PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?productOrService ?productOrServiceLabel WHERE {
  wd:Q95 wdt:P1056 ?productOrService .
  OPTIONAL {
    ?productOrService rdfs:label ?productOrServiceLabel FILTER ( LANG( ?productOrServiceLabel ) = "en" )
  }
}

Got 8 rows and 2 columns:
| productOrService               | productOrServiceLabel |
| ------------------------------ | --------------------- |
| Software tools (wd:Q111897729) | Software tools (en)   |
| Google Maps (wd:Q12013)        | Google Maps (en)      |
| Google Pay (wd:Q19834616)      | Google Pay (en)       |
| Google Ads (wd:Q271982)        | Google Ads (en)       |
| search engine (wd:Q4182287)    | search engine (en)    |
| Google Voice (wd:Q51712)       | Google Voice (en)     |
| Gmail (wd:Q9334)               | Gmail (en)            |
| Google Search (wd:Q9366)       | Google Search (en)    |

Google offers customers various products and services including Software tools, Google Maps, Google Pay, Google Ads, search engine, Google Voice, Gmail, and Google Search.

[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 products and\/or services does google offer customers?

[Assistant] To answer the question about what products and/or services Google offers to customers, I will first identify the entity for Google in Wikidata. Then, I will look for properties related to products and services offered by this entity. These properties might include "product," "service," "offers," or similar. After identifying relevant properties, I will construct a SPARQL query to retrieve the products and services associated with Google.

[Tool]
Top 10 entity alternatives:
1. Google, also known as google.com, Google LLC, Google, Inc., Google Inc., Big G (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc.
2. Google, also known as Big G, google.com, Google Inc., Google LLC, Google, Inc. (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc.
3. Google Search, also known as BackRub, goo.gle, Google, google.com, Google homepage (wd:Q9366): search engine by Google LLC
4. Alphabet Inc., also known as Alphabet, Alphabet company, Alphabet Inc, Alphabet, Inc, Alphabet, Inc. (wd:Q20800404): American multinational technology conglomerate
5. Google+, also known as G+, Google Plus (wd:Q356): social networking service
6. .google, also known as dot google (wd:Q20573262): top-level Internet domain
7. google, also known as to google, googling (wd:Q1156923): transitive verb, meaning to search for something using the Google search engine
8. Google Google (wd:Q123412777): Tamil song from Thuppakki movie
9. Archaeology & Language, also known as Google (wd:Q23301814): 1998 Pimlico edition
10. Google Canada, also known as Google, Google Kitchener-Waterloo, Google Waterloo (wd:Q30338099)

[Assistant] The entity for Google as an American multinational technology company is wd:Q95. Next, I will search for properties related to products and services offered by Google (wd:Q95). I will look for properties that might indicate products or services.

[Tool]
Top 10 property alternatives:
1. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as p/wdt): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
2. official shop URL, also known as online store, shop, shop URL, store, store URL (wd:P10225 as p/wdt): official URL where the agent sells products/merchandise, official website
3. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): 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
4. official app, also known as app, mobile app, official application, official mobile application (wd:P4290 as p/wdt): official app for this organization or other entity (a downloadable application for Android, iOS, etc.)
5. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as p/wdt): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
6. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
7. uses, also known as uses trope, used, using, wielded, wields (wd:P2283 as p/wdt): item or concept used by the subject or in the operation (see also instrument [P1303] and armament [P520])
8. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
9. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as p/wdt): official name of the subject in its official language(s), name
10. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant] The property "product, material, or service produced or provided" (wdt:P1056) seems to be the most relevant for finding products and services offered by Google. I will now construct a SPARQL query to retrieve the products and services associated with Google (wd:Q95) using this property. I will also include labels for better readability.

[Tool]
Got 8 rows and 2 columns:
| productOrService               | productOrServiceLabel |
| ------------------------------ | --------------------- |
| Software tools (wd:Q111897729) | Software tools (en)   |
| Google Maps (wd:Q12013)        | Google Maps (en)      |
| Google Pay (wd:Q19834616)      | Google Pay (en)       |
| Google Ads (wd:Q271982)        | Google Ads (en)       |
| search engine (wd:Q4182287)    | search engine (en)    |
| Google Voice (wd:Q51712)       | Google Voice (en)     |
| Gmail (wd:Q9334)               | Gmail (en)            |
| Google Search (wd:Q9366)       | Google Search (en)    |

[Assistant] I found several products and services offered by Google using the property "product, material, or service produced or provided." These include Software tools, Google Maps, Google Pay, Google Ads, search engine, Google Voice, Gmail, and Google Search. This answers the user's question about what products and/or services Google offers customers. I will now provide the final answer with the SPARQL query and the list of products and services.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves products and services offered by Google using the property 'product, material, or service produced or provided' (wdt:P1056). The results include relevant and well-known Google products and services such as Google Maps, Google Pay, Google Ads, Gmail, and Google Search. The query also includes English labels for readability. The answer is accurate, complete, and directly addresses the user's question. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?team ?teamLabel WHERE {
  wd:Q1374361 wdt:P54 ?team .
  OPTIONAL {
    ?team rdfs:label ?teamLabel FILTER ( LANG( ?teamLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| team                                   | teamLabel                     |
| -------------------------------------- | ----------------------------- |
| New York Giants (wd:Q190618)           | New York Giants (en)          |
| Texas Longhorns football (wd:Q7707821) | Texas Longhorns football (en) |

Tom Landry played for the New York Giants and the Texas Longhorns football team.

