instruments, Inc. (en)               |
| AMG Capital Management, LLC v. FTC (wd:Q106742479)                       | AMG Capital Management, LLC v. FTC (en)                       |
| Americans for Prosperity Foundation v. Bonta (wd:Q106819213)             | Americans for Prosperity Foundation v. Bonta (en)             |

These are some United States Supreme Court cases (decisions rendered by the highest court of the United States) retrieved from Wikidata.

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

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

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

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

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

[User] what are the supreme court cases?

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

[Tool]
Example 1:
Question:
who is leann rimes with now?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q120533 wdt:P26 ?x .
}

Using entities:
LeAnn Rimes, also known as LeAnn Rimes Cibrian, Margaret LeAnn Rimes Cibrian, Margaret LeAnn Rimes (wd:Q120533): American singer and actress (born 1982), songwriter, singer, actor

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

Example 2:
Question:
what to do around krabi thailand?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q570116 ; wdt:P131 wd:Q1000353 .
}

Using entities:
Krabi (wd:Q1000353): town in Krabi province, Thailand
tourist attraction, also known as attraction for tourists, POI for tourists, tourism attraction, touristic attraction, tourist place (wd:Q570116): place of interest where tourists visit

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
what is the main language spoken in switzerland?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q39 wdt:P37 ?x .
}

Using entities:
Switzerland, also known as Confoederatio Helvetica, Swiss, Swiss Confederation (wd:Q39): country in Central Europe

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

[Assistant]
The question "what are the supreme court cases?" is quite broad. Supreme Court cases are legal cases decided by a Supreme Court, typically the highest judicial body in a country. To answer this question, I need to identify entities related to "Supreme Court cases."

Step 1: Identify the entity for "Supreme Court case" in Wikidata.
Step 2: Retrieve instances of this entity or related entities.

I will start by searching for the entity "Supreme Court case" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. ELUFIOYE AND 9 OTHERS v HALILU AND 17 OTHERS, also known as Supreme Court case (wd:Q125556110): supreme court case between Elufloye and 9 others and Halilu and 17 others
2. FEDERAL REPUBLIC OF NIGERIA v T. A. DAIRO & Others, also known as Supreme court case (wd:Q125658363): Federal government in court with T.A. Dairo & others.
3. Salihu v Wasiu, also known as Supreme court case (wd:Q125403314): Supreme Court case between Salihu v Wasiu
4. Nsirim v Dr. Amadi ( SC.40/2005) [2016] NGSC 67 (21 January 2016), also known as Nigeria supreme court case (wd:Q125415178): a Nigeria  supreme Court cases
5. Nevada Supreme Court decision, also known as Nevada Supreme Court case (wd:Q121470056): decision rendered by the highest court of Nevada
6. United States Supreme Court decision, also known as Supreme Court decision, US Supreme Court cases, US Supreme Court case, United States Supreme Court case, United States Supreme Court cases (wd:Q19692072): decision rendered by the highest court of the United States
7. Supreme Court Case Selections Act, also known as Supreme Court Case Selections Act of 1988 (wd:Q7644854): 1988 U.S. law removing some appeals-by-right to the Supreme Court
8. Monkey case in Supreme Court (wd:Q59013757): scientific article published in Nature
9. Seed-patent case in Supreme Court (wd:Q74202143): journal article; published in Nature on 2013-02-19
10. Supreme court of Nigeria case (wd:Q125677284)

[Assistant]
There are multiple entities for specific Supreme Court cases and some general entities like "United States Supreme Court decision" (wd:Q19692072) which represents decisions rendered by the highest court of the United States.

To answer the question broadly about Supreme Court cases, it would be appropriate to consider instances of the entity "United States Supreme Court decision" or similar entities representing Supreme Court cases.

Next, I will check if there is a general class or category for Supreme Court cases and then retrieve some examples of such cases. I will look for subclasses or instances of "United States Supreme Court decision" (wd:Q19692072).

[Tool] Got no rows and 3 columns

[Assistant] There are no direct instances of "United States Supreme Court decision" (wd:Q19692072) using the property "instance of" (wdt:P31). I will try to find subclasses of this entity to see if there are more specific categories of Supreme Court cases.

[Tool] Got no rows and 3 columns

[Assistant]
There are no subclasses of "United States Supreme Court decision" (wd:Q19692072) using the property "subclass of" (wdt:P279).

