PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?party WHERE {
  wd:Q91 wdt:P102 ?party .
}

Got 3 rows and 1 column:
| ?party                           |
| -------------------------------- |
| Republican Party (wd:Q29468)     |
| Whig Party (wd:Q42183)           |
| National Union Party (wd:Q80719) |

Abraham Lincoln was a member of the Republican Party, the Whig Party, and the National Union Party.

[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 party was abe lincoln part of?

[Assistant]
To answer the question about which party Abraham Lincoln was a part of, I need to first identify the entity for Abraham Lincoln and then find the property that indicates his political affiliation.

### Step 1: Identify the entity for Abraham Lincoln
I will use the `search_entity` function to find the entity for Abraham Lincoln.

```json
{
  "name": "search_entity",
  "arguments": {
    "kg": "wikidata",
    "query": "abraham lincoln"
  }
}
```

Let's execute this to find the entity for Abraham Lincoln.

[Tool]
Top 10 entity alternatives:
1. Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer
2. USS Abraham Lincoln, also known as CVN-72, Abraham Lincoln, USS Abraham Lincoln CVN-72 (wd:Q587557): 1988 Nimitz-class aircraft carrier
3. Abraham Lincoln (wd:Q166089): 1930 film by D. W. Griffith
4. Statue of Abraham Lincoln, also known as Abraham Lincoln (wd:Q4669005): statue at the Lincoln Memorial, Washington, D.C.
5. Abraham Lincoln, also known as Captain Abraham Lincoln (wd:Q2821841): grandfather of president Abraham Lincoln (1744-1786), military personnel
6. Abraham Lincoln, also known as Abraham Lincoln Statue, Statue of Abraham Lincoln (wd:Q16001435): artwork by Lot Flannery
7. Abraham Lincoln (wd:Q10322725): 1869 painting by George P.A. Healy
8. The Dramatic Life of Abraham Lincoln, also known as Abraham Lincoln, Dramatic Life of Abraham Lincoln (wd:Q7730887): 1924 film by Phil Rosen
9. Abraham Lincoln (wd:Q4668998): 1924 film by J. Searle Dawley
10. Statue of Abraham Lincoln, also known as Abraham Lincoln, Statue of Abraham Lincoln (Lincoln, Nebraska), The Gettysburg Lincoln (wd:Q4669002): statue in Lincoln, Nebraska by Daniel Chester French

[Assistant]
The top result for Abraham Lincoln is `wd:Q91`, which refers to the president of the United States from 1861 to 1865. This is the entity we need.

### Step 2: Identify the property for political affiliation
Next, I need to find the property that indicates political affiliation. I will use the `search_property` function to find this property.

```json
{
  "name": "search_property",
  "arguments": {
    "kg": "wikidata",
    "query": "political party"
  }
}
```

Let's execute this to find the property for political affiliation.

[Tool]
Top 10 property alternatives:
1. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): the political party of which a person is or has been a member or otherwise affiliated, member of
2. political alignment, also known as political position, alignment (wd:P1387 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): political position within the left–right political spectrum
3. political coalition, also known as electoral block, political bloc, political alliance, electoral list, electoral alliance (wd:P5832 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): agreement for cooperation between different political parties, member of
4. position held, also known as function, held position, holds position, job, office held (wd:P39 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): subject currently or formerly holds the object position or public office
5. parliamentary group, also known as faction, party organization, party (wd:P4100 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): parliamentary group to which a member of a parliament belongs, member of
6. political ideology, also known as editorial viewpoint, has political ideology, ideology, official ideology, official political ideology (wd:P1142 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): political ideology of an organization or person or of a work (such as a newspaper)
7. candidate, also known as candidate in this election, has election candidate, electoral candidate, election has candidate (wd:P726 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person or party that is an option for an office in this election, participant
8. successful candidate, also known as election winner, winning candidate, winner of election, election won by, elected (wd:P991 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person(s) or political organization(s) elected after the election, candidate, winner
9. candidacy in election, also known as ran in election, running in election, election candidacy, candidate in election, candidate in (wd:P3602 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): election where the subject is a candidate, participant in
10. participant, also known as suspect, player, party, participants, has participant (wd:P710 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person, group of people or organization (object) that actively t...ct has role" (P3831). Use P1923 for participants that are teams., significant person

[Assistant]
The top result for the property indicating political affiliation is `wd:P102`, which stands for "member of political party."

