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 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]
To answer the question about the school Karl Benz attended, we need to identify the entity for Karl Benz and then find the property that indicates his educational institution.

First, let's search for the entity representing Karl Benz in the knowledge graph.

[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 top result for Karl Benz is `wd:Q40224`, which represents Carl Friedrich Benz, the automotive and engine designer and manufacturer. This is the correct entity for Karl Benz.

Next, we need to find the property that indicates the educational institution he attended. Let's search for properties related to education 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 wdt/p): educational institution attended by subject, affiliation
2. Commons gallery, also known as gallery (wd:P935 as wdt/p): name of the Wikimedia Commons gallery page(s) related to this item (is suitable to allow multiple links to more gallery pages)
3. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
4. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
5. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
6. described at URL, also known as mentioned at URL, descURL, described on webpage, discussed at URL, d@url (wd:P973 as wdt/p): item is described at the following URL, URL
7. child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt/p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
9. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
10. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt/p): full name of a person at birth, if different from their current, generally used name, name

No other items found

[Assistant]
The top result for properties related to education is `wdt:P69` (educated at), which indicates the educational institution attended by the subject.

Now, let's construct a SPARQL query to find the school Karl Benz attended.

```sparql
SELECT ?school WHERE {
  wd:Q40224 wdt:P69 ?school .
  OPTIONAL { ?school rdfs:label ?schoolLabel . FILTER(LANG(?schoolLabel) = "en") }
}
```

This query will return the IRI of the school Karl Benz attended, along with an optional English label for the school.

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| ?school                                |
| -------------------------------------- |
| University of Karlsruhe (wd:Q29426438) |

[Assistant]
The SPARQL query returned the IRI of the school Karl Benz attended, which is `wd:Q29426438`. The optional label for this school is "University of Karlsruhe".

Therefore, the school Karl Benz attended is the University of Karlsruhe.

Here is the final SPARQL query and answer:

```sparql
SELECT ?school WHERE {
  wd:Q40224 wdt:P69 ?school .
  OPTIONAL { ?school rdfs:label ?schoolLabel . FILTER(LANG(?schoolLabel) = "en") }
}
```

Answer: Karl Benz attended the University of Karlsruhe.

[Tool] Stopped generation process


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 |
| opera (wd:Q1344)                    | opera               |
| classical music (wd:Q9730)          | classical music     |

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]
To answer the question about the type of music Claude Debussy played, we need to identify Claude Debussy as an entity and then find out the musical genres or styles associated with him.

First, let's search for Claude Debussy in the knowledge graph.

[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]
The top result for Claude Debussy is the correct one (wd:Q4700). Now, let's find out the musical genres or styles associated with Claude Debussy. We can search for properties related to musical style or genre for this entity.

Let's search for properties related to musical style or genre for Claude Debussy.

[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 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
2. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
5. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as wdt/p): notable scientific, artistic or literary work, or other work of significance among subject's works
6. movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as wdt/p): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.
7. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as wdt/p): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
8. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as wdt/p): musical instrument that a person plays or teaches or used in a music occupation, uses
9. 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, country
10. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in

No other items found

[Assistant]
The property "genre" (wdt:P136) seems to be the most relevant for finding the type of music Claude Debussy played. Let's execute a SPARQL query to find the musical genres associated with Claude Debussy.

Here is the SPARQL query:

```sparql
SELECT ?genre ?genreLabel
WHERE {
  wd:Q4700 wdt:P136 ?genre.
  OPTIONAL { ?genre rdfs:label ?genreLabel . FILTER(LANG(?genreLabel) = "en") }
}
```

Let's execute this query.