I will now try to find instances of Supreme Court cases more generally by searching for entities that are instances of "court case" or similar and have a relation to "Supreme Court."

I will start by searching for the entity "court case" to find a general class for court cases.

[Tool]
Top 10 entity alternatives:
1. legal case, also known as court action, court case, legal conflict, legal dispute, legal issue (wd:Q2334719): dispute resolved by a court
2. ALHAJI NURUDEEN OLUFUNMISE v MRS. ABIOLA LABINJOH FALANA, also known as Court case (wd:Q125555447): a case between Alhaji Nurudeen Olufunmise and Mrs. Abiola Labinjoh Falana in the supreme court of Nigeria.
3. GOVERNOR OF ZAMFARA STATE & Othe...GHirnor vs Yongo (2023) & Others, also known as Court case (wd:Q125634982): Zamfara State Government and others in court with individuals.
4. Monier Construction Company Ltd v Tobias I. Azubuike, also known as Court case (wd:Q125570224): supreme court case on plaintiffs damages
5. MUSTAPHA ABOABA JIMOH SHOTUNWA KAFARU OSHUGBO v D.B. KALAIWO, also known as Court case (wd:Q125537465): a case between Mustapha Aboaba Jimoh Shotunwa Kafaru Oshugbo and D.B. Kalaiwo
6. NATIONAL BANK OF NIG. LIMITED & ...OHN AKINIKUNMI SHOYOYE & Another, also known as Court case (wd:Q125556441): supreme Court case on 27 May 1977
7. THOMAS E. DOWLING v INSPECTOR-GENERAL OF POLICE, also known as Court case (wd:Q125536984): a Supreme court case between Thomas E. Dowling and the inspector general of police
8. SIMPLICIO KUFEJI v A. KOGBE, also known as Court case (wd:Q125545276): a case in High Court of Lagos State of Nigeria.
9. long-running court case (wd:Q11653052)
10. Caseley Court (wd:Q17535983): thatched cottage in Lustleigh, Teignbridge, England, UK

[Assistant]
The general entity for court cases is "legal case" (wd:Q2334719), which is described as a dispute resolved by a court.

Next, I will try to find instances of legal cases that are specifically Supreme Court cases. I will look for legal cases that have a property indicating they are related to a Supreme Court. For this, I will search for properties related to "Supreme Court" for the entity "legal case" (wd:Q2334719).

[Tool]
Top 10 property alternatives:
1. said to be the same as, also known as may be, the same as, synonymous with, same as, same (wd:P460 as p/wdt): this item is said to be the same as that item, though this may be uncertain or disputed
2. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
5. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as p/wdt): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
6. equivalent class, also known as schema.org type, same kind of thing, same grouping, same class, external class (wd:P1709 as p/wdt): equivalent class in other ontologies (use property URI), exact match, URL
7. properties for this type, also known as uses properties, Wikidata properties for this type, Wikidata properties for this class, uses property, things one could say about (wd:P1963 as p/wdt): when this subject is used as object of “instance of”, the following properties normally apply
8. exact match, also known as owl:sameAs, the same as, skos:exactMatch, same meaning, sameas (wd:P2888 as p/wdt): URL used to link two items or properties, indicating a high degree of confidence that the concepts can be used interchangeably
9. different from, also known as not to be confused with, to be distinguished from, similar to, see also, rejected match (wd:P1889 as p/wdt): item that is different from another item, with which it may be confused
10. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).

No other items found

[Assistant]
There are no specific properties directly linking legal cases to Supreme Court in the property search for the entity "legal case" (wd:Q2334719).

I will try a different approach: I will search for instances of "legal case" (wd:Q2334719) that have "Supreme Court" mentioned in their labels or descriptions. This might help find Supreme Court cases more directly.

I will search for entities with the keyword "Supreme Court case" to find relevant instances.