### Step 3: Build and execute the SPARQL query
Now that we have the entity for Abraham Lincoln (`wd:Q91`) and the property for political affiliation (`wd:P102`), we can build a SPARQL query to find out which party Abraham Lincoln was a part of.

```sparql
SELECT ?party WHERE {
  wd:Q91 wdt:P102 ?party .
}
```

Let's execute this query to get the result.

[Tool]
Got 3 rows and 1 column:
| ?party                           |
| -------------------------------- |
| Republican Party (wd:Q29468)     |
| Whig Party (wd:Q42183)           |
| National Union Party (wd:Q80719) |

[Assistant]
The SPARQL query returned three political parties that Abraham Lincoln was a part of:

1. **Republican Party** (`wd:Q29468`)
2. **Whig Party** (`wd:Q42183`)
3. **National Union Party** (`wd:Q80719`)

Abraham Lincoln was a member of multiple political parties during his career, but he is most famously associated with the Republican Party.

### Final Answer
Abraham Lincoln was a member of the Republican Party, the Whig Party, and the National Union Party.

Here is the final SPARQL query and answer:

```sparql
SELECT ?party WHERE {
  wd:Q91 wdt:P102 ?party .
}
```

Answer: Abraham Lincoln was a member of the Republican Party, the Whig Party, and the National Union Party.

Let's finalize this with the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?product WHERE {
  wd:Q95 wdt:P1056 ?product
}

Got 8 rows and 1 column:
| ?product                       |
| ------------------------------ |
| Software tools (wd:Q111897729) |
| Google Maps (wd:Q12013)        |
| Google Pay (wd:Q19834616)      |
| Google Ads (wd:Q271982)        |
| search engine (wd:Q4182287)    |
| Google Voice (wd:Q51712)       |
| Gmail (wd:Q9334)               |
| Google Search (wd:Q9366)       |

The products and services offered by Google include: 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 the products and/or services offered by Google, we need to identify the entity for Google and then find the properties that describe its products and services.

### Step 1: Identify the entity for Google
Let's start by searching for the entity "Google" in the knowledge graph.

[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 top result for "Google" is `wd:Q95`, which represents Google LLC, the American multinational technology company. We will use this entity to find the products and services it offers.

### Step 2: Identify properties related to products and services
Next, we need to find properties that describe the products and services offered by a company. Let's search for properties related to "products" and "services".

[Tool]
Top 10 property alternatives:
1. product or material produced, also known as products, product or service provided, product, material, or service produced or provided, product, producer of (wd:P1056 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): 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. 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 prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): 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
3. typically sells, also known as product, sells, sold products, usually sells (wd:P7163 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): type of goods particular type of shops typically sell
4. official shop URL, also known as online store, shop, shop URL, store, store URL (wd:P10225 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): official URL where the agent sells products/merchandise, official website
5. catalog, also known as catalogue, registry, exhibition catalogue, cat. (wd:P972 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): catalog for the item, or, as a qualifier of P528 – catalog for which the 'catalog code' is valid, part of
6. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): 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
7. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): award or recognition received by a person, organization or creative work
8. grants, also known as awards, bestows, confers, gives out (wd:P5460 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): confers degree, honor, award, prize, title, certificate or medal denoting achievement to a person or organization
9. number of representations, also known as shows, performances, number of shows, number of concerts, no. of shows (wd:P5027 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): number of shows (including the premiere) of a concert tour or a performing arts production
10. depicts, also known as portrays, presents, preserves, quotes, represents (wd:P180 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): entity visually depicted in an image, literarily described in a ...o an audiovisual or other medium; see also P921,  'main subject', has part(s)

[Tool]
Top 10 property alternatives:
1. product or material produced, also known as products, product or service provided, product, material, or service produced or provided, product, producer of (wd:P1056 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): 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. 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 prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): 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
3. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): notable scientific, artistic or literary work, or other work of significance among subject's works
4. occupation, also known as job, work, vocation, profession, employment (wd:P106 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
5. published in, also known as song on album, tome of the book, tome of, track of, track on (wd:P1433 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): larger work that a given work was published in, like a book, journal or music album, part of
6. number of representations, also known as shows, performances, number of shows, number of concerts, no. of shows (wd:P5027 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): number of shows (including the premiere) of a concert tour or a performing arts production
7. depicts, also known as portrays, presents, preserves, quotes, represents (wd:P180 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): entity visually depicted in an image, literarily described in a ...o an audiovisual or other medium; see also P921,  'main subject', has part(s)
8. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): sports teams or clubs that the subject represents or represented, member of
9. service options (wd:P11424 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): options for eating at a restaurant, café, etc
10. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): 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

[Assistant]
From the search results, the property `wd:P1056` (product or material produced) seems to be the most relevant for finding the products and services offered by Google. Let's use this property to construct a SPARQL query to find the products and services of Google.