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

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

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

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

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

[User] who did tom landry play for?

[Assistant]
The question is asking about the sports team or teams that Tom Landry played for. Tom Landry is a well-known figure in American football, primarily recognized as a coach, but he also had a playing career. To answer this, I need to find the entity for Tom Landry in Wikidata and then find the property that relates to the teams he played for.

Step 1: Search for the entity "Tom Landry" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Tom Landry, also known as Thomas Wade Landry (wd:Q1374361): American football coach and player (1924–2000), American football player, American football coach, aircraft pilot
2. Tom Landry (wd:Q108629583): statue in Arlington, United States of America - Robert Summers - 2001
3. Landry Tomb (wd:Q4856268): historic place
4. Tom Landry Strategy Football (wd:Q108536207)
5. Landry, Tom (1924-2000), football coach (wd:Q103866595): encyclopedia article
6. 75th US Colored Infantry: Landry, Tom (wd:Q107830161): file unit in the National Archives and Records Administration's holdings (NAID 170728667)
7. 84th US Colored Infantry: Landry, Tom (wd:Q107699626): file unit in the National Archives and Records Administration's holdings (NAID 107157520)
8. A personal tribute to Tom Landry (wd:Q93705732)
9. Art Garfunkel, also known as Arthur Ira Garfunkel, Arthur Ira "Art" Garfunkel, Tom, Arthur Garfunkel (wd:Q4039): American singer (born 1941), singer-songwriter, television actor, street artist, songwriter, teacher, singer, actor, poet
10. Tom, also known as Tom River (wd:Q216188): river in Khakassia, Kemerovo Oblast, and Tomsk Oblast, Russia

[Assistant]
The entity for Tom Landry is wd:Q1374361, which corresponds to Thomas Wade Landry, an American football coach and player. Now, I need to find the property that relates to the teams he played for. This is likely related to "sports team" or "member of sports team" or something similar.

Step 2: Search for properties related to "team played for" or "sports team" for the entity Tom Landry (wd:Q1374361).

[Tool]
Top 10 property alternatives:
1. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
2. sport, also known as play, plays, sport played, sports (wd:P641 as p/wdt): sport that the subject participates or participated in or is associated with
3. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team
4. coach of sports team, also known as trainer of sports team, club manager of sports team, trainer of, team manager of sports team, team manager of (wd:P6087 as p/wdt): sports club or team for which this person is or was on-field manager or coach
5. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as p/wdt): country a person or a team represents when playing a sport, country
6. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
7. Pro Football Reference player ID, also known as PFR player ID, Pro-Football-Reference.com player ID, Pro-Football-Reference.com player identifier, Pro Football Reference player identifier (wd:P3561 as p/wdt): identifier for American football players at Pro-Football-Reference.com
8. NFL.com player ID (former scheme), also known as National Football League player ID, NFL.com ID (former scheme), NFL ID, NFL identifier (wd:P3539 as p): numeric identifier for American football players at NFL.com
9. NFL.com player ID, also known as NFL.com player ID, NFL ID, NFL.com player ID (new scheme), National Football League player ID (wd:P9338 as p/wdt): identifier for American football players at NFL.com
10. Pro Football Reference coach ID, also known as Pro-Football-Reference.com coach identifier, Pro-Football-Reference.com coach ID, PFR coach ID, Pro Football Reference coach identifier (wd:P6836 as p/wdt): identifier for American football coaches at Pro Football Reference

No other items found

[Assistant] The property "member of sports team" (wdt:P54) is the appropriate property to find the teams Tom Landry played for. Now I will construct a SPARQL query to get the sports teams that Tom Landry (wd:Q1374361) played for using the property wdt:P54. I will also include the labels of the teams for better readability.

[Tool]
Got 2 rows and 2 columns:
| team                                   | teamLabel                     |
| -------------------------------------- | ----------------------------- |
| New York Giants (wd:Q190618)           | New York Giants (en)          |
| Texas Longhorns football (wd:Q7707821) | Texas Longhorns football (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the sports teams Tom Landry played for using the property 'member of sports team' (wdt:P54). The answer includes the New York Giants and the Texas Longhorns football team, which matches the query results. The query also correctly includes English labels for readability. The output is accurate and complete for the user's question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?currency ?currencyLabel WHERE {
  wd:Q1028 wdt:P38 ?currency .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

The currency you should take to Morocco is the Moroccan dirham.

[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 should you take to morocco?

[Assistant]
To answer the question "what currency should you take to Morocco?", I need to find the official currency of Morocco in the knowledge graph.