[Tool]
Top 10 entity alternatives:
1. ELUFIOYE AND 9 OTHERS v HALILU AND 17 OTHERS, also known as Supreme Court case (wd:Q125556110): supreme court case between Elufloye and 9 others and Halilu and 17 others
2. FEDERAL REPUBLIC OF NIGERIA v T. A. DAIRO & Others, also known as Supreme court case (wd:Q125658363): Federal government in court with T.A. Dairo & others.
3. Salihu v Wasiu, also known as Supreme court case (wd:Q125403314): Supreme Court case between Salihu v Wasiu
4. Nsirim v Dr. Amadi ( SC.40/2005) [2016] NGSC 67 (21 January 2016), also known as Nigeria supreme court case (wd:Q125415178): a Nigeria  supreme Court cases
5. Nevada Supreme Court decision, also known as Nevada Supreme Court case (wd:Q121470056): decision rendered by the highest court of Nevada
6. United States Supreme Court decision, also known as Supreme Court decision, US Supreme Court cases, US Supreme Court case, United States Supreme Court case, United States Supreme Court cases (wd:Q19692072): decision rendered by the highest court of the United States
7. Supreme Court Case Selections Act, also known as Supreme Court Case Selections Act of 1988 (wd:Q7644854): 1988 U.S. law removing some appeals-by-right to the Supreme Court
8. Monkey case in Supreme Court (wd:Q59013757): scientific article published in Nature
9. Seed-patent case in Supreme Court (wd:Q74202143): journal article; published in Nature on 2013-02-19
10. Supreme court of Nigeria case (wd:Q125677284)

[Assistant]
There are many specific Supreme Court cases as entities, but no direct general class with many instances.

To provide a meaningful answer, I will retrieve some examples of Supreme Court cases by searching for entities that have "Supreme Court case" in their label or description.

I will now write a SPARQL query to find entities with labels containing "Supreme Court case" and return their IRIs and labels.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
The query timed out, likely because searching labels with CONTAINS on the entire dataset is expensive.

I will try a different approach: I will query for entities that are instances of "legal case" (wd:Q2334719) and have "Supreme Court" in their label. This should narrow down the search and be more efficient.

[Tool]
Got 15 rows and 2 columns, showing the first 5 and last 5 rows below:
| case                                                                                | caseLabel                                                                |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| Supreme Court petitions to nulli...Philippine presidential election (wd:Q130271352) | Supreme Court petitions to nulli...Philippine presidential election (en) |
| Mitchell v. Supreme Court of Florida (wd:Q19048766)                                 | Mitchell v. Supreme Court of Florida (en)                                |
| Duke v. Committee Grievances of ...ourt of the District of Columbia (wd:Q19088719)  | Duke v. Committee Grievances of ...ourt of the District of Columbia (en) |
| Lists of United States Supreme Court cases by volume (wd:Q2864336)                  | Lists of United States Supreme Court cases by volume (en)                |
| wd:Q6602711                                                                         | list of United States Supreme Court cases by the Roberts Court (en)      |
| ...                                                                                | ...                                                                      |
| wd:Q6646863                                                                         | Lists of United States Supreme Court cases (en)                          |
| Landmark cases of the Supreme Court of Japan (wd:Q7389210)                          | Landmark cases of the Supreme Court of Japan (en)                        |
| 2019 Supreme Court verdict on Ayodhya dispute (wd:Q74332303)                        | 2019 Supreme Court verdict on Ayodhya dispute (en)                       |
| Supreme Court cases of the American Civil War (wd:Q7644868)                         | Supreme Court cases of the American Civil War (en)                       |
| wd:Q7892232                                                                         | United States Supreme Court cases involving mental health (en)           |

[Assistant]
I found several entities related to Supreme Court cases, including specific cases and lists of cases. Since the question is broad, I will provide a query that retrieves some Supreme Court cases (instances of legal cases with "Supreme Court" in their label) along with their labels.

Here is the SPARQL query that retrieves Supreme Court cases with their labels:

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query retrieves items that are instances of legal cases and have 'Supreme Court' in their English label. While this approach finds some relevant Supreme Court cases, it also returns lists of cases and other related items rather than individual Supreme Court cases only. To improve, the query should focus on legal cases that are specifically decided by a Supreme Court, for example by checking if the court involved is a Supreme Court (using a property like 'court' or 'decided by' linked to an entity that is a Supreme Court). This would yield more precise results of actual Supreme Court cases rather than lists or unrelated items. Also, the query currently returns only 20 results; consider increasing or removing the limit if more results are desired.

[Assistant]
Thank you for the feedback. To improve the query, I will focus on legal cases that are specifically decided by a Supreme Court. For this, I will look for legal cases (instances of wd:Q2334719) that have a property indicating the court that decided the case, and this court should be an instance or subclass of a Supreme Court.