### Step 3: Construct the SPARQL query
We will query for the products and services of Google using the `wd:P1056` property.

[Tool]
Got 8 rows and 1 column:
| ?product                       |
| ------------------------------ |
| Software tools (wd:Q111897729) |
| Google Maps (wd:Q12013)        |
| Google Pay (wd:Q19834616)      |
| Google Ads (wd:Q271982)        |
| search engine (wd:Q4182287)    |
| Google Voice (wd:Q51712)       |
| Gmail (wd:Q9334)               |
| Google Search (wd:Q9366)       |

[Assistant]
The SPARQL query has returned the following products and services offered by Google:

- Software tools (wd:Q111897729)
- Google Maps (wd:Q12013)
- Google Pay (wd:Q19834616)
- Google Ads (wd:Q271982)
- Search engine (wd:Q4182287)
- Google Voice (wd:Q51712)
- Gmail (wd:Q9334)
- Google Search (wd:Q9366)

These results provide a good list of the products and services that Google offers to its customers.

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

```sparql
SELECT ?product WHERE { wd:Q95 wdt:P1056 ?product }
```

The products and services offered by Google include:
- Software tools
- Google Maps
- Google Pay
- Google Ads
- Search engine
- Google Voice
- Gmail
- Google Search

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?team WHERE {
  wd:Q1374361 wdt:P54 ?team .
}

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]
To answer the question "Who did Tom Landry play for?", we need to identify the entity for Tom Landry and then find the teams he played for. Let's start by searching for Tom Landry in the knowledge graph.

### Step 1: Search for Tom Landry
I will use the `search_entity` function to find the entity for Tom Landry.

```json
{
  "name": "search_entity",
  "arguments": {
    "kg": "wikidata",
    "query": "Tom Landry"
  }
}
```

Let's execute this search.

[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 top result for "Tom Landry" is `wd:Q1374361`, which matches the description of the American football coach and player. We will use this entity to find out which team(s) he played for.

### Step 2: Find the Teams Tom Landry Played For
We need to find the property that indicates the team(s) a player played for. Let's search for properties related to "played for" or "team".

```json
{
  "name": "search_property",
  "arguments": {
    "kg": "wikidata",
    "query": "played for"
  }
}
```

Let's execute this search.

[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 prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): sports teams or clubs that the subject represents or represented, member of
2. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): musical instrument that a person plays or teaches or used in a music occupation, uses
3. instrumentation, also known as scoring, scored for, orchestration, instruments employed, orchestrated for (wd:P870 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): combination of musical instruments employed in a composition or accompanying a (folk) dance
4. participant, also known as suspect, player, party, participants, has participant (wd:P710 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person, group of people or organization (object) that actively t...ct has role" (P3831). Use P1923 for participants that are teams., significant person
5. sport, also known as play, plays, sport played, sports (wd:P641 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): sport that the subject participates or participated in or is associated with
6. employer, also known as working at, working for, working place, works at, works for (wd:P108 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person or organization for which the subject works or worked, affiliation
7. time played, also known as minutes played (wd:P9140 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): time (usually minutes) played by a participant in a sporting event
8. number of matches played/races/starts, also known as gp, starts, races, number of games played, mp (wd:P1350 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): matches or games a player or a team played during an event. Also...matches a player officially appeared in during the whole career.
9. points/goal scored by, also known as goal scored by, points scored by, scored by, scorer (wd:P1363 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person who scored a point or goal in a game
10. set in environment, also known as set in location, takes place in, setting location, playing in, narrative set in (wd:P8411 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): environment (geographic feature, building type, etc.) the narrative work is set in, significant place, depicts

[Assistant]
The property `wd:P54` (member of sports team) seems to be the most relevant for finding the team(s) Tom Landry played for. Let's use this property to construct a SPARQL query to find the teams Tom Landry played for.

