PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?language ?languageLabel WHERE {
  wd:Q148 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| language                        | languageLabel           |
| ------------------------------- | ----------------------- |
| Standard Chinese (wd:Q727694)   | Standard Chinese (en)   |
| Chinese (wd:Q7850)              | Chinese (en)            |
| languages of China (wd:Q835866) | languages of China (en) |

The main language used in China (wd:Q148) is Standard Chinese (Mandarin), represented by the item wd:Q9059.

[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 is the main language used in china?

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?stadium ?stadiumLabel WHERE {
  wd:Q221878 wdt:P115 ?stadium .
  OPTIONAL {
    ?stadium rdfs:label ?stadiumLabel FILTER ( lang( ?stadiumLabel ) = "en" )
  }
}

The Seattle Seahawks play at Lumen Field (wd:Q612736).

[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] where do the seattle seahawks play?

[Tool]
Top 10 entity alternatives:
1. Seattle Seahawks (wd:Q221878): American football team
2. Seattle Seahawks (wd:Q1431833): ice hockey team
3. history of the Seattle Seahawks, also known as Seattle Seahawks history, the Seattle Seahawks history (wd:Q3973903): aspect of history
4. 2021 Seattle Seahawks season (wd:Q104869618): 46th season in franchise history
5. 2022 Seattle Seahawks season (wd:Q110445415): 47th season in franchise history
6. 2023 Seattle Seahawks season (wd:Q116170066): 48th season in franchise history
7. 2020 Seattle Seahawks season (wd:Q81002024): 45th season in franchise history
8. 2018 Seattle Seahawks season (wd:Q47191924): 43rd season in franchise history; final one under ownership of Paul Allen
9. 2015 Seattle Seahawks season (wd:Q19255692): 40th season in franchise history
10. 2024 Seattle Seahawks season (wd:Q124167235): 49th season in franchise history

[Tool]
Top 10 property alternatives:
1. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
2. YouTube channel ID, also known as YouTube account, YouTube channel, YouTube channel identifier, official YouTube channel, youtube.com/channel/ (wd:P2397 as wdt/p): ID of the YouTube channel of a person or organisation (not to be...f the channel) The ID can also be used for music.youtube.com IDs, website username or ID
3. subreddit, also known as r/, reddit, Reddit community ID, Reddit forum, Reddit sub ID (wd:P3984 as wdt/p): name of the Reddit forum associated to this subject
4. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt/p): home stadium or venue of a sports team or applicable performing arts organization, location
5. topic's main template, also known as topic has template, topic's main module, topic's main infobox, topic infobox, main template (wd:P1424 as wdt/p): the main template relating to a topic
6. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as wdt/p): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of

No other items found

[Tool]
Got 1 row and 2 columns:
| stadium                  | stadiumLabel     |
| ------------------------ | ---------------- |
| Lumen Field (wd:Q612736) | Lumen Field (en) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?tz ?tzLabel WHERE {
  wd:Q16568 wdt:P421 ?tz .
  OPTIONAL {
    ?tz rdfs:label ?tzLabel FILTER ( LANG( ?tzLabel ) = "en" )
  }
}

Jacksonville, Florida (wd:Q16568) is in the Eastern Daylight Time zone (wd:Q15080196).

[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 is jacksonville fl timezone?

[Tool]
Top 10 entity alternatives:
1. Jacksonville, also known as Jacksonville, FL, Jacksonville, Florida (wd:Q16568): city in Duval County, Florida, United States
2. Jacksonville Beach, also known as Jacksonville Beach, FL, Jacksonville Beach, Florida (wd:Q988928): city in Duval County, Florida, United States
3. Ortega, also known as Ortega, Jacksonville, Florida (wd:Q7104308): neighborhood of Jacksonville, Florida, US
4. San Marco, also known as San Marco, Florida, South Jacksonville, Florida (wd:Q14686391): former city of South Jacksonville, Florida, United States; neighborhood of Jacksonville
5. Bayard, also known as Bayard, Jacksonville, Florida (wd:Q4874329): human settlement in Jacksonville, Florida, United States of America
6. history of Jacksonville, Florida, also known as Jacksonville, Florida history (wd:Q17022720): aspect of history
7. education in Jacksonville, Florida, also known as education of Jacksonville, Florida, Jacksonville, Florida education (wd:Q5341043): Overview of education in Jacksonville, Florida
8. Northside, also known as North Jacksonville, Florida, Northside (Jacksonville), Northside Jacksonville, Northside, Jacksonville, North Jacksonville (wd:Q85778622): region of Jacksonville, Florida, United States
9. Jacksonville Heights, also known as Jacksonville Heights, FL, Jacksonville Heights, Florida (wd:Q122594337): hamlet in Duval County, Florida, United States
10. Jacksonville, Florida Auditions (wd:Q114464461): episode of American Idol (S8 E5)