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

[Tool]
Top 10 entity alternatives:
1. Morocco, also known as ⵎⵓⵔⴰⴽⵓⵛ, Marocco, MAR, ma, Lmaġrib (wd:Q1028): sovereign state in North Africa
2. Morocco, also known as al-Maġrib, Kingdom of Morocco, ⵎⵓⵔⴰⴽⵓⵛ, Lmaġrib, ma (wd:Q1028): sovereign state in North Africa
3. Morocco (wd:Q577754): 1930 film by Josef von Sternberg and Henry Hathaway
4. Morocco, also known as Morocco, IN, Morocco, Indiana (wd:Q2374422): town in Indiana, United States
5. Morocco leather, also known as Levant, Morocco (wd:Q2118555): soft, pliable leather used for bookbinding, wallets, linings for luggage, gloves and shoes
6. Morocco at the 1960 Summer Olympics, also known as 1960 Summer Olympics, Morocco (wd:Q2149869): sporting event delegation
7. Exit Marrakech, also known as Morocco (wd:Q14949869): 2013 film by Caroline Link
8. Sharifian Empire, also known as Morocco (wd:Q12183875): historical name given to Morocco
9. blouza, also known as Morocco (wd:Q2907091): traditional dress of Morocco and Algeria, traditional dress of Algeria
10. Morocco titular see, also known as Marocco, Marruecos titular see, Morocco, Titular see of Marocco (wd:Q3708053): titular see

[Assistant] The entity for the sovereign state Morocco is wd:Q1028. Next, I will find the property that indicates the official currency of Morocco. I will search for properties related to "currency" for the entity Morocco (wd:Q1028).

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as p/wdt): currency used by item, uses
2. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as p/wdt): market value of all officially recognized final goods and services produced within a country in a given period of time
3. central bank (wd:P1304 as p/wdt): country's central bank
4. flag, also known as flag description (wd:P163 as p/wdt): subject's flag
5. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
6. VAT rate, also known as goods and services tax rate, GST, sales tax, taxation rate for sales, tax rate for sales (wd:P2855 as p/wdt): percentage value-added tax in this country or region. Do not use for sales tax. For specialised rates, use qualifiers
7. The New Yorker topic ID, also known as TNY ID, The NewYorker topic ID, New Yorker topic ID, NewYorker topic ID, newyorker.com (wd:P13317 as p/wdt): identifier of a topic on The New Yorker website
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
9. continent (wd:P30 as p/wdt): continent of which the subject is a part, located in/on physical feature
10. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity

No other items found

[Assistant] The property "currency" (wdt:P38) is used to indicate the currency used by an item. I will now query the currency used by Morocco (wd:Q1028) using this property.

[Tool]
Got 1 row and 2 columns:
| currency                     | currencyLabel        |
| ---------------------------- | -------------------- |
| Moroccan dirham (wd:Q200192) | Moroccan dirham (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the currency used by Morocco (wd:Q1028) using the property wdt:P38. The query returns the Moroccan dirham (wd:Q200192) along with its English label, which directly answers the user's question about the currency to take to Morocco. The query follows the rules by returning the identifier and label, and the answer is accurate and complete.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?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) |

China has multiple official languages listed, including Chinese and languages of China. However, the primary and most widely used official language of China is Standard Chinese, also known as Mandarin.

[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 primary language of china?

[Assistant]
To answer the question "What is the primary language of China?", I need to identify the entity for China and find the property that indicates the primary or official language of a country.

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

[Tool]
Top 10 entity alternatives:
1. People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia
2. porcelain, also known as china, fine china (wd:Q130693): ceramic material
3. China, also known as All under Heaven, Zhonghua, Cathay, Zhongguo, Tianxia (wd:Q29520): cultural region, ancient civilization, and nation in East Asia, ...in political situation and rarely refer to the Republic of China
4. China, also known as Sinae, Zhonghua, Zhongguo, Tianxia, Middle Kingdom (wd:Q29520): cultural region, ancient civilization, and nation in East Asia, ...in political situation and rarely refer to the Republic of China
5. 1125 China, also known as (1125) China, China (wd:Q136211): asteroid
6. China, also known as China, TX, China, Texas (wd:Q288864): city in Jefferson County, Texas, United States
7. China, also known as China, Maine, China, ME (wd:Q3447500): town in Kennebec County, Maine, United States
8. China (wd:Q932423): town in Ōshima district, Kagoshima prefecture, Japan
9. Tianxia, also known as All under Heaven, Tien Hsia, T'ien Hsia, Tien-hsia, T'ien-hsia (wd:Q955223): Chinese cultural, philosophical, and political concept
10. China (wd:Q942154): municipality in the Nuevo León, Mexico

[Assistant] The entity for the country China is wd:Q148 (People's Republic of China). Next, I need to find the property that indicates the primary or official language of a country. I will search for properties related to "official language" or "language" for the entity China (wd:Q148).

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as p/wdt): language designated as official by this item, language used
2. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
3. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as p/wdt): language widely used (spoken or written) in this place or at this event or organisation
4. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as p/wdt): official name of the subject in its official language(s), name
5. basic form of government, also known as form of government, government, type of government (wd:P122 as p/wdt): subject's government
6. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity
7. main regulatory text, also known as regulated by, statutory authorization, statutory authority, legally established by, legal basis (wd:P92 as p/wdt): text setting the main rules by which the subject is regulated
8. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): 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
9. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as p/wdt): political office that is fulfilled by the head of the government of this item
10. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as p/wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

No other items found

[Assistant] The property "official language" (wdt:P37) is the most relevant property for the primary language of a country. Now, I will write a SPARQL query to get the official language(s) of China (wd:Q148) using the property wdt:P37. I will also include the label of the language for better readability.

[Tool]
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) |

[Assistant]
The query returned three results for the official language of China: Standard Chinese (wd:Q727694), Chinese (wd:Q7850), and languages of China (wd:Q835866). The primary and most specific language among these is "Standard Chinese," which is commonly known as Mandarin.