### Step 3: Construct and Execute the SPARQL Query
We will query for the teams Tom Landry played for using the `wd:P54` property.

```sparql
SELECT ?team WHERE {
  wd:Q1374361 wdt:P54 ?team .
}
```

Let's execute this query.

[Tool]
Got 2 rows and 1 column:
| ?team                                  |
| -------------------------------------- |
| New York Giants (wd:Q190618)           |
| Texas Longhorns football (wd:Q7707821) |

[Assistant]
The SPARQL query returned two teams that Tom Landry played for: the New York Giants and the Texas Longhorns football team.

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

Let's provide the final answer with the SPARQL query.

```json
{
  "name": "answer",
  "arguments": {
    "kg": "wikidata",
    "sparql": "SELECT ?team WHERE { wd:Q1374361 wdt:P54 ?team . }",
    "answer": "Tom Landry played for the New York Giants and the Texas Longhorns football team."
  }
}
```

[Tool] Stopped generation process


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

Got 1 row and 2 columns:
| ?currency                    | ?currencyLabel  |
| ---------------------------- | --------------- |
| Moroccan dirham (wd:Q200192) | Moroccan dirham |

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 about the currency to take to Morocco, we need to identify the official currency of Morocco. Let's start by searching for the entity representing Morocco and then look for the property that indicates the currency used in a country.

[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 top result for "Morocco" is the sovereign state in North Africa, which is the entity we are looking for. Now, let's find the property that indicates the currency used in a country.

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): currency used by item, uses
2. ISO 4217 code, also known as currency code, ISO 4217, ISO 4217 alphabetic code, ISO currency code (wd:P498 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): identifier for a currency per ISO 4217
3. price, also known as cost, exchange rate, list price, MSRP, published price (wd:P2284 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): published price listed or paid for a product (use with unit of currency)
4. prize money, also known as money, purse, value (wd:P2121 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): amount in a specific currency
5. cash (wd:P2232 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): the value of cash and securities held by a state government
6. currency symbol description (wd:P489 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): item with description of currency symbol, notation
7. face value, also known as coin value, numeric value of coin, value of coin (wd:P3934 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): value printed on a coin, stamp or banknote by the issuing authority
8. quantity, also known as amount, total number, total, qty, occurrences (wd:P1114 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): number of instances of this subject in the universe of the subje...e actual number of instances in Wikidata may be lower or higher)
9. item of property constraint, also known as claim value, value, qid, property value, item qualifier (wd:P2305 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): qualifier to define a property constraint in combination with "property constraint" (P2302)
10. numeric value, also known as numerical value, value (wd:P1181 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): numerical value of a number, a mathematical constant, or a physical constant

[Assistant]
The property `currency` (wd:P38) is the most relevant for our purpose. Now, let's construct a SPARQL query to find the currency used in Morocco.

We will use the entity `Morocco` (wd:Q1028) and the property `currency` (wd:P38) to retrieve the currency.

Let's execute the SPARQL query:

```sparql
SELECT ?currency
WHERE {
  wd:Q1028 wdt:P38 ?currency .
}
```

This query will return the currency used in Morocco.

[Tool]
Got 1 row and 1 column:
| ?currency                    |
| ---------------------------- |
| Moroccan dirham (wd:Q200192) |

[Assistant]
The currency used in Morocco is the Moroccan dirham (wd:Q200192).

To provide a complete answer, let's include the label of the currency in the query. We will use an OPTIONAL clause to fetch the label if available.

Here is the final SPARQL query:

```sparql
SELECT ?currency ?currencyLabel
WHERE {
  wd:Q1028 wdt:P38 ?currency .
  OPTIONAL { ?currency rdfs:label ?currencyLabel . FILTER(LANG(?currencyLabel) = "en") }
}
```

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

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

[Assistant]
The currency used in Morocco is the Moroccan dirham (wd:Q200192).

Therefore, the answer to the question "What currency should you take to Morocco?" is:

**Moroccan dirham**

Here is the final SPARQL query and answer:

```sparql
SELECT ?currency ?currencyLabel
WHERE {
  wd:Q1028 wdt:P38 ?currency .
  OPTIONAL { ?currency rdfs:label ?currencyLabel . FILTER(LANG(?currencyLabel) = "en") }
}
```

Answer: **Moroccan dirham**

[Tool] Stopped generation process


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

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

The primary language of China is Standard Mandarin (Standard Chinese).