Step 1: Identify the property used for the court that decided a case. Common properties could be "court" (wdt:P449) or "decided by" (wdt:P2860).
Step 2: Filter cases where the court is an instance or subclass of a Supreme Court (wd:Q7748).

I will first check the property "court" (wdt:P449) for some legal cases to see if it is used for the court that decided the case.

[Tool] Got no rows and 3 columns

[Assistant]
There are no triples with the property "court" (wdt:P449) and the object "legal case" (wd:Q2334719). This means "court" is not used as a property pointing to legal cases.

I will now check the property "decided by" (wdt:P2860) for legal cases.

[Tool] Got no rows and 3 columns

[Assistant]
There are no triples with the property "decided by" (wdt:P2860) and the object "legal case" (wd:Q2334719). This means "decided by" is not used as a property pointing to legal cases.

I will now try to find properties used for legal cases by searching for properties related to "court" for the entity "legal case" (wd:Q2334719). This might help identify the correct property to link a legal case to the court that decided it.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
3. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as p/wdt): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
4. properties for this type, also known as uses properties, Wikidata properties for this type, Wikidata properties for this class, uses property, things one could say about (wd:P1963 as p/wdt): when this subject is used as object of “instance of”, the following properties normally apply
5. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
6. said to be the same as, also known as may be, the same as, synonymous with, same as, same (wd:P460 as p/wdt): this item is said to be the same as that item, though this may be uncertain or disputed
7. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
8. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
9. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
10. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as wdt/p/wdtn): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)

No other items found

[Assistant]
There are no properties directly related to "court" for the entity "legal case" (wd:Q2334719).

I will try to find properties related to "decided" or "decision" for the entity "legal case" to identify the property linking a case to the court that decided it.

[Tool]
Top 10 property alternatives:
1. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
2. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
3. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as p/wdt): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
4. NDL Authority ID, also known as NDLSH (NDL Subject Headings), NDLNA (NDL Name Authority), NDLNAId, NDL identifier, NDL ID (wd:P349 as wdt/p/wdtn): identifier for authority control per the National Diet Library of Japan
5. properties for this type, also known as uses properties, Wikidata properties for this type, Wikidata properties for this class, uses property, things one could say about (wd:P1963 as p/wdt): when this subject is used as object of “instance of”, the following properties normally apply
6. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
7. different from, also known as not to be confused with, to be distinguished from, similar to, see also, rejected match (wd:P1889 as p/wdt): item that is different from another item, with which it may be confused
8. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
9. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
10. said to be the same as, also known as may be, the same as, synonymous with, same as, same (wd:P460 as p/wdt): this item is said to be the same as that item, though this may be uncertain or disputed

No other items found

[Assistant]
There are no properties directly related to "decided" or "decision" for the entity "legal case" (wd:Q2334719).

I will try a different approach: I will look for instances of "United States Supreme Court decision" (wd:Q19692072) which is a specific entity representing Supreme Court decisions in the US. This might give a more precise list of Supreme Court cases.

I will query for instances of "United States Supreme Court decision" (wd:Q19692072).

[Tool]
Got 50 rows and 2 columns, showing the first 5 and last 5 rows below:
| case                                                                     | caseLabel                                                     |
| ------------------------------------------------------------------------ | ------------------------------------------------------------- |
| Trump v. New York (wd:Q100496432)                                        | Trump v. New York (en)                                        |
| New Hampshire v. Maine (wd:Q101093598)                                   | New Hampshire v. Maine (en)                                   |
| Roman Catholic Diocese of Brooklyn v. Cuomo (wd:Q102532067)              | Roman Catholic Diocese of Brooklyn v. Cuomo (en)              |
| EEOC v. Wyoming (wd:Q104672335)                                          | EEOC v. Wyoming (en)                                          |
| Bogan v. Scott-Harris (wd:Q104821362)                                    | Bogan v. Scott-Harris (en)                                    |
| ...                                                                      | ...                                                           |
| Ford Motor Co. v. Montana Eighth Judicial Dist. (wd:Q106609883)          | Ford Motor Co. v. Montana Eighth Judicial Dist. (en)          |
| New York State Rifle & Pistol Association, Inc. v. Bruen (wd:Q106626962) | New York State Rifle & Pistol Association, Inc. v. Bruen (en) |
| Nautilus, Inc. v. Biosig Instruments, Inc. (wd:Q106679587)               | Nautilus, Inc. v. Biosig Instruments, Inc. (en)               |
| AMG Capital Management, LLC v. FTC (wd:Q106742479)                       | AMG Capital Management, LLC v. FTC (en)                       |
| Americans for Prosperity Foundation v. Bonta (wd:Q106819213)             | Americans for Prosperity Foundation v. Bonta (en)             |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves instances of United States Supreme Court decisions (wd:Q19692072) and their English labels, which directly answers the user's question about Supreme Court cases. The query respects the requirement to return identifiers and labels, and the result set includes relevant cases. The answer explanation is clear and concise. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?currency ?currencyLabel WHERE {
  wd:Q244 wdt:P38 ?currency .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