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

[Assistant]
The SPARQL query returned the following musical genres associated with Claude Debussy:

- Impressionist music
- Opera
- Classical music

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

Here is the final SPARQL query and answer:

```sparql
SELECT ?genre ?genreLabel
WHERE {
  wd:Q4700 wdt:P136 ?genre.
  OPTIONAL { ?genre rdfs:label ?genreLabel . FILTER(LANG(?genreLabel) = "en") }
}
```

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

[Tool] Stopped generation process


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:P4884 wd:Q11201 .
  ?case rdfs:label ?caseLabel .
  FILTER ( LANG( ?caseLabel ) = "en" )
}
LIMIT 10

Got 10 rows and 2 columns:
| ?case                                                       | ?caseLabel                                  |
| ----------------------------------------------------------- | ------------------------------------------- |
| Trump v. New York (wd:Q100496432)                           | Trump v. New York                           |
| New Hampshire v. Maine (wd:Q101093598)                      | New Hampshire v. Maine                      |
| Roman Catholic Diocese of Brooklyn v. Cuomo (wd:Q102532067) | Roman Catholic Diocese of Brooklyn v. Cuomo |
| McKinney v. Arizona (wd:Q104161429)                         | McKinney v. Arizona                         |
| EEOC v. Wyoming (wd:Q104672335)                             | EEOC v. Wyoming                             |
| Bogan v. Scott-Harris (wd:Q104821362)                       | Bogan v. Scott-Harris                       |
| Allen v. State Bd. of Elections (wd:Q104830455)             | Allen v. State Bd. of Elections             |
| Regan v. Wald (wd:Q104835310)                               | Regan v. Wald                               |
| Biden v. Sierra Club (wd:Q104843212)                        | Biden v. Sierra Club                        |
| Fulton v. City of Philadelphia (wd:Q104848915)              | Fulton v. City of Philadelphia              |

Some of the Supreme Court cases include: Trump v. New York, New Hampshire v. Maine, Roman Catholic Diocese of Brooklyn v. Cuomo, McKinney v. Arizona, EEOC v. Wyoming, Bogan v. Scott-Harris, Allen v. State Bd. of Elections, Regan v. Wald, Biden v. Sierra Club, and Fulton v. City of Philadelphia.

[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]
To answer the question about Supreme Court cases, we need to identify the relevant entities and properties in the knowledge graph. We'll start by searching for the entity representing the Supreme Court and then look for properties that might indicate cases associated with it.

First, let's search for the entity "Supreme Court."

[Tool]
Top 10 entity alternatives:
1. Supreme Court of the United States, also known as US Supreme Court, U.S. Supreme Court, United States Supreme Court, Supreme Court of the U.S., SCOTUS (wd:Q11201): highest court of jurisdiction in the United States
2. supreme court, also known as apex court, court of last resort, highest court of appeal (wd:Q190752): highest court in a jurisdiction
3. Supreme Court of India, also known as Indian Supreme Court, India Supreme Court, SCI, SCOI, SCOIN (wd:Q213380): Highest court of jurisdiction in the Republic of India
4. U.S. state supreme court, also known as supreme court (wd:Q7603882): highest court of a U.S. state's judicial system
5. Supreme Court, also known as Pragati Maidan (wd:Q7237614): metro station in Delhi, India
6. Supreme Court, also known as Supreme Court of Hong Kong (wd:Q7644839): former high court of Hong Kong
7. Court of Cassation, also known as Corte di cassazione, Supreme Court (wd:Q3694720): Supreme Court of Vatican City
8. Supreme Court (wd:Q7644844): British-bred Thoroughbred racehorse
9. Supreme Court, also known as High Court of Saudi Arabia, Saudi Arabia Supreme Court, Supreme Court of Saudi Arabia (wd:Q16117686)
10. Supreme Court, also known as Obergericht (wd:Q29651718): court building in the city of Bern, Switzerland

[Assistant]
The top result is the "Supreme Court of the United States" (wd:Q11201), which is likely the entity we are interested in. Next, we need to find properties that might link this entity to specific court cases. Let's search for properties related to "cases" or "decisions" for the Supreme Court of the United States.

We will use the `search_property_of_entity` function to find relevant properties.

[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 wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
3. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
4. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
5. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as wdt/p): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
6. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
7. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
8. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt/p): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
9. 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/p): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
10. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category

No other items found

[Assistant]
The search did not yield any properties directly related to "cases" or "decisions" for the Supreme Court of the United States. However, we can try another approach by searching for properties related to "court cases" or "legal cases" in general and then see if they are used with the Supreme Court of the United States.

Let's search for properties related to "court cases" or "legal cases" using the `search_property` function.