I will finalize the answer with the primary language of China being Standard Chinese.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the official languages of China, including Standard Chinese (Mandarin). However, it also returns 'Chinese' and 'languages of China', which are less specific or not primary languages. The answer should clarify that Standard Chinese (Mandarin) is the primary official language. To improve, the query could be refined to filter or prioritize the primary or most widely used official language, or the answer should explicitly state that Standard Chinese (Mandarin) is the primary language among the official languages listed.

[Assistant] Thank you for the feedback. To improve the answer, I will clarify that among the official languages of China, Standard Chinese (Mandarin) is the primary and most widely used official language. The SPARQL query already retrieves all official languages, so I will keep it as is but provide a more precise explanation in the answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the official languages of China using the property wdt:P37. The answer correctly identifies Standard Chinese (Mandarin) as the primary and most widely used official language of China, which aligns with common knowledge. The query results include Standard Chinese, Chinese, and languages of China, which is comprehensive. The output is clear, accurate, and complete for the user's question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?owner ?ownerLabel WHERE {
  wd:Q156578 wdt:P127 ?owner .
  OPTIONAL {
    ?owner rdfs:label ?ownerLabel FILTER ( LANG( ?ownerLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| owner                                               | ownerLabel                                 |
| --------------------------------------------------- | ------------------------------------------ |
| Hannoversche Beteiligungsgesellschaft (wd:Q1529289) | Hannoversche Beteiligungsgesellschaft (en) |
| Qatar Investment Authority (wd:Q1571175)            | Qatar Investment Authority (en)            |
| Porsche Automobil Holding SE (wd:Q2104551)          | Porsche Automobil Holding SE (en)          |

The Volkswagen Group is owned by multiple entities including Hannoversche Beteiligungsgesellschaft, Qatar Investment Authority, and Porsche Automobil Holding SE.

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

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

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

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

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

[User] who owns volkswagen car company?

[Assistant]
To answer the question "Who owns Volkswagen car company?" I need to identify the entity for "Volkswagen car company" and then find the property that indicates ownership or the owner of this company.

Step 1: Search for the entity "Volkswagen car company" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Volkswagen, also known as VW (wd:Q246): German automotive brand; manufacturing subsidiary of Volkswagen Group
2. Volkswagen Group, also known as Volkswagen, VOLKSWAGEN AG, Volkswagen Aktiengesellschaft, VOLKSWAGEN AKTIENGESELLSCHAFT, VW (wd:Q156578): German automotive manufacturing conglomerate
3. .volkswagen (wd:Q24033243): top-level domain
4. Volkswagen (wd:Q30256185): company in Verona, Italy
5. Volkswagen (wd:Q98823874): postcard by Louise Lawler (MET, 2014.679.3)
6. Volkswagen Beetle, also known as VW Bug, VW Beetle, Volkswagen Bug, Volkswagen Type 1 (wd:Q152946): compact car selling
7. Volkswagen Golf, also known as Volkswagen Caribe, Volkswagen Rabbit (wd:Q247): small family car manufactured by Volkswagen
8. Volkswagen Passat, also known as VW Passat (wd:Q216754): Car model series
9. Volkswagen Polo, also known as Volkswagen Derby (wd:Q247819): Series of automobiles manufactured by Volkswagen
10. Volkswagen Arena (wd:Q155603): football stadium in Wolfsburg, Germany

[Assistant]
There are two relevant entities related to Volkswagen car company:
1. Volkswagen (wd:Q246) - German automotive brand; manufacturing subsidiary of Volkswagen Group
2. Volkswagen Group (wd:Q156578) - German automotive manufacturing conglomerate

Since the question is about the ownership of the Volkswagen car company, it is more appropriate to consider the Volkswagen Group (wd:Q156578) as the company entity.

Step 2: Search for properties related to ownership for the entity Volkswagen Group (wd:Q156578).

[Tool]
Top 10 property alternatives:
1. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as p/wdt): owner of the subject
2. owner of, also known as owns, owns property, shareholder of (wd:P1830 as p/wdt): entities owned by the subject
3. has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as p/wdt): subsidiary of a company or organization; generally a fully owned...siness division" (P199). Opposite of parent organization (P749)., has part(s), owner of
4. parent organization, also known as parent company, parent institution, parent organisation, parent unit, part of (wd:P749 as p/wdt): parent organization of an organization, opposite of subsidiaries (P355), owned by, part of
5. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as p/wdt): founder or co-founder of this organization, religion, place or entity, creator
6. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
7. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
8. significant person, also known as significant people, sigper, sign. person, relevant person, relevant people (wd:P3342 as p/wdt): person linked to the item in any possible way
9. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
10. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as p/wdt): presiding member of an organization, group or body, director / manager, significant person

No other items found

[Assistant]
The property "owned by" (wdt:P127) is the relevant property to find the owner of the Volkswagen Group (wd:Q156578).

Step 3: Query the owner(s) of Volkswagen Group using the property "owned by" (wdt:P127).