[Tool]
Top 10 property alternatives:
1. located in time zone, also known as TZ, time zone, timezone (wd:P421 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): time zone for this item
2. refine date, also known as date refinement, exact time, hour, local time, quarter (wd:P4241 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): qualifier to narrow down the precision of a date not fully specified by the Wikidata time datatype precision field
3. time index, also known as time coordinate, timestamp, temporal coordinate, relative time (wd:P4895 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): indicate when something happens relative to its beginning
4. point in time, also known as at time, as of, year, when, time of event (wd:P585 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
5. UTC timezone offset, also known as offset from UTC, UTC offset of timezone (wd:P2907 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): difference between Coordinated Universal Time (UTC) and this timezone, numeric value
6. term length of position, also known as term length, time in position, term of position, position term, length of term (wd:P2097 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): length of time in years (unit: Q577) a person (usually a politician) is to serve in a particular position. Do not add bounds., duration
7. start time, also known as start date, since, valid, join time, joined (wd:P580 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): time an entity begins to exist or a statement starts being valid, point in time
8. duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): length of time of an event or process
9. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
10. IANA timezone ID (wd:P6687 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): identifier of a time zone in the IANA database

[Tool]
Got 1 row and 2 columns:
| tz                                   | tzLabel                    |
| ------------------------------------ | -------------------------- |
| Eastern Daylight Time (wd:Q15080196) | Eastern Daylight Time (en) |

[Tool]
Got 1 row and 3 columns:
| subject                  | property                        | object                               |
| ------------------------ | ------------------------------- | ------------------------------------ |
| Jacksonville (wd:Q16568) | located in time zone (wdt:P421) | Eastern Daylight Time (wd:Q15080196) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?formOfGovernment ?formOfGovernmentLabel WHERE {
  wd:Q145 wdt:P122 ?formOfGovernment .
  OPTIONAL {
    ?formOfGovernment rdfs:label ?formOfGovernmentLabel .
    FILTER ( LANG( ?formOfGovernmentLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| formOfGovernment                    | formOfGovernmentLabel        |
| ----------------------------------- | ---------------------------- |
| constitutional monarchy (wd:Q41614) | constitutional monarchy (en) |

The United Kingdom has a constitutional monarchy as its form of government.

[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 form of government is the uk?

[Tool]
Top 10 property alternatives:
1. basic form of government, also known as form of government, government, type of government (wd:P122 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): subject's government
2. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): seat of government of a country, province, state or other type of administrative territorial entity
3. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
4. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): political office that is fulfilled by the head of the government of this item
5. authority, also known as executive authority, governed by, governing authority, governing body, has authority (wd:P797 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): entity having executive power on given entity
6. voting system, also known as electoral system, voting system, type of election (wd:P8196 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): system used for this election or vote
7. Classification of the Functions of Government, also known as COFOG ID, COFOG number (wd:P9798 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): UN classification to compare government agencies across countries
8. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): political office that is fulfilled by the head of state of this item
9. country, also known as sovereign state, state, land, host country (wd:P17 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
10. foundational text, also known as main text, treaty, organic law, founding document, establishing document (wd:P457 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): text through which an institution or object has been created or established