[Tool]
Top 10 property alternatives:
1. defendant, also known as litigant, respondant, plaintiff in, accused (wd:P1591 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): person or organization accused at a trial, object of occurrence, participant
2. highest judicial authority, also known as supreme court, judiciary, judicial branch, has supreme court, court (wd:P209 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): supreme judicial body within a country, administrative division, or other organization
3. court, also known as court (wd:P4884 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): specific court a legal case is or was heard or decided in
4. has grammatical case, also known as cases, has case (wd:P2989 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): case used in this language, has part(s)
5. plaintiff, also known as accuser, claimant, litigant, pursuer (wd:P1620 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): party who initiates a lawsuit, participant
6. number of cases, also known as case number, total number of cases, occurrences reported, number of occurrences, number of infections (wd:P1603 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): cumulative number of confirmed, probable and suspected occurrences
7. verdict (wd:P11922 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): decision made at the end of a trial by the judge or jury
8. penalty, also known as judicial sentence, punishment, sentence (wd:P1596 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): penalty imposed by an authority
9. legal citation of this text, also known as case citation, statute citation, regulation citation, parallel citation, neutral citation (wd:P1031 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): legal citation of legislation or a court decision.
10. participant, also known as suspect, player, party, participants, has participant (wd:P710 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): person, group of people or organization (object) that actively t...ct has role" (P3831). Use P1923 for participants that are teams., significant person

[Assistant]
From the search results, the property `court` (wd:P4884) seems to be the most relevant for linking court cases to the Supreme Court of the United States. We can use this property to find court cases that were heard or decided by the Supreme Court.

Let's construct a SPARQL query to find court cases where the Supreme Court of the United States (wd:Q11201) is the court.

```sparql
SELECT ?case WHERE {
  ?case wdt:P4884 wd:Q11201 .
}
```

We will execute this query to see the results.

[Tool]
Got 20,101 rows and 1 column, showing the first 5 and last 5 rows below:
| ?case                                                       |
| ----------------------------------------------------------- |
| Trump v. New York (wd:Q100496432)                           |
| New Hampshire v. Maine (wd:Q101093598)                      |
| Roman Catholic Diocese of Brooklyn v. Cuomo (wd:Q102532067) |
| McKinney v. Arizona (wd:Q104161429)                         |
| EEOC v. Wyoming (wd:Q104672335)                             |
| ...                                                         |
| Dallas v. Stanglin (wd:Q97453091)                           |
| Lehman v. Shaker Heights (wd:Q97474383)                     |
| Torres v. Madrid (wd:Q97516280)                             |
| Worcester v. Georgia (wd:Q976845)                           |
| Edmond v. United States (wd:Q97738165)                      |

[Assistant]
The SPARQL query successfully returned a list of court cases where the Supreme Court of the United States (wd:Q11201) was the court. The results include various cases such as "Trump v. New York" and "Worcester v. Georgia."

To provide a more complete answer, we can also include the labels of these cases. Let's modify the query to include the labels of the cases.

```sparql
SELECT ?case ?caseLabel WHERE {
  ?case wdt:P4884 wd:Q11201 .
  ?case rdfs:label ?caseLabel .
  FILTER(LANG(?caseLabel) = "en")
}
LIMIT 10
```

This query will return the IRIs and English labels of the first 10 Supreme Court cases. Let's execute this query.

[Tool]
Got 10 rows and 2 columns:
| ?case                                                       | ?caseLabel                                  |
| ----------------------------------------------------------- | ------------------------------------------- |
| Trump v. New York (wd:Q100496432)                           | Trump v. New York                           |
| New Hampshire v. Maine (wd:Q101093598)                      | New Hampshire v. Maine                      |
| Roman Catholic Diocese of Brooklyn v. Cuomo (wd:Q102532067) | Roman Catholic Diocese of Brooklyn v. Cuomo |
| McKinney v. Arizona (wd:Q104161429)                         | McKinney v. Arizona                         |
| EEOC v. Wyoming (wd:Q104672335)                             | EEOC v. Wyoming                             |
| Bogan v. Scott-Harris (wd:Q104821362)                       | Bogan v. Scott-Harris                       |
| Allen v. State Bd. of Elections (wd:Q104830455)             | Allen v. State Bd. of Elections             |
| Regan v. Wald (wd:Q104835310)                               | Regan v. Wald                               |
| Biden v. Sierra Club (wd:Q104843212)                        | Biden v. Sierra Club                        |
| Fulton v. City of Philadelphia (wd:Q104848915)              | Fulton v. City of Philadelphia              |