[Tool]
Got 3 rows and 2 columns:
| owner                                               | ownerLabel                                 |
| --------------------------------------------------- | ------------------------------------------ |
| Hannoversche Beteiligungsgesellschaft (wd:Q1529289) | Hannoversche Beteiligungsgesellschaft (en) |
| Qatar Investment Authority (wd:Q1571175)            | Qatar Investment Authority (en)            |
| Porsche Automobil Holding SE (wd:Q2104551)          | Porsche Automobil Holding SE (en)          |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the owners of the Volkswagen Group using the property 'owned by' (wdt:P127). The answer lists the main entities owning Volkswagen, which matches the query results. The query also includes English labels for readability. The output is accurate, complete, and follows the rules for SPARQL queries. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?team ?teamLabel WHERE {
  wd:Q706908 wdt:P54 ?team .
  OPTIONAL {
    ?team rdfs:label ?teamLabel FILTER ( LANG( ?teamLabel ) = "en" )
  }
}

Got 5 rows and 2 columns:
| team                              | teamLabel                 |
| --------------------------------- | ------------------------- |
| New York Yankees (wd:Q213417)     | New York Yankees (en)     |
| Texas Rangers (wd:Q329816)        | Texas Rangers (en)        |
| Detroit Tigers (wd:Q650855)       | Detroit Tigers (en)       |
| Washington Nationals (wd:Q825838) | Washington Nationals (en) |
| Houston Astros (wd:Q848117)       | Houston Astros (en)       |

Pudge Rodriguez (Iván Rodríguez) has played for the following teams: New York Yankees, Texas Rangers, Detroit Tigers, Washington Nationals, and Houston Astros.

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

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

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

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

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

[User] who has pudge rodriguez played for?

[Assistant] To answer the question "Who has Pudge Rodriguez played for?", I first need to identify the entity for "Pudge Rodriguez" in Wikidata. Then, I will look for the property that indicates the sports teams or clubs he has played for. Let's start by searching for the entity "Pudge Rodriguez" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Iván Rodríguez, also known as Pudge Rodríguez, Pudge Rodriguez, Pudge, Iván Rodríguez Torres, Ivan Rodriguez Torres (wd:Q706908): Puerto Rican Hall of Fame baseball player, baseball player
2. Ivan ‘Pudge' Rodríguez Field (wd:Q115284691): baseball field in Annandale, Virginia
3. Rodrigues, also known as Rodrigues Islands, Rodriguez, Rodriguez Island (wd:Q208668): Mauritian island
4. Sixto Rodriguez, also known as Rodriguez, Sixto Diaz Rodriguez, Sixto Díaz Rodríguez, Sixto Rodriquez, Sugar Man (wd:Q1894125): American musician (1942–2023), singer-songwriter, guitarist, musician
5. Rodriguez, also known as Municipality of Rodriguez, Montalban (wd:Q106825): municipality of the Philippines in the province of Rizal
6. David Valdes, also known as Rodríguez, Samuel Róbinson (wd:Q1358685): Venezuelan educator, philosopher and politician, philosopher, pedagogue, writer
7. Simón Rodríguez, also known as Samuel Róbinson, Rodríguez (wd:Q1358685): Venezuelan educator, philosopher and politician, philosopher, pedagogue, writer
8. 13760 Rodriguez, also known as (13760) Rodriguez, Rodriguez (wd:Q1090306): asteroid
9. Rodríguez (wd:Q1654058): family name
10. Rodríguez, also known as Rodriguez (wd:Q32453): small town in the San José Department of southern Uruguay

[Assistant] The entity "Pudge Rodriguez" corresponds to Iván Rodríguez (wd:Q706908), a Puerto Rican Hall of Fame baseball player. Now, I will look for the property that indicates the sports teams or clubs he has played for. I will search for properties related to "team" or "club" for the entity Iván Rodríguez (wd:Q706908).

[Tool]
Top 10 property alternatives:
1. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
2. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team
3. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as p/wdt): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
4. sport, also known as play, plays, sport played, sports (wd:P641 as p/wdt): sport that the subject participates or participated in or is associated with
5. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
6. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
8. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
9. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
10. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country

No other items found

[Assistant] The property "member of sports team" (wdt:P54) is used to indicate the sports teams or clubs that Iván Rodríguez (Pudge Rodriguez) has played for. I will now construct a SPARQL query to retrieve the teams he has played for using this property.

[Tool]
Got 5 rows and 2 columns:
| team                              | teamLabel                 |
| --------------------------------- | ------------------------- |
| New York Yankees (wd:Q213417)     | New York Yankees (en)     |
| Texas Rangers (wd:Q329816)        | Texas Rangers (en)        |
| Detroit Tigers (wd:Q650855)       | Detroit Tigers (en)       |
| Washington Nationals (wd:Q825838) | Washington Nationals (en) |
| Houston Astros (wd:Q848117)       | Houston Astros (en)       |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all the sports teams that Pudge Rodriguez (Iván Rodríguez) has played for by using the property 'member of sports team' (wdt:P54). The query also optionally retrieves the English labels of these teams, which is helpful for readability. The execution result matches the known teams he played for, and the answer is complete and accurate. No further refinement is necessary.


PREFIX p: <http://www.wikidata.org/prop/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?originalVoiceActor ?originalVoiceActorLabel WHERE {
  wd:Q908772 p:P725 ?statement .
  ?statement ps:P725 ?originalVoiceActor ; pq:P580 ?startTime .
  OPTIONAL {
    ?originalVoiceActor rdfs:label ?originalVoiceActorLabel FILTER ( LANG( ?originalVoiceActorLabel ) = "en" )
  }
}
ORDER BY ?startTime
LIMIT 1

Got 1 row and 2 columns:
| originalVoiceActor         | originalVoiceActorLabel |
| -------------------------- | ----------------------- |
| Lacey Chabert (wd:Q232910) | Lacey Chabert (en)      |

The original voice actor who voiced Meg Griffin on Family Guy is Lacey Chabert.