[Tool]
Top 10 entity alternatives:
1. United Kingdom, also known as U.K., UK, U. K., U K, United Kingdom of Great Britain and Northern Ireland (wd:Q145): country in north-west Europe
2. United Kingdom, also known as U K, The United Kingdom of Great Britain and Northern Ireland, The UK, U. K., Great Britain and Northern Ireland (wd:Q145): country in north-west Europe
3. United Kingdom of Great Britain and Ireland, also known as Great Britain and Ireland, UK, UKGBI, United Kingdom (wd:Q174193): historical sovereign state (1801–1922)
4. A United Kingdom, also known as United Kingdom (wd:Q21528200): 2016 film by Amma Asante
5. United Kingdom in the Eurovision Song Contest 2010, also known as United Kingdom (wd:Q974636)
6. United Kingdom (wd:Q108280869): 1989 studio album by American Music Club
7. Pedlars Act 1871, also known as Pedlars Act 1881, United Kingdom, (wd:Q55629342): 1871 United Kingdom of Great Britain and Ireland Act of Parliament 34 & 35 Vic c. 96
8. United Kingdom (wd:Q110577800): Manny Montes's single
9. United Kingdom (wd:Q7887906): album by Manny Montes
10. United Kingdom (wd:Q96412324)

[Tool]
Got 1 row and 2 columns:
| formOfGovernment                    | formOfGovernmentLabel        |
| ----------------------------------- | ---------------------------- |
| constitutional monarchy (wd:Q41614) | constitutional monarchy (en) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?lang ?langLabel WHERE {
  wd:Q213 wdt:P2936 ?lang .
  OPTIONAL {
    ?lang rdfs:label ?langLabel FILTER ( LANG( ?langLabel ) = "en" )
  }
}

Got 5 rows and 2 columns:
| lang                              | langLabel                |
| --------------------------------- | ------------------------ |
| German (wd:Q188)                  | German (en)              |
| Carpathian Romani (wd:Q5045611)   | Carpathian Romani (en)   |
| Czech Sign Language (wd:Q5201809) | Czech Sign Language (en) |
| Polish (wd:Q809)                  | Polish (en)              |
| Czech (wd:Q9056)                  | Czech (en)               |

The languages spoken (i.e., widely used) in the Czech Republic are: Czech, German, Polish, Carpathian Romani, and Czech Sign Language.

[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 is spoken in czech republic?

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt/p): language designated as official by this item, language used
2. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt/p): language widely used (spoken or written) in this place or at this event or organisation
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. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as wdt/p): label for the items in their official language  or their original language, name
5. culture, also known as archaeological culture, civilisation, civilization (wd:P2596 as wdt/p): human culture or people (or several cultures) associated with this item, part of
6. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as wdt/p): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
7. 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
8. 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
9. religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as wdt/p): religion of a person, organization or religious building, or associated with this subject
10. Unicode character, also known as emoji, emote, pictograph, Unicode symbol (wd:P487 as wdt/p): Unicode character representing the item (only if this is not a c...acter or a compatiblity character: in that case, use only P4213)

No other items found

[Tool]
Got 5 rows and 1 column:
| lang                              |
| --------------------------------- |
| German (wd:Q188)                  |
| Carpathian Romani (wd:Q5045611)   |
| Czech Sign Language (wd:Q5201809) |
| Polish (wd:Q809)                  |
| Czech (wd:Q9056)                  |

[Tool]
Got 1 row and 1 column:
| lang             |
| ---------------- |
| Czech (wd:Q9056) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ( YEAR( ?date ) AS ?year ) WHERE {
  ?sb wdt:P31 wd:Q32096 ; wdt:P1346 wd:Q276539 ; wdt:P585 ?date .
}
ORDER BY ?year

The Baltimore Ravens won the Super Bowl in the years 2001 and 2013.

[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 baltimore ravens win superbowl?