[Assistant]
The SPARQL query has successfully returned the IRIs and English labels of the first 10 Supreme Court cases. Here are the results:

| Case IRI                                                   | Case Label                                  |
|------------------------------------------------------------|---------------------------------------------|
| [wd:Q100496432](http://www.wikidata.org/entity/Q100496432) | Trump v. New York                           |
| [wd:Q101093598](http://www.wikidata.org/entity/Q101093598) | New Hampshire v. Maine                      |
| [wd:Q102532067](http://www.wikidata.org/entity/Q102532067) | Roman Catholic Diocese of Brooklyn v. Cuomo |
| [wd:Q104161429](http://www.wikidata.org/entity/Q104161429) | McKinney v. Arizona                         |
| [wd:Q104672335](http://www.wikidata.org/entity/Q104672335) | EEOC v. Wyoming                             |
| [wd:Q104821362](http://www.wikidata.org/entity/Q104821362) | Bogan v. Scott-Harris                       |
| [wd:Q104830455](http://www.wikidata.org/entity/Q104830455) | Allen v. State Bd. of Elections             |
| [wd:Q104835310](http://www.wikidata.org/entity/Q104835310) | Regan v. Wald                               |
| [wd:Q104843212](http://www.wikidata.org/entity/Q104843212) | Biden v. Sierra Club                        |
| [wd:Q104848915](http://www.wikidata.org/entity/Q104848915) | Fulton v. City of Philadelphia              |

These are some of the Supreme Court cases. To provide a more comprehensive list, we can remove the `LIMIT 10` clause, but for now, this gives us a good starting point.

Here is the final SPARQL query and answer:

```sparql
SELECT ?case ?caseLabel WHERE {
  ?case wdt:P4884 wd:Q11201 .
  ?case rdfs:label ?caseLabel .
  FILTER(LANG(?caseLabel) = "en")
}
LIMIT 10
```

The answer to the question "What are the Supreme Court cases?" is the list of cases provided above.

Now, I will finalize the answer using the `answer` function.

[Tool] Stopped generation process


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 ?currency ?currencyLabel WHERE {
  wd:Q244 wdt:P38 ?currency .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel .
    FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| ?currency                     | ?currencyLabel   |
| ----------------------------- | ---------------- |
| Barbadian dollar (wd:Q194351) | Barbadian dollar |

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]
To answer the question about what currency to take to Barbados, we need to identify the official currency of Barbados. Let's start by searching for the entity "Barbados" in the knowledge graph.

I will use the `search_entity` function to find the IRI for 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 top result for "Barbados" is the island nation in the Caribbean, which is the entity we are interested in. Its IRI is `wd:Q244`.

Next, we need to find the property that represents the official currency of a country. I will use the `search_property` function to find a suitable property.

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): currency used by item, uses
2. central bank/issuer, also known as authority, issuer, issuing authority (wd:P562 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): central bank or other issuing authority for the currency
3. ISO 4217 code, also known as currency code, ISO 4217, ISO 4217 alphabetic code, ISO currency code (wd:P498 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): identifier for a currency per ISO 4217
4. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): language designated as official by this item, language used
5. official symbol, also known as symbol, state tartan, official tartan, floral emblem, official emblem (wd:P2238 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): official symbol of an organisation
6. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): market value of all officially recognized final goods and services produced within a country in a given period of time
7. house publication, also known as has mouthpiece, publishes, publication, organization publication, organisation publication (wd:P2813 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): media that speaks for an organization or a movement, and that is usually edited by its members
8. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): label for the items in their official language  or their original language, name
9. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): official name of the subject in its official language(s), name
10. central bank (wd:P1304 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): country's central bank

[Assistant]
The property `currency` (wd:P38) seems to be the most relevant for finding the official currency of a country.