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

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

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

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

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

[User] who originally voiced meg on family guy?

[Assistant]
To answer the question "Who originally voiced Meg on Family Guy?", I need to identify the entity for "Meg Griffin" from Family Guy and find the property related to the original voice actor for this character.

Step 1: Search for the entity "Meg Griffin" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Meg Griffin, also known as Megan Griffin, Megatron "Meg" Harvey Oswald Griffin, Megatron Harvey Oswald Griffin, Megan "Meg" Griffin (wd:Q908772): fictional character from the Family Guy franchise, high school student
2. Meg Griffin (wd:Q6807983): American radio disc jockey, radio personality, disc jockey
3. Megan Kate Griffin-Pickering (wd:Q103292935): Ph.D. University of Cambridge 2019
4. griffin, also known as griffon, gryphon (wd:Q130223): legendary animal
5. Griffin, also known as Griffin, GA, Griffin, Georgia (wd:Q1012372): county seat of Spalding County, Georgia, United States
6. The Meg, also known as Meg, The Meg IMAX 2D, The Meg IMAX 3D (wd:Q27957869): 2018 film by Jon Turteltaub
7. (RS)-propylene glycol, also known as methylethylene glycol, methyl ethyl glycol, methylethyl glycol, HOCH2CH(OH)CH3, methyl glycol (wd:Q161495): pair of enantiomers
8. Heinkel He 177 Greif, also known as Luftwaffe's Lighter, Luftwaffenfeuerzeug, Griffin, Heinkel 177, Greif (wd:Q316321): 1939 heavy bomber family by Heinkel
9. Griffin, also known as Griffin, IN, Griffin, Indiana (wd:Q2096172): town in Indiana, USA
10. 4995 Griffin, also known as Griffin (wd:Q389857): asteroid

[Assistant] The entity "Meg Griffin" from Family Guy is identified as wd:Q908772. Next, I need to find the property that relates this character to the original voice actor. I will search for properties related to "voice actor" or "voiced by" for the entity Meg Griffin (wd:Q908772).

[Tool]
Top 10 property alternatives:
1. voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as p/wdt): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member
2. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as p/wdt): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
3. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
4. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as p/wdt): full name of a person at birth, if different from their current, generally used name, name
5. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
6. media franchise, also known as franchise, mass media franchise, media mix, presented in media franchise (wd:P8345 as p/wdt): this creative work belongs to this media franchise
7. first appearance, also known as debut, present initially in, introduced in work, initial appearance, first film (wd:P4584 as p/wdt): work in which a fictional/mythical character or entity first appeared, present in work
8. from narrative universe, also known as from narrative, in continuity, from universe, in cycle, in world of (wd:P1080 as p/wdt): subject's fictional entity is in the object narrative. See also P1441 (present in work) and P1445 (fictional universe described in), part of
9. birthday, also known as b-day, bday, birth day (wd:P3150 as p/wdt): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
10. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as p/wdt): maker of this creative work or other object (where no more specific property exists)

No other items found

[Assistant] The property "voice actor" (wdt:P725) is the relevant property for the performer of a spoken role in a creative work such as animation, which fits the question about who originally voiced Meg Griffin. Now I will query the original voice actor for Meg Griffin (wd:Q908772) using this property.

[Tool]
Got 2 rows and 2 columns:
| voiceActor                 | voiceActorLabel    |
| -------------------------- | ------------------ |
| Lacey Chabert (wd:Q232910) | Lacey Chabert (en) |
| Mila Kunis (wd:Q37628)     | Mila Kunis (en)    |

[Assistant] The query returned two voice actors for Meg Griffin: Lacey Chabert and Mila Kunis. To determine who originally voiced Meg, I need to check which of these voice actors was the first or original one. I will check the statements or qualifiers related to the voice actor property for Meg Griffin to see if there is a qualifier indicating the original or first voice actor.

[Tool]
Got 2 rows and 3 columns:
| subject                  | property               | object                     |
| ------------------------ | ---------------------- | -------------------------- |
| Meg Griffin (wd:Q908772) | voice actor (wdt:P725) | Mila Kunis (wd:Q37628)     |
| Meg Griffin (wd:Q908772) | voice actor (wdt:P725) | Lacey Chabert (wd:Q232910) |

[Assistant] The direct statements do not indicate which voice actor was the original one. I will now check the detailed statements (with qualifiers) for the voice actor property of Meg Griffin to see if there is a qualifier indicating the original or first voice actor.

[Tool]
Got 2 rows and 3 columns:
| subject                  | property             | object                                         |
| ------------------------ | -------------------- | ---------------------------------------------- |
| Meg Griffin (wd:Q908772) | voice actor (p:P725) | s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d |
| Meg Griffin (wd:Q908772) | voice actor (p:P725) | s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba |

[Assistant] There are two statements for the voice actor property with qualifiers. I will now check the details of these statements to find any qualifier indicating the original or first voice actor.