[Tool]
Top 10 entity alternatives:
1. Baltimore Ravens (wd:Q276539): National Football League franchise in Baltimore, Maryland
2. history of the Baltimore Ravens, also known as the Baltimore Ravens history, Baltimore Ravens history (wd:Q16995510): aspect of history
3. Baltimore Ravens Cheerleaders (wd:Q4852915): NFL cheerleading squad
4. Baltimore Ravens awards (wd:Q97358836)
5. 2021 Baltimore Ravens season (wd:Q104869586): 26th season in franchise history
6. 2023 Baltimore Ravens season (wd:Q116170173): 28th season in franchise history
7. 2022 Baltimore Ravens season (wd:Q110445353): 27th season in franchise history
8. 2019 Baltimore Ravens season (wd:Q60525815): Ravens record would be 4-12?
9. 2018 Baltimore Ravens season (wd:Q47454104): 23rd season in franchise history
10. 2020 Baltimore Ravens season (wd:Q80964250): 25th season in franchise history

[Tool]
Top 10 entity alternatives:
1. America's Game: The Super Bowl Champions (wd:Q4742545): US television program
2. Green Bay Packers Super Bowl XLV Champions (wd:Q123700634)
3. Super Bowl, also known as AFL–NFL World Championship Game (wd:Q32096): National Football League championship game
4. Super Bowl (wd:Q121409161): 2023 single by Stray Kids
5. Super Bowl (wd:Q104642171): American horse
6. Super Champion (wd:Q7642242): French brand of bicycle rims
7. Super Champion (wd:Q3504125): Monegasque TV game show
8. Super Bowl, also known as xkcd 60 (wd:Q18612009): 60th strip of the webcomic xkcd
9. Super Bowl, also known as xkcd 1480 (wd:Q20671274): 1480th strip of the webcomic xkcd
10. Super Bowl (wd:Q51263859): episode of Aqua Teen Hunger Force (S2 E3)

[Tool] Got no rows and 3 columns

[Tool]
Top 10 property alternatives:
1. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
2. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt/p): home stadium or venue of a sports team or applicable performing arts organization, location
3. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt/p): league or competition in which team or player has played, or in which an event occurs, participant in
4. 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
5. 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
6. 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
7. 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)
8. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt/p): 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
9. FAST ID, also known as Faceted Application of Subject Terminology ID, FAST subject heading, fst, worldcat.org/fast (wd:P2163 as wdt/p/wdtn): authority control identifier in WorldCat's “FAST Linked Data” authority file
10. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt/p): 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))

No other items found

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool]
Top 10 entity alternatives:
1. Super Bowl XXXV, also known as 2001 Super Bowl, Super Bowl 35, Super Bowl 2001 (wd:Q625210): 2001 edition of the Super Bowl
2. Super Bowl XXXVIII, also known as Super Bowl 38, 2004 Super Bowl, Super Bowl 2004 (wd:Q1049630): 2004 edition of the Super Bowl
3. Super Bowl XXXVI, also known as Super Bowl 2002, 2002 Super Bowl, Super Bowl 36 (wd:Q1073479): 2002 edition of the Super Bowl
4. Super Bowl XXXVII, also known as 2003 Super Bowl, Super Bowl 2003, Super Bowl 37 (wd:Q939802): 2003 edition of the Super Bowl
5. Super Bowl XXXV halftime show (wd:Q104877749): halftime show of the 2001 Super Bowl
6. Super Bowl XXXVI halftime show (wd:Q96406798): halftime show of the 2002 Super Bowl
7. Super Bowl XXXVII halftime show (wd:Q104878132): halftime show of the 2003 Super Bowl
8. Super Bowl XXXVIII halftime show (wd:Q85804187): halftime show of the 2004 Super Bowl
9. Super Bowl XXXVIII halftime show controversy, also known as Nipplegate (wd:Q541283): 2004 controversy over indecent exposure on television
10. Super Bowl, also known as AFL–NFL World Championship Game (wd:Q32096): National Football League championship game