The currency to take to Barbados is the Barbadian dollar.

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

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

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

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

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

[User] what currency to take to barbados?

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

[Tool]
Example 1:
Question:
who is the leader of cuba 2012?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q27977064 ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z > "2012-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
President of Costa Rica (wd:Q27977064): head of state and head of government of Costa Rica

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 2:
Question:
what kind of money do the philippines use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q928 wdt:P38 ?x .
}

Using entities:
Philippines, also known as ph, The Philippines, RP, Republic of the Philippines, Philippine Islands (wd:Q928): archipelagic country in Southeast Asia

Using properties:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

Example 3:
Question:
what is beyonce's daughters name?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q36153 wdt:P40 ?x .
}

Using entities:
Beyoncé, also known as Queen B, Harmonies by The Hive, Beyoncé Knowles-Carter, Beyoncé Knowles, Beyonce Knowles (wd:Q36153): recording artist, American singer, film director, entrepreneur, singer, dancer, actor

Using properties:
child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

[Assistant] From the examples, I see that the property for currency used by a country is wdt:P38. Now I need to find the entity for Barbados and then query the currency used by Barbados.

[Tool]
Top 10 entity alternatives:
1. Barbados, also known as 🇧🇧, BAR, Barbadoes, bb, BB (wd:Q244): island nation in the Caribbean
2. Barbados (wd:Q807306): Swedish dansband
3. Barbados (wd:Q4858589): single by Typically Tropical
4. Barbados (wd:Q4858586): musical composition by Charlie Parker
5. Barbados (wd:Q10426260): 1995 studio album by Barbados
6. Barbados (wd:Q16950300): song
7. Barbados (wd:Q2649101): plantation in Surinam
8. Barbados (wd:Q98687855): jazz blues by Charlie Parker
9. Barbados (wd:Q74608067): scientific article published on 01 June 1987
10. Barbados (wd:Q59508554): painting by J.E.H. MacDonald

[Assistant] The entity for Barbados as an island nation in the Caribbean is wd:Q244. Now I will query the currency used by Barbados using the property wdt:P38.

[Tool]
Got 1 row and 2 columns:
| currency                      | currencyLabel         |
| ----------------------------- | --------------------- |
| Barbadian dollar (wd:Q194351) | Barbadian dollar (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the currency used in Barbados (wd:Q244) by using the property wdt:P38 (currency). The query also optionally retrieves the English label of the currency. The answer 'The currency to take to Barbados is the Barbadian dollar.' is accurate and matches the query result. The query follows the rules by returning the actual identifier and label optionally. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?inception WHERE {
  wd:Q650840 wdt:P571 ?inception .
}

The Philadelphia Phillies began in the year 1883.

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

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

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

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

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

[User] what year did the phillies begin?

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

[Tool]
Example 1:
Question:
what language is mainly spoken in england?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q21 wdt:P2936 ?x .
}

Using entities:
England, also known as England, United Kingdom, England, UK, ENG (wd:Q21): country in north-west Europe, part of the United Kingdom

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

Example 2:
Question:
where is lanzarote in a world map?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q182432 wdt:P625 ?x .
}

Using entities:
Lanzarote (wd:Q182432): one of the main islands of the Canary Islands, Spain

Using properties:
coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

Example 3:
Question:
what character did liv tyler play in lord of the rings?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q127367 p:P161 ?p .
  ?p ps:P161 wd:Q168763 ; pq:P453 ?x .
}

Using entities:
The Lord of the Rings: The Fellowship of the Ring, also known as Lord of the Rings: The Fellowship of the Ring, The Fellowship of the Ring (wd:Q127367): 2001 film by Peter Jackson
Liv Tyler, also known as Liv Rundgren, Liv Tallarico, Liv Rundgren Tyler (wd:Q168763): American actress, fashion model, photo model, film actor, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

[Assistant]
The question is about the year the Phillies began. The Phillies is a baseball team, so I need to find the entity for the Philadelphia Phillies and then find the property that indicates the year it was founded or began.