[Tool]
Got 6 rows and 3 columns:
| subject                                        | property              | object                              |
| ---------------------------------------------- | --------------------- | ----------------------------------- |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | start time (pq:P580)  | 1999-12-26T00:00:00Z (xsd:dateTime) |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | voice actor (ps:P725) | Mila Kunis (wd:Q37628)              |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | wikibase:rank         | wikibase:NormalRank                 |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | rdf:type              | wikibase:BestRank                   |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | start time (pqv:P580) | v:f3464911887585a185abfe9a3a6348d1  |
| s:Q908772-2df0fb71-42b4-067b-f562-ebbe815d170d | rdf:type              | wikibase:Statement                  |

[Tool]
Got 18 rows and 3 columns, showing the first 10 rows below:
| subject                                        | property              | object                                |
| ---------------------------------------------- | --------------------- | ------------------------------------- |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | start time (pq:P580)  | 1999-01-31T00:00:00Z (xsd:dateTime)   |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | end time (pq:P582)    | 1999-09-30T00:00:00Z (xsd:dateTime)   |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | voice actor (ps:P725) | Lacey Chabert (wd:Q232910)            |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | pq:P10663             | Death Has a Shadow (wd:Q1191505)      |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | wikibase:rank         | wikibase:NormalRank                   |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | rdf:type              | wikibase:BestRank                     |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | start time (pqv:P580) | v:4d3b247501548c614f1e15774931d252    |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | end time (pqv:P582)   | v:82dcc86a69d08b486bc109e94c737a9d    |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | pq:P10663             | I Never Met the Dead Man (wd:Q253099) |
| s:Q908772-b7b7d9a6-4308-76d3-ec32-48dab73062ba | pq:P10663             | Chitty Chitty Death Bang (wd:Q860840) |
| ...                                            | ...                   | ...                                   |

[Assistant]
The statement with voice actor Mila Kunis has a start time qualifier of 1999-12-26. The statement with voice actor Lacey Chabert has a start time qualifier of 1999-01-31 and an end time qualifier of 1999-09-30. This indicates that Lacey Chabert originally voiced Meg Griffin before Mila Kunis.

I will now formulate the final SPARQL query to return the original voice actor of Meg Griffin based on the earliest start time for the voice actor property.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query contains a syntax error because the OPTIONAL clause is placed outside the main WHERE block, which is not valid. The OPTIONAL clause should be inside the WHERE block. Also, the query should ensure it retrieves the original voice actor of Meg Griffin (Q908772) by using the correct property for voice actors (P725) and ordering by the start time qualifier (P580) to get the earliest actor. The query should return the actor's identifier and label within the same WHERE block. Please fix the syntax and structure of the query to make it executable and correctly retrieve the original voice actor.

[Assistant] Thank you for the feedback. I will fix the syntax error by placing the OPTIONAL clause inside the WHERE block. I will also ensure the query retrieves the original voice actor of Meg Griffin (Q908772) by using the voice actor property (P725) and ordering by the start time qualifier (P580) to get the earliest actor. The query will return the actor's identifier and label within the same WHERE block. I will now correct and execute the updated query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the original voice actor of Meg Griffin by selecting the voice actor with the earliest start time qualifier. The answer 'Lacey Chabert' is accurate according to the data. The query also optionally retrieves the English label for readability. The approach and result are appropriate and complete for the user's question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?placeOfDeath ?placeOfDeathLabel WHERE {
  wd:Q714185 wdt:P20 ?placeOfDeath .
  OPTIONAL {
    ?placeOfDeath rdfs:label ?placeOfDeathLabel FILTER ( LANG( ?placeOfDeathLabel ) = "en" )
  }
}

Jenni Rivera's body was found in Iturbide.

[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 did they find jenni rivera's body?

[Assistant]
The question asks for the location where Jenni Rivera's body was found. To answer this, I need to identify the entity for Jenni Rivera in Wikidata and then find a property related to the location where her body was found or discovered.

Step 1: Search for the entity "Jenni Rivera" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Jenni Rivera, also known as Jenny Rivera, Dolores Janney Rivera Saavedra (wd:Q714185): American singer (1969–2012), television producer, singer-songwriter, recording artist, record producer, businessperson, film actor, composer, singer, actor
2. Jennifer Rivera (wd:Q22088654): American opera singer, opera singer
3. Jennifer Rivera (wd:Q99230893): rhythmic gymnast
4. Jenni Rivera Fashion (wd:Q18359270): web-based fashion boutique
5. Jenni Rivera: Mariposa de Barrio, also known as Mariposa de Barrio (wd:Q29267690): television series
6. Jenniffer López, also known as Jenniffer Katherine Lopez Rivera (wd:Q26131407): weightlifter
7. Jenni Rivera, Mexican-American Singer, Dies at 43 (wd:Q123654230): The New York Times article (December 10, 2012)
8. Rivera (wd:Q646498): city in Uruguay
9. Rivera (wd:Q1526269): Colombian municipality of the department of Huila
10. Rivera, also known as Rivera, Switzerland, Rivera TI (wd:Q663061): village and former municipality in Mendrisio in the canton of Ticino, Switzerland

[Assistant] The entity for Jenni Rivera is wd:Q714185, which corresponds to the American singer Jenni Rivera (1969–2012). Now I need to find a property related to the location where her body was found or discovered. I will search for properties related to "body found" or "discovered" for this entity.