Now, let's use this property to find the currency of Barbados. I will construct a simple SPARQL query to retrieve the currency of Barbados and execute it.

```sparql
SELECT ?currency
WHERE {
  wd:Q244 wdt:P38 ?currency .
}
```

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| ?currency                     |
| ----------------------------- |
| Barbadian dollar (wd:Q194351) |

[Assistant]
The official currency of Barbados is the Barbadian dollar (wd:Q194351).

To provide a more complete answer, I will also include the label of the currency in the SPARQL query. Here is the final SPARQL query:

```sparql
SELECT ?currency ?currencyLabel
WHERE {
  wd:Q244 wdt:P38 ?currency .
  OPTIONAL { ?currency rdfs:label ?currencyLabel . FILTER(LANG(?currencyLabel) = "en") }
}
```

Let's execute this query to get the label of the currency.

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

[Assistant]
The official currency of Barbados is the Barbadian dollar (wd:Q194351).

Here is the final SPARQL query and the answer to the user's question:

```sparql
SELECT ?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**.

[Tool] Stopped generation process


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

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]
To answer the question about when the Philadelphia Phillies began, we need to identify the entity representing the Philadelphia Phillies and then find the property that indicates their founding year.

### Step 1: Identify the entity for the Philadelphia Phillies
Let's start by searching for the entity representing the Philadelphia Phillies in the knowledge graph.

[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 top result for the Philadelphia Phillies is `wd:Q650840`, which represents the baseball team. We will use this entity to find the founding year.

### Step 2: Identify the property for the founding year
Next, we need to find the property that indicates the founding year of the team. We can search for properties related to "founding" or "established" for the entity `wd:Q650840`.

Let's search for properties related to "founding" or "established" for the Philadelphia Phillies.

[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 wdt/p): 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 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
3. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
4. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon

No other items found

[Assistant]
The property `wdt:P571` (inception) seems to be the most relevant for finding the founding year of the Philadelphia Phillies. Let's construct a SPARQL query to retrieve this information.

### Step 3: Construct and execute the SPARQL query
We will now write a SPARQL query to get the founding year of the Philadelphia Phillies using the property `wdt:P571`.

[Tool]
Got 1 row and 1 column:
| ?foundingYear        |
| -------------------- |
| 1883-01-01T00:00:00Z |

[Assistant]
The Philadelphia Phillies began in the year 1883.

### Final Answer
Here is the final SPARQL query and the answer to the question:

```sparql
SELECT ?foundingYear WHERE { wd:Q650840 wdt:P571 ?foundingYear }
```

The Philadelphia Phillies began in the year 1883.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?voiceActor WHERE {
  wd:Q12206942 wdt:P725 ?voiceActor .
  ?movie wdt:P161 ?voiceActor .
  VALUES ?movie {
    wd:Q17738 wd:Q181795 wd:Q181803
  }
  .
}

James Earl Jones

[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]
To answer the question about who voiced Darth Vader in the original Star Wars movies, we need to identify the following:

1. The entity representing Darth Vader in the knowledge graph.
2. The entity representing the original Star Wars movies.
3. The property that links a character to the voice actor.

Let's start by searching for the entity representing Darth Vader.

[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 top result for "Darth Vader" is the character from the Star Wars trilogy, which is what we are looking for. The IRI for this entity is `wd:Q12206942`.

Next, we need to find the property that links a character to the voice actor. Let's search for properties related to "voice actor" or "voiced by."

[Tool]
Top 10 property alternatives:
1. voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): 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 person ID, also known as behindthevoiceactors.com person ID, BTVA person ID, BTVA ID (wd:P5007 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): identifier of a person on the website Behind The Voice Actors
3. Deutsche Synchronkartei dubbing voice actor ID, also known as Synchronkartei dubbing voice actor identifier, Synchronkartei dubbing voice actor ID, Deutsche Synchronkartei dubbing voice actor identifier (wd:P4727 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): identifier for a dubbing voice actor, in the synchronisation (dubbing) database Deutsche Synchronkartei
4. Behind The Voice Actors short ID, also known as BTVA short ID (wd:P7318 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): identifier of a short on the website Behind The Voice Actors
5. Behind The Voice Actors character ID, also known as Behind The Voice Actors character identifier, BTVA character ID, BTVA character identifier (wd:P5107 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): identifier of a character from the Behind The Voice Actors website
6. Behind The Voice Actors franchise ID, also known as BTVA franchise ID (wd:P5382 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): identifier of a franchise in Behind the Voice Actors
7. Behind The Voice Actors film ID, also known as Behind The Voice Actors movie ID, BTVA movie ID (wd:P5384 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): identifier of a film on the website Behind The Voice Actors
8. MyAnimeList people ID, also known as MyAnimeList actor ID, MyAnimeList voice actor ID, MyAnimeList staff ID, MyAnimeList person ID, MAL voice actor ID (wd:P4084 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): identifier for a person or group of people on MyAnimeList
9. 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 pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): audio file representing the speaking voice of a person; or of an animated cartoon or other fictitious character, audio
10. voice type, also known as range of voice, register, tessitura, type of voice, vocal type (wd:P412 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): person's voice type. expected values: soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass (and derivatives)

[Assistant]
The top result for "voice actor" is `wd:P725`, which is the property that links a character to the voice actor.

Now, let's construct a SPARQL query to find out who voiced Darth Vader in the original Star Wars movies. We will use the entity `wd:Q12206942` for Darth Vader and the property `wd:P725` for the voice actor.

We also need to ensure that we are looking at the original Star Wars movies. Let's search for the original Star Wars movies to get their entities.

[Tool]
Top 10 entity alternatives:
1. Star Wars sequel trilogy, also known as sequel trilogy (Star Wars), Star Wars movies VII-IX, Star Wars movies VII to IX, Star Wars: The Sequel Trilogy, Star Wars VII-IX (wd:Q6586871): third film trilogy in the Star Wars franchise
2. Star Wars prequel trilogy, also known as Star Wars: The Prequel Trilogy, Star Wars movies I to III, Star Wars movies I-III, Star Wars movies 1 to 3, Star Wars movies 1-3 (wd:Q25540924): second film trilogy in the Star Wars franchise
3. Star Wars original trilogy, also known as Star Wars IV-VI (wd:Q25540859): trilogy in the Star Wars film series