Next, I will search for the entity "Philadelphia Phillies" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Philadelphia Phillies, also known as Phillies, Quakers, Phils, Philadelphia Quakers (wd:Q650840): baseball team in Philadelphia, Pennsylvania, United States, Major League Baseball team
2. Philadelphia Phillies, also known as Philadelphia Quakers, Phillies, Quakers, Phils (wd:Q650840): baseball team in Philadelphia, Pennsylvania, United States, Major League Baseball team
3. Philadelphia Phillies (wd:Q7182765): professional American football team from 1902
4. history of the Philadelphia Phillies, also known as Philadelphia Phillies history, the Philadelphia Phillies history (wd:Q5870209): aspect of history
5. WikiProject Philadelphia Phillies (wd:Q21830603): Wikimedia subject-area collaboration
6. 2018 Philadelphia Phillies season (wd:Q47010509): Major League Baseball season
7. 2009 Philadelphia Phillies season (wd:Q3466492): Major League Baseball season
8. 2022 Philadelphia Phillies season (wd:Q108179426): Major League Baseball season
9. 2010 Philadelphia Phillies season (wd:Q3467975): Major League Baseball season
10. 2021 Philadelphia Phillies season (wd:Q104859453): major League Baseball season

[Assistant] The Philadelphia Phillies baseball team is represented by the entity wd:Q650840 in Wikidata. Now I will search for properties related to the founding or start year of this team. I will search for properties related to "start year" or "founded" for the entity Philadelphia Phillies (wd:Q650840).

[Tool]
Top 10 property alternatives:
1. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
2. named after, also known as toponym, namesake, named in honor of, named for, etymology (wd:P138 as p/wdt): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
3. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as p/wdt): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person
4. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as p/wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place

No other items found

[Assistant] The property "inception" (wdt:P571) corresponds to the founding or start date of an entity. I will now write a SPARQL query to get the inception year of the Philadelphia Phillies (wd:Q650840).

[Tool]
Got 1 row and 1 column:
| inception                           |
| ----------------------------------- |
| 1883-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the inception date (P571) of the Philadelphia Phillies (Q650840) from Wikidata. The answer "The Philadelphia Phillies began in the year 1883." is accurate and supported by the query result. The query follows the rules by returning the actual identifier and the date value without unnecessary labels or services. No further refinement is needed.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?voiceActor ?voiceActorLabel WHERE {
  wd:Q12206942 wdt:P725 ?voiceActor .
  OPTIONAL {
    ?voiceActor rdfs:label ?voiceActorLabel FILTER ( LANG( ?voiceActorLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| voiceActor                     | voiceActorLabel       |
| ------------------------------ | --------------------- |
| James Earl Jones (wd:Q203960)  | James Earl Jones (en) |
| Jean-Louis Faure (wd:Q3166756) | Jean-Louis Faure (en) |
| Philippe Catoire (wd:Q3379526) | Philippe Catoire (en) |

The voice actors who voiced Darth Vader in the original Star Wars movies include James Earl Jones, Jean-Louis Faure, and Philippe Catoire. James Earl Jones is the primary voice actor for Darth Vader in the original English versions.

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

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

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

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

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

[User] who voiced darth vader in the original star wars movies?