[Tool]
Top 10 property alternatives:
1. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
2. competition won, also known as won event, won, winner of, victory (wd:P2522 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): competition or sports event won by the subject, participant in
3. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): award or recognition received by a person, organization or creative work
4. number of wins, also known as games won, won, wins, W, sporting wins (wd:P1355 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): number of sporting matches, games or events won
5. results, also known as output, result (wd:P2501 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): results of a competition such as sports or elections
6. has effect, also known as has symptom, implies, leads to, led to, outcome (wd:P1542 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): effect of this item, followed by
7. conferred by, also known as presented by, officiated by, issued by, granted by, given by (wd:P1027 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): person or organization who grants an award, certification, grant, or role
8. has cause, also known as implied by, originated due to, initial cause, outcome of, reason (wd:P828 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): underlying cause, entity that ultimately resulted in this effect, follows
9. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): significant or notable events associated with the subject
10. successful candidate, also known as election winner, winning candidate, winner of election, election won by, elected (wd:P991 as prn/pqn/psv/pqv/p/pq/prv/psn/ps/wdt/pr/wdtn): person(s) or political organization(s) elected after the election, candidate, winner

[Tool]
Got 1 row and 3 columns:
| subject                      | property           | object                        |
| ---------------------------- | ------------------ | ----------------------------- |
| Super Bowl XXXV (wd:Q625210) | winner (wdt:P1346) | Baltimore Ravens (wd:Q276539) |

[Tool]
Got 1 row and 3 columns:
| subject                      | property              | object                 |
| ---------------------------- | --------------------- | ---------------------- |
| Super Bowl XXXV (wd:Q625210) | instance of (wdt:P31) | Super Bowl (wd:Q32096) |

[Tool]
Got 1 row and 3 columns:
| subject                      | property                 | object                              |
| ---------------------------- | ------------------------ | ----------------------------------- |
| Super Bowl XXXV (wd:Q625210) | point in time (wdt:P585) | 2001-01-28T00:00:00Z (xsd:dateTime) |

[Tool]
Top 10 entity alternatives:
1. Super Bowl XLVII, also known as 2013 Super Bowl, Harbaugh Bowl, Harbowl, Super Bowl 2013, Super Bowl 47 (wd:Q126291): 2013 edition of the Super Bowl
2. Super Bowl XLVIII, also known as 2014 Super Bowl, Super Bowl 48, Super Bowl 2014 (wd:Q1190093): 2014 edition of the Super Bowl
3. Super Bowl XLVII post-game (wd:Q123693291)
4. Super Bowl XLVII halftime show (wd:Q7642202): halftime show of the 2013 Super Bowl
5. Security at Super Bowl XLVII (wd:Q123693422)
6. Super Bowl XLVII pre-game ceremonies (wd:Q123693292)
7. Super Bowl XLVIII post-game (wd:Q123693288)
8. Super Bowl Boulevard at Super Bowl XLVII (wd:Q123693406)
9. Super Bowl XLVIII halftime show (wd:Q17026444): halftime show of the 2014 Super Bowl
10. Media coverage of Super Bowl XLVII (wd:Q123700505)

[Tool]
Got 1 row and 3 columns:
| subject                       | property           | object                        |
| ----------------------------- | ------------------ | ----------------------------- |
| Super Bowl XLVII (wd:Q126291) | winner (wdt:P1346) | Baltimore Ravens (wd:Q276539) |

[Tool]
Got 1 row and 3 columns:
| subject                       | property                 | object                              |
| ----------------------------- | ------------------------ | ----------------------------------- |
| Super Bowl XLVII (wd:Q126291) | point in time (wdt:P585) | 2013-02-03T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?airport ?airportLabel WHERE {
  ?airport wdt:P31 / wdt:P279 * wd:Q1248784 ; wdt:P131 + wd:Q60 .
  ?airport rdfs:label ?airportLabel
  FILTER ( LANG( ?airportLabel ) = "en" ) .
}

Got 3 rows and 2 columns:
| airport                                          | airportLabel                               |
| ------------------------------------------------ | ------------------------------------------ |
| Floyd Bennett Field (wd:Q1430350)                | Floyd Bennett Field (en)                   |
| LaGuardia Airport (wd:Q319654)                   | LaGuardia Airport (en)                     |
| John F. Kennedy International Airport (wd:Q8685) | John F. Kennedy International Airport (en) |

The airports located in New York City are:
- John F. Kennedy International Airport
- LaGuardia Airport
- Floyd Bennett Field

[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 is the name of airport in new york?