4. Star Wars, also known as Star Wars (Original Motion Picture Soundtrack), Star Wars soundtrack (wd:Q2715371): 1977 soundtrack album
5. Risk: Star Wars Original Trilogy Edition (wd:Q7336215): game
6. Lego Star Wars II: The Original Trilogy, also known as Lego Star Wars 2: The Original Trilogy (wd:Q55239): 2006 video game
7. Movies in Mind: Star Wars The consciousness 'awakens'. (wd:Q47681902): scientific article
8. Star Wars, also known as 1977 Star Wars (wd:Q462): epic space opera multimedia franchise created by George Lucas
9. Star Wars: Episode IV – A New Hope, also known as 1977 Star Wars, A New Hope, Star Wars, Star Wars: A New Hope, Star Wars: Episode IV (wd:Q17738): 1977 film directed by George Lucas
10. Star Wars, also known as Star Wars: The Arcade Game (wd:Q54317): 1983 video game

[Assistant]
The entity for the original Star Wars movies is `wd:Q25540859`. This represents the original trilogy of Star Wars films.

Now, we need to construct a SPARQL query to find the voice actor of Darth Vader (`wd:Q12206942`) specifically in the context of the original Star Wars movies (`wd:Q25540859`).

Let's write the SPARQL query to find the voice actor of Darth Vader in the original Star Wars movies.

[Tool]
Got 3 rows and 1 column:
| ?voiceActor                    |
| ------------------------------ |
| James Earl Jones (wd:Q203960)  |
| Jean-Louis Faure (wd:Q3166756) |
| Philippe Catoire (wd:Q3379526) |

[Assistant]
The query returned multiple voice actors for Darth Vader. However, we need to filter these results to only include the voice actor for the original Star Wars movies.

James Earl Jones is the most well-known voice actor for Darth Vader in the original Star Wars movies. To confirm this, we can add a filter to our query to check if the voice actor is associated with the original Star Wars movies.

Let's refine the query to include this filter.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the refined query did not return any results, which suggests that the relationship between the voice actor and the original Star Wars movies might not be directly represented in the way we tried.

Instead, let's try a different approach. We can look for the specific movies in the original Star Wars trilogy and check if the voice actor is linked to those movies.

The original Star Wars movies are:
- Star Wars: Episode IV – A New Hope (1977)
- Star Wars: Episode V – The Empire Strikes Back (1980)
- Star Wars: Episode VI – Return of the Jedi (1983)

Let's search for these movies and then check the voice actor for Darth Vader in these specific movies.

[Tool]
Top 10 entity alternatives:
1. Star Wars: Episode IV – A New Hope, also known as 1977 Star Wars, A New Hope, Star Wars, Star Wars: A New Hope, Star Wars: Episode IV (wd:Q17738): 1977 film directed by George Lucas
2. Star Wars XXX: A Porn Parody, also known as Star Wars XXX: A Porn Parody Episode IV - A New Hole, Star Wars XXX - A Porn Parody (wd:Q15848933): 2012 film by Axel Braun
3. Star Wars: From the Adventures of Luke Skywalker, also known as 1976 Star Wars, Star Wars: A New Hope (wd:Q6272668): 1976 Star Wars novel by Alan Dean Foster
4. Episode IV: A New Hope (wd:Q114500213): episode of Reaper (S2 E1)
5. Star Wars: A New Hope (wd:Q124372359): 1995 Del Rey edition
6. EFOSC2 episode IV: a new hope (wd:Q68123117): scientific article published in January 2008
7. Star Wars-style holograms: a new hope? (wd:Q59038525): scientific article published in Nature
8. William Shakespeare's Star Wars: Verily, a New Hope (wd:Q18155858): play written by Ian Doescher
9. Star Wars: Episode VII – The Force Awakens, also known as Star Wars 7, Force Awakens, The Force Awakens, TFA, Star Wars VII (wd:Q6074): 2015 film directed by J. J. Abrams
10. Star Wars: Episode II – Attack of the Clones, also known as Attack of the Clones, Star Wars: Episode II -- Attack of the Clones (wd:Q181069): 2002 American epic space opera film directed by George Lucas

[Assistant]
The top result for "Star Wars: Episode IV – A New Hope" is `wd:Q17738`.

Next, let's search for "Star Wars: Episode V – The Empire Strikes Back" and "Star Wars: Episode VI – Return of the Jedi" to get their entities.

[Tool]
Top 10 entity alternatives:
1. Star Wars: Episode V – The Empire Strikes Back, also known as Star Wars 5, The Empire Strikes Back, Star Wars V, Star Wars Episode V: The Empire Strikes Back, Star Wars: Episode V The Empire Strikes Back (wd:Q181795): 1980 American epic space opera film directed by Irvin Kershner
2. Star Wars: The Empire Strikes Back, also known as 1992 The Empire Strikes Back (wd:Q54329): 1992 video game
3. Star Wars/The Empire Strikes Bac...undtrack from the Motion Picture (wd:Q7601131): 1980 soundtrack album by John Williams, London Symphony Orchestra