[Tool]
Top 10 property alternatives:
1. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as p/wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
2. place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as p/wdt): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
3. Find a Grave memorial ID, also known as FaG ID, FaGID, Find A Grave grave ID, Findagrave ID, Find A Grave memorial ID (wd:P535 as p/wdt): identifier of an individual's burial place in the Find a Grave database
4. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as p/wdt): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
5. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as p/wdt): dissolved, abolished or demolished date, date on which the subject died, end time
6. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as p/wdt): significant or notable events associated with the subject
8. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
9. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
10. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

No other items found

[Assistant] There is no direct property indicating the location where Jenni Rivera's body was found. However, the property "place of death" (wdt:P20) might be relevant as it indicates the location of death, which could be related to where the body was found. I will check the place of death for Jenni Rivera.

[Tool]
Got 1 row and 2 columns:
| placeOfDeath             | placeOfDeathLabel |
| ------------------------ | ----------------- |
| Iturbide (wd:Q116918876) | Iturbide (en)     |

[Assistant] Jenni Rivera's place of death is Iturbide. This is likely the location where her body was found. I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the place of death for Jenni Rivera using the property wdt:P20. The result shows that her body was found in Iturbide, which matches the human-readable answer provided. The query includes an optional clause to get the English label of the place, which is appropriate. The answer is accurate and complete based on the data from Wikidata. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?currency ?currencyLabel WHERE {
  wd:Q29 wdt:P38 ?currency .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| currency        | currencyLabel |
| --------------- | ------------- |
| Euro (wd:Q4916) | euro (en)     |

The currency used by Spain is the Euro (wd:Q4916).

[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 money does spain use?

[Assistant]
To answer the question "What money does Spain use?" I need to find the currency used by the country Spain in the knowledge graph.

Step 1: Identify the entity for Spain.
Step 2: Identify the property for currency or money used by a country.
Step 3: Query the currency used by Spain.

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

[Tool]
Top 10 entity alternatives:
1. Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa
2. Spain men's national football team, also known as La Furia, The Spanish Fury, The Red One, The Red Fury, The Fury (wd:Q42267): men's national association football team representing Spain
3. Second Spanish Republic, also known as Spain (wd:Q178038): political regime established in Spain between April 14, 1931 and April 1, 1939
4. New Spain, also known as Colonial Central America, Central America under Spain, Viceroyalty of New Spain, Spanish Mexico, Spanish Central America (wd:Q170603): viceroyalty of the Spanish Empire (1535-1821)
5. Spain under the Restoration, also known as Bourbon Restoration, Spain, Second Bourbon Restoration, Restoration, Restoration (Spain) (wd:Q1044536): name given to a period between 1874 (end of First Spanish Republ...econd Spanish Republic), and the state of Spain during that time
6. Kingdom of Spain (1820-1823), also known as Kingdom of Spain, Spain, Trienio Liberal (wd:Q238809): 1820–1823 Spanish political period
7. Spain under Joseph Bonaparte, also known as Kingdom of Spain, Napoleonic Spain, Spain (wd:Q1709185): Napoleonic client state (1808–1813)
8. Sexenio Democrático, also known as Kingdom of Spain, Spain (wd:Q12411956): 1868–1874 period of fu under a provisional government
9. Ominous Decade, also known as Kingdom of Spain, second restoration of absolutism, Spain (wd:Q2378204): period in the history of Spain, corresponding to the second rest...reign of Fernando VII from August 31, 1823 to September 29, 1833
10. Hispanic Monarchy, also known as Spains, Hispanic Crown, Spain, Kingdom of Spains, Crown of Spain (wd:Q766543): (1479-1716) set of territories distributed throughout the world,...monarch and corresponding to the period of the House of Habsburg

[Assistant] The entity for Spain as a country is wd:Q29 (Kingdom of Spain). Next, I need to find the property that represents the currency used by a country. I will search for properties related to "currency" or "money" used by the entity Spain (wd:Q29).

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as p/wdt): currency used by item, uses
2. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as p/wdt): market value of all officially recognized final goods and services produced within a country in a given period of time
3. flag, also known as flag description (wd:P163 as p/wdt): subject's flag
4. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. VAT rate, also known as goods and services tax rate, GST, sales tax, taxation rate for sales, tax rate for sales (wd:P2855 as p/wdt): percentage value-added tax in this country or region. Do not use for sales tax. For specialised rates, use qualifiers
6. The New Yorker topic ID, also known as TNY ID, The NewYorker topic ID, New Yorker topic ID, NewYorker topic ID, newyorker.com (wd:P13317 as p/wdt): identifier of a topic on The New Yorker website
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
8. continent (wd:P30 as p/wdt): continent of which the subject is a part, located in/on physical feature
9. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity
10. located in time zone, also known as TZ, time zone, timezone (wd:P421 as p/wdt): time zone for this item

No other items found

[Assistant]
The property "currency" (wdt:P38) is the appropriate property for the currency used by an item, such as a country.

Now I will write a SPARQL query to get the currency used by Spain (wd:Q29) using the property wdt:P38.

[Tool]
Got 1 row and 2 columns:
| currency        | currencyLabel |
| --------------- | ------------- |
| Euro (wd:Q4916) | euro (en)     |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the currency used by Spain (wd:Q29) using the property wdt:P38 (currency). The query also optionally retrieves the English label of the currency. The result correctly identifies the Euro (wd:Q4916) as the currency of Spain. The answer is accurate and complete, and the query follows the rules for returning identifiers and labels. No further refinement is necessary.