[Tool]
Top 10 entity alternatives:
1. New York City, also known as Capital of the World, Big Apple, the five boroughs, The City So Nice They Named It Twice, NY, NY (wd:Q60): most populous city in the United States
2. New York, also known as New York state, New York, United States, US-NY, The Empire State, Empire State (wd:Q1384): state of the United States of America
3. New York, also known as US-NY, The Empire State, State of New York, NY state, NYS (wd:Q1384): state of the United States of America
4. Newburgh, also known as Newburgh, New York, Newburgh, NY (wd:Q1044808): city in Orange County, New York, United States
5. New York, New York (wd:Q743367): 1977 American musical-drama film directed by Martin Scorsese
6. Niu-York, also known as New York, Oleksandrivske, Novgorodskoye, Novgorodske, New-York (wd:Q4322522): rural settlement in Bakhmut Raion, Donetsk Oblast (province), Ukraine
7. New York, also known as New York (magazine), Vulture (blog), New York Magazine (wd:Q1507987): American magazine on life, culture, politics, and style, focusing on New York City
8. Province of New York, also known as Colony of New York, New York, New-York, New York Colony (wd:Q769668): former colony in North America, part of Great Britain
9. New York-New York Hotel and Casino, also known as New York, New York, New York-New York Hotel & Casino (wd:Q1429071): hotel and casino in Las Vegas
10. Theme from New York, New York, also known as New York, New York (wd:Q2039364): song written and composed by Fred Ebb and John Kander, originally recorded by Liza Minnelli and released in 1977

[Tool]
Top 10 entity alternatives:
1. airport, also known as aerodrome, air port, airports (wd:Q1248784): location where aircraft take off and land with extended support facilities, mostly for commercial air transport
2. Airport (wd:Q409022): 1970 film directed by George Seaton
3. AirPort, also known as Apple AirPort (wd:Q697292): brand of wifi router equipment made by Apple Inc.
4. Airport, also known as Airport, CA, Airport, California (wd:Q4698872): census-designated place in Stanislaus County, California, USA
5. Airport (wd:Q2604087): 1968 novel by Arthur Hailey
6. Kasese Airport, also known as Airport, HUKS, KSE (wd:Q6374123): airport in Uganda
7. Basongo Airport, also known as airport, BAN, FZVR (wd:Q3339360): airport in Democratic Republic of the Congo
8. Bambili-Dingila Airport, also known as airport, FZKB, Aéroport de Bambili-Dingila (wd:Q3206837): airport in Democratic Republic of the Congo
9. Bokungu Airport, also known as Airport, FZGF (wd:Q4938837): airport in Democratic Republic of the Congo
10. Airport, also known as Rapid Airport (wd:Q11289474): Rapid trains in Hokkaido, Japan

[Tool] Got no rows and 2 columns

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool]
Got 99 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                                                    | object                                                                                |
| ----------------------------- | ----------------------------------------------------------- | ------------------------------------------------------------------------------------------------ |
| Broadway Mansions (wd:Q23804) | instance of (wdt:P31)                                       | hotel (wd:Q27686)                                                                                |
| Broadway Mansions (wd:Q23804) | country (wdt:P17)                                           | People's Republic of China (wd:Q148)                                                             |
| Broadway Mansions (wd:Q23804) | located in the administrative territorial entity (wdt:P131) | Hongkou (wd:Q661364)                                                                             |
| Broadway Mansions (wd:Q23804) | coordinate location (wdt:P625)                              | POINT(121.485483 31.246338) (geo:wktLiteral)                                                     |
| Broadway Mansions (wd:Q23804) | Commons category (wdt:P373)                                 | Broadway Mansions                                                                                |
| Broadway Mansions (wd:Q23804) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/20112-Shanghai%2C%20Broadway%20Mansions.jpg> |
| Broadway Mansions (wd:Q23804) | inception (wdt:P571)                                        | 1934-01-01T00:00:00Z (xsd:dateTime)                                                              |
| Broadway Mansions (wd:Q23804) | heritage designation (wdt:P1435)                            | Shanghai Cultural Relics Protection Unit (wd:Q10867873)                                          |
| Broadway Mansions (wd:Q23804) | architectural style (wdt:P149)                              | Art Deco (wd:Q173782)                                                                            |
| Broadway Mansions (wd:Q23804) | architect (wdt:P84)                                         | P&T Architects & Engineers Ltd. (wd:Q3359930)                                                    |
| ...                           | ...                                                         | ...                                                                                |