[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 determine the primary language of China, we need to identify the entity for China and then find the property that indicates the official or primary language of a country. Let's start by searching for the entity representing China.

[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] From the search results, the most relevant entity for China is "People's Republic of China" (wd:Q148). Next, we need to find the property that indicates the official or primary language of a country. Let's search for properties related to "official language" or "primary language."

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): 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 prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): label for the items in their official language  or their original language, name
3. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): language status identifier by Ethnologue.com using EGIDS scale
4. language regulatory body, also known as language authority, regulatory body (wd:P1018 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): regulatory body of a language
5. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): language(s) that a person or a people speaks, writes or signs, including the native language(s)
6. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): language or languages a person has learned from early childhood, languages spoken, written or signed
7. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): language widely used (spoken or written) in this place or at this event or organisation
8. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
9. programmed in, also known as language, programming language, written in (wd:P277 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): the programming language(s) in which the software is developed
10. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): language in which the writer has written their work, languages spoken, written or signed

[Assistant]
The most relevant property for finding the official language of a country is "official language" (wd:P37). Now, let's construct a SPARQL query to find the official language of China (wd:Q148).

Here is the initial SPARQL query:

```sparql
SELECT ?language
WHERE {
  wd:Q148 wdt:P37 ?language .
}
```

Let's execute this query to see the results.

[Tool]
Got 3 rows and 1 column:
| ?language                       |
| ------------------------------- |
| Standard Chinese (wd:Q727694)   |
| Chinese (wd:Q7850)              |
| languages of China (wd:Q835866) |

[Assistant]
The query returned three results for the official language of China:
1. Standard Chinese (wd:Q727694)
2. Chinese (wd:Q7850)
3. Languages of China (wd:Q835866)

To provide a more precise answer, we need to understand what these entities represent. Let's look at the labels and descriptions of these entities to determine which one is the primary language of China.

We can use the `rdfs:label` property to get the labels of these entities. Here is the updated SPARQL query:

```sparql
SELECT ?language ?label
WHERE {
  wd:Q148 wdt:P37 ?language .
  OPTIONAL { ?language rdfs:label ?label . FILTER(LANG(?label) = "en") }
}
```

Let's execute this query to get the labels.

[Tool]
Got 3 rows and 2 columns:
| ?language                       | ?label             |
| ------------------------------- | ------------------ |
| Standard Chinese (wd:Q727694)   | Standard Mandarin  |
| Chinese (wd:Q7850)              | Chinese            |
| languages of China (wd:Q835866) | languages of China |

[Assistant]
The query results provide the following labels for the official languages of China:
1. Standard Chinese (wd:Q727694) - labeled as "Standard Mandarin"
2. Chinese (wd:Q7850) - labeled as "Chinese"
3. Languages of China (wd:Q835866) - labeled as "languages of China"

"Standard Mandarin" (Standard Chinese) is the primary and most widely used official language of China. Therefore, the primary language of China is Standard Mandarin.

Here is the final SPARQL query and answer:

```sparql
SELECT ?language ?label
WHERE {
  wd:Q148 wdt:P37 ?language .
  OPTIONAL { ?language rdfs:label ?label . FILTER(LANG(?label) = "en") }
}
```

The primary language of China is **Standard Mandarin** (Standard Chinese).

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?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 |
| Qatar Investment Authority (wd:Q1571175)            | Qatar Investment Authority            |
| Porsche Automobil Holding SE (wd:Q2104551)          | Porsche Automobil Holding SE          |

The owners of the Volkswagen car company are: 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?", we need to identify the entity representing Volkswagen and then find out who owns it. Let's start by searching for the entity representing Volkswagen.

[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]
From the search results, the entity representing the Volkswagen car company is likely "Volkswagen Group" (wd:Q156578), which is described as a German automotive manufacturing conglomerate. Next, we need to find out who owns this company. We will look for a property that indicates ownership, such as "owner" or "shareholder."

Let's search for properties related to ownership.