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

[Tool]
Example 1:
Question:
what type of money do japanese use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q17 wdt:P38 ?x .
}

Using entities:
Japan, also known as State of Japan, Nippon-koku, Nippon, Nihon-koku, Nihon (wd:Q17): island country in East Asia

Using properties:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

Example 2:
Question:
what shows did kellie martin star in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q235754 .
  ?x wdt:P31 / wdt:P279 * wd:Q5398426 .
}

Using entities:
Kellie Martin, also known as Kellie Noelle Martin (wd:Q235754): American actress, television actor, film director, voice actor, film actor, actor
television series, also known as TV show, TV-series, television show, TV series (wd:Q5398426): connected set of television program episodes under the same title

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
who did lamar odom sign with?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q296403 wdt:P54 ?x .
}

Using entities:
Lamar Odom, also known as Lamar Joseph Odom, The Goods, L.O., Candy Man (wd:Q296403): American basketball player, basketball player

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

[Assistant]
The question is about the voice actor of Darth Vader in the original Star Wars movies. We need to find the entity for Darth Vader and then find the property related to the voice actor or voice actor role in the original Star Wars movies.

Step 1: Search for the entity "Darth Vader" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Darth Vader, also known as Anakin Skywalker, Vader, Lord Vader (wd:Q12206942): main villain of the Star Wars Trilogy, commander-in-chief, starship pilot, mass murderer, war criminal, swordfighter, knight
2. Darth Vader, also known as Darth Oleksiyovych Vader (wd:Q15995646): Ukrainian politician, politician
3. Darth Vader, also known as 1978 Darth Vader (wd:Q125307067): 1978 Star Wars miniature action figure
4. Darth Vader (wd:Q47512405): painting by Marshall Arisman
5. Darth Vader Grotesque (wd:Q5225625): artwork by Jay Hall Carpenter
6. Darth & Vader (wd:Q19705315)
7. The Imperial March, also known as Darth Vader's Theme, Imperial March (wd:Q2061833): musical theme composed by John Williams for the 1980 film "Star Wars: The Empire Strikes Back"
8. Star Wars: Darth Vader (wd:Q30895582): American comic book series
9. Darth Vader's lightsaber, also known as Darth Vader's laser sword (wd:Q109322280): fictional weapon from Star Wars
10. Shawn Rescues Darth Vader (wd:Q50814533): episode of Psych (S6 E1)

[Assistant] The entity for Darth Vader as the main villain of the Star Wars Trilogy is wd:Q12206942. Next, I will search for properties related to voice actors or actors for this entity.

[Tool]
Top 10 property alternatives:
1. voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as p/wdt): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member
2. Behind The Voice Actors character ID, also known as Behind The Voice Actors character identifier, BTVA character ID, BTVA character identifier (wd:P5107 as p/wdt): identifier of a character from the Behind The Voice Actors website
3. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as p/wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
4. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
5. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as p/wdt): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
6. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
7. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as p/wdt): full name of a person at birth, if different from their current, generally used name, name
8. theme music, also known as theme song (wd:P942 as p/wdt): theme music/song used by the item
9. superhuman feature or ability, also known as has superpower, magic, magic ability, magical ability, supernatural abilities (wd:P2563 as p/wdt): superhuman, supernatural, or paranormal abilities that the fictional subject exhibits, uses
10. member of the crew of, also known as crewmember of, crew of, member of crew, served aboard, ship appointments (wd:P5096 as p/wdt): person who has been a member of a crew associated with the vesse...e of crew member (P1029), backup or reserve team or crew (P3015), member of

No other items found

[Assistant] The property "voice actor" (wdt:P725) is the relevant property to find the voice actor of Darth Vader. Now I will query for the voice actor of Darth Vader (wd:Q12206942) using this property.

[Tool]
Got 3 rows and 2 columns:
| voiceActor                     | voiceActorLabel       |
| ------------------------------ | --------------------- |
| James Earl Jones (wd:Q203960)  | James Earl Jones (en) |
| Jean-Louis Faure (wd:Q3166756) | Jean-Louis Faure (en) |
| Philippe Catoire (wd:Q3379526) | Philippe Catoire (en) |

[Assistant]
The voice actors for Darth Vader in the original Star Wars movies include James Earl Jones, Jean-Louis Faure, and Philippe Catoire. James Earl Jones is the most well-known voice actor for Darth Vader in the original English versions. Jean-Louis Faure and Philippe Catoire likely provided the voice in dubbed versions.

I will now provide the final answer with these voice actors.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the voice actors who voiced Darth Vader in the original Star Wars movies using the property 'voice actor' (wdt:P725). The answer includes the primary and additional voice actors, which is accurate and complete. The query also optionally retrieves English labels for better readability. The output aligns well with the user's question and provides a comprehensive answer. No further refinement is necessary.