[Tool]
Top 10 entity alternatives:
1. John F. Kennedy International Airport, also known as Kennedy International Airport, New York International Airport, KJFK, JFK International Airport, Kennedy International (wd:Q8685): international airport in New York, United States
2. John F. Kennedy International Airport, also known as Idlewild Airport, Kennedy International, JFK International Airport, KJFK, JFK Airport (wd:Q8685): international airport in New York, United States
3. Protests against Executive Order 13769, also known as 2017 John F. Kennedy International Airport protest (wd:Q28547752): protest in the United States
4. John F. Kennedy International Airport Terminal 8 (wd:Q128561890)
5. Eclectic and Futuristic: John F. Kennedy International Airport (wd:Q128643584): scholarly article
6. 2007 John F. Kennedy International Airport attack plot (wd:Q4608705): Foiled terrorist plot
7. John F. Kennedy Memorial Airport, also known as KASX, ASX (wd:Q2900611): airport in Ashland, Wisconsin, United States of America
8. Our Lady of the Skies Chapel at ...F. Kennedy International Airport (wd:Q17051623): Catholic chapel
9. PRESIDENT JOHN F. KENNEDY AT INTERNATIONAL MONETARY (NAID 123360) (wd:Q67614914): item in the National Archives and Records Administration's holdings
10. John F. Kennedy, also known as John Kennedy, John Fitzgerald Kennedy, John F Kennedy, Kennedy, President Kennedy (wd:Q9696): President of the United States from 1961 to 1963, anti-communist, naval officer, statesperson, journalist, politician, writer

[Tool]
Got 2 rows and 2 columns:
| airport                           | airportLabel             |
| --------------------------------- | ------------------------ |
| Floyd Bennett Field (wd:Q1430350) | Floyd Bennett Field (en) |
| LaGuardia Airport (wd:Q319654)    | LaGuardia Airport (en)   |

[Tool]
Got 1 row and 3 columns:
| subject                                          | property                                                    | object             |
| ------------------------------------------------ | ----------------------------------------------------------- | ------------------ |
| John F. Kennedy International Airport (wd:Q8685) | located in the administrative territorial entity (wdt:P131) | Queens (wd:Q18424) |

[Tool]
Got 2 rows and 3 columns:
| subject                                          | property              | object                                      |
| ------------------------------------------------ | --------------------- | ------------------------------------------- |
| John F. Kennedy International Airport (wd:Q8685) | instance of (wdt:P31) | international airport (wd:Q644371)          |
| John F. Kennedy International Airport (wd:Q8685) | instance of (wdt:P31) | commercial traffic aerodrome (wd:Q94993988) |

[Tool] Stopped generation process


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

Karl Benz was educated at the University of Karlsruhe (wd:Q29426438).

[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?

[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

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

[Tool] Stopped generation process


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

Got 3 rows and 1 column:
| genreLabel               |
| ------------------------ |
| classical music (en)     |
| impressionist music (en) |
| opera (en)               |

Claude Debussy played Impressionist 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?