4. Star Wars: The Empire Strikes Back (wd:Q54327): 1985 video game
5. Super Star Wars: The Empire Strikes Back, also known as Super Empire Strikes Back (wd:Q54330): 1993 video game
6. Classic Star Wars: The Empire Strikes Back (wd:Q3778745): 1997 novel
7. Star Wars: Episode VII – The Force Awakens, also known as Star Wars 7, Force Awakens, The Force Awakens, TFA, Star Wars VII (wd:Q6074): 2015 film directed by J. J. Abrams
8. Star Wars: Episode VIII – The Last Jedi, also known as Last Jedi, Star Wars 8, Star Wars Episode VIII, Star Wars: Episode VIII, Star Wars: The Last Jedi (wd:Q18486021): 2017 film directed by Rian Johnson
9. Impact factor wars: Episode V--the empire strikes back (wd:Q83421448): scientific article published on 01 March 2009
10. Star Wars: Episode VI – Return of the Jedi, also known as Star Wars: Episode VI Return of the Jedi, Return of the Jedi (wd:Q181803): 1983 film directed by Richard Marquand

[Assistant]
The top result for "Star Wars: Episode V – The Empire Strikes Back" is `wd:Q181795`.

Next, let's search for "Star Wars: Episode VI – Return of the Jedi" to get its entity.

[Tool]
Top 10 entity alternatives:
1. Star Wars: Episode VI – Return of the Jedi, also known as Star Wars: Episode VI Return of the Jedi, Return of the Jedi (wd:Q181803): 1983 film directed by Richard Marquand
2. Return of the Jedi, also known as Star Wars Episode VI: Return of the Jedi (wd:Q4350761): soundtrack
3. Star Wars: Episode VIII – The Last Jedi, also known as Last Jedi, Star Wars 8, Star Wars Episode VIII, Star Wars: Episode VIII, Star Wars: The Last Jedi (wd:Q18486021): 2017 film directed by Rian Johnson
4. Return of the Jedi: Death Star Battle, also known as Star Wars: Return of the Jedi: Death Star Battle, Star Wars: Return of the Jedi - Death Star Battle (wd:Q54331): 1983 video game
5. Star Wars: Return of the Jedi, also known as Return of the Jedi (wd:Q54334): 1984 arcade video game
6. Super Star Wars: Return of the Jedi, also known as Super Return of the Jedi (wd:Q54335): 1994 video game
7. Star Wars: Return of the Jedi: Ewok Adventure (wd:Q54332): cancelled Star Wars video game
8. Carotid wars episode VI: Return of the standard (wd:Q38138851): scientific article
9. Star Wars: Episode III – Revenge of the Sith, also known as Star Wars Episode III, Star Wars: Episode III -- Revenge of the Sith, Star Wars: Revenge of the Sith (wd:Q42051): 2005 American epic space opera film directed by George Lucas
10. Star Wars: Episode II – Attack of the Clones, also known as Attack of the Clones, Star Wars: Episode II -- Attack of the Clones (wd:Q181069): 2002 American epic space opera film directed by George Lucas

[Assistant]
The top result for "Star Wars: Episode VI – Return of the Jedi" is `wd:Q181803`.

Now we have the entities for the three original Star Wars movies:
- `wd:Q17738` for "Star Wars: Episode IV – A New Hope"
- `wd:Q181795` for "Star Wars: Episode V – The Empire Strikes Back"
- `wd:Q181803` for "Star Wars: Episode VI – Return of the Jedi"

We will now construct a SPARQL query to find the voice actor of Darth Vader in these specific movies. We will use the property `wd:P725` to link the character to the voice actor and check if the voice actor is associated with any of these movies.

Let's write the SPARQL query to find the voice actor of Darth Vader in the original Star Wars movies.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the query did not return any results, which suggests that the voice actor might not be directly linked to the specific movies in the way we tried.

Let's try a different approach. We can look for the voice actor of Darth Vader and then check if they are associated with the original Star Wars movies through the character's role in those movies.

We will use the property `wd:P161` (cast member) to link the voice actor to the movies. Let's write the SPARQL query to find the voice actor of Darth Vader and check if they are associated with the original Star Wars movies through this property.

[Tool]
Got 1 row and 1 column:
| ?voiceActor                   |
| ----------------------------- |
| James Earl Jones (wd:Q203960) |

[Assistant]
The SPARQL query has returned the voice actor of Darth Vader in the original Star Wars movies as James Earl Jones.

Therefore, the answer to the question "Who voiced Darth Vader in the original Star Wars movies?" is James Earl Jones.

Here is the final SPARQL query and answer:

```sparql
SELECT DISTINCT ?voiceActor WHERE {
  wd:Q12206942 wdt:P725 ?voiceActor .
  ?movie wdt:P161 ?voiceActor .
  VALUES ?movie { wd:Q17738 wd:Q181795 wd:Q181803 } .
}
```

Answer: James Earl Jones

[Tool] Stopped generation process