[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

[Tool] Stopped generation process


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

Got 19,705 rows and 2 columns, showing the first 5 and last 5 rows below:
| case                                                                            | caseLabel                                                             |
| ------------------------------------------------------------------------------- | --------------------------------------------------------------------- |
| 108 United States 1 Amendments to Rules 1 and 10 (wd:Q19019247)                 | 108 United States 1 Amendments to Rules 1 and 10 (en)                 |
| 10 East 40th Street Building Incorporated v. Callus (wd:Q19019245)              | 10 East 40th Street Building Incorporated v. Callus (en)              |
| 149 Madison Ave Corporation v. Asselta (wd:Q19019249)                           | 149 Madison Ave Corporation v. Asselta (en)                           |
| 14 Penn Plaza LLC v. Pyett (wd:Q4549948)                                        | 14 Penn Plaza LLC v. Pyett (en)                                       |
| 2,606.84 Acres of Land in Tarrant County, Texas v. United States (wd:Q19019583) | 2,606.84 Acres of Land in Tarrant County, Texas v. United States (en) |
| ...                                                                             | ...                                                                   |
| Zucht v. King (wd:Q19084855)                                                    | Zucht v. King (en)                                                    |
| Zuckerman v. Greason (wd:Q19084861)                                             | Zuckerman v. Greason (en)                                             |
| Zurcher v. Stanford Daily (wd:Q8075379)                                         | Zurcher v. Stanford Daily (en)                                        |
| Zwicker v. Boll (wd:Q19084934)                                                  | Zwicker v. Boll (en)                                                  |
| Zwickler v. Koota (wd:Q19084940)                                                | Zwickler v. Koota (en)                                                |

The query retrieves all items that are instances of "United States Supreme Court decision" (i.e., Supreme Court cases), along with their English labels.

[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?

[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)

[Tool]
Got 163 rows and 3 columns, showing the first 10 rows below:
| subject                                             | property                            | object                                                                                |
| --------------------------------------------------- | ----------------------------------- | ------------------------------------------------------------------------------------------------------- |
| United States Supreme Court decision (wd:Q19692072) | country (wdt:P17)                   | United States (wd:Q30)                                                                                |
| United States Supreme Court decision (wd:Q19692072) | image (wdt:P18)                     | <http://commons.wikimedia.org/wiki/Special:FilePath/Oblique%20facade%203%2C%20US%20Supreme%20Court.jpg> |
| United States Supreme Court decision (wd:Q19692072) | subclass of (wdt:P279)              | legal case (wd:Q2334719)                                                                                |
| United States Supreme Court decision (wd:Q19692072) | applies to jurisdiction (wdt:P1001) | United States (wd:Q30)                                                                                |
| United States Supreme Court decision (wd:Q19692072) | topic's main category (wdt:P910)    | wd:Q6996306                                                                                |
| United States Supreme Court decision (wd:Q19692072) | topic's main template (wdt:P1424)   | wd:Q14373911                                                                                |
| United States Supreme Court decision (wd:Q19692072) | has list (wdt:P2354)                | wd:Q6646863                                                                                |
| United States Supreme Court decision (wd:Q19692072) | court (wdt:P4884)                   | Supreme Court of the United States (wd:Q11201)                                                          |
| United States Supreme Court decision (wd:Q19692072) | MeSH tree code (wdtn:P672)          | <http://id.nlm.nih.gov/mesh/I01.880.604.583.858>                                                        |
| United States Supreme Court decision (wd:Q19692072) | MeSH descriptor ID (wdtn:P486)      | <http://id.nlm.nih.gov/mesh/D035521>                                                                    |
| ...                                                 | ...                                 | ...                                                                                |

[Tool]
Got 10 rows and 2 columns:
| 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)                       |
| Tyler v. Cain (wd:Q104822251)                               | Tyler v. Cain (en)                               |
| Office of Senator Mark Dayton v. Hanson (wd:Q104822282)     | Office of Senator Mark Dayton v. Hanson (en)     |
| Kentucky Retirement Systems v. EEOC (wd:Q104829763)         | Kentucky Retirement Systems v. EEOC (en)         |
| Beck v. Washington (wd:Q104830314)                          | Beck v. Washington (en)                          |
| Allen v. State Bd. of Elections (wd:Q104830455)             | Allen v. State Bd. of Elections (en)             |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?currency ?currencyLabel ?code WHERE {
  wd:Q244 wdt:P38 ?currency .
  OPTIONAL {
    ?currency wdt:P498 ?code
  }
  .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

The official currency of Barbados is the Barbadian dollar (ISO 4217 code: BBD).

[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?

[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

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

[Tool]
Got 1 row and 3 columns:
| subject                       | property                 | object |
| ----------------------------- | ------------------------ | ------ |
| Barbadian dollar (wd:Q194351) | ISO 4217 code (wdt:P498) | BBD    |

[Tool] Stopped generation process