[Tool]
Top 10 property alternatives:
1. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): owner of the subject
2. owner of, also known as owns, owns property, shareholder of (wd:P1830 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): entities owned by the subject
3. has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): subsidiary of a company or organization; generally a fully owned...siness division" (P199). Opposite of parent organization (P749)., has part(s), owner of
4. copyright holder, also known as licensor, proprietor, copyright owner, copyright ‘owner’ (wd:P3931 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person or organisation who holds the copyright of a work according to the Berne Convention, owned by
5. beneficial owner, also known as beneficial ownership, UBO (wd:P12621 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): natural person or persons who ultimately owns or controls a company or organisation
6. properties for this type, also known as uses properties, Wikidata properties for this type, Wikidata properties for this class, uses property, things one could say about (wd:P1963 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): when this subject is used as object of “instance of”, the following properties normally apply
7. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): main Wikidata property for this item
8. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
9. afterward owned by, also known as subsequently owned by, purchased by, owned after by, new owner, bought by (wd:P11812 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person or institution that owned the subject after stated event....ficant event (P793)" for events like sales, auctions, gifts, etc
10. leased to, also known as lessee (wd:P13047 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person or organisation that holds or was granted a lease on the subject, occupant

[Assistant]
The property "owned by" (wd:P127) seems to be the most relevant for our purpose. We will use this property to find out who owns the Volkswagen Group (wd:Q156578).

Let's construct a SPARQL query to find the owner of the Volkswagen Group.

```sparql
SELECT ?owner WHERE {
  wd:Q156578 wdt:P127 ?owner .
}
```

We will execute this query to get the result.

[Tool]
Got 3 rows and 1 column:
| ?owner                                              |
| --------------------------------------------------- |
| Hannoversche Beteiligungsgesellschaft (wd:Q1529289) |
| Qatar Investment Authority (wd:Q1571175)            |
| Porsche Automobil Holding SE (wd:Q2104551)          |

[Assistant]
The query returned three entities that own the Volkswagen Group:

1. Hannoversche Beteiligungsgesellschaft (wd:Q1529289)
2. Qatar Investment Authority (wd:Q1571175)
3. Porsche Automobil Holding SE (wd:Q2104551)

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

```sparql
SELECT ?owner ?ownerLabel WHERE {
  wd:Q156578 wdt:P127 ?owner .
  OPTIONAL { ?owner rdfs:label ?ownerLabel . FILTER(LANG(?ownerLabel) = "en") }
}
```

We will execute this updated query to get the labels.

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

[Assistant]
The query results show that the Volkswagen Group (Volkswagen car company) is owned by the following entities:

1. **Hannoversche Beteiligungsgesellschaft** (wd:Q1529289)
2. **Qatar Investment Authority** (wd:Q1571175)
3. **Porsche Automobil Holding SE** (wd:Q2104551)

These are the major shareholders of the Volkswagen Group.

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

```sparql
SELECT ?owner ?ownerLabel WHERE {
  wd:Q156578 wdt:P127 ?owner .
  OPTIONAL { ?owner rdfs:label ?ownerLabel . FILTER(LANG(?ownerLabel) = "en") }
}
```

The owners of the Volkswagen car company are:
- Hannoversche Beteiligungsgesellschaft
- Qatar Investment Authority
- Porsche Automobil Holding SE

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?team WHERE {
  wd:Q706908 wdt:P54 ?team .
}

Got 5 rows and 1 column:
| ?team                             |
| --------------------------------- |
| New York Yankees (wd:Q213417)     |
| Texas Rangers (wd:Q329816)        |
| Detroit Tigers (wd:Q650855)       |
| Washington Nationals (wd:Q825838) |
| Houston Astros (wd:Q848117)       |

Pudge Rodríguez has played for the 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 about which teams Pudge Rodríguez has played for, we need to identify the entity for Pudge Rodríguez and then find the teams he has been associated with through his career.

### Step 1: Identify the Entity for Pudge Rodríguez
Let's start by searching for the entity representing Pudge Rodríguez 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 top result for "Pudge Rodríguez" is Iván Rodríguez (wd:Q706908), which is the correct entity for the baseball player.

### Step 2: Identify the Property for Teams Played For
Next, we need to find the property that indicates the teams a player has played for. A common property for this in Wikidata is "member of sports team" (P54).

Let's verify this property.

[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 prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): sports teams or clubs that the subject represents or represented, member of
2. number of participants, also known as number of competitors, number of teams, participant count, participants, qty participants (wd:P1132 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): number of participants of an event, e.g. people or groups of people that take part in the event (NO units), quantity
3. number of matches played/races/starts, also known as gp, starts, races, number of games played, mp (wd:P1350 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): matches or games a player or a team played during an event. Also...matches a player officially appeared in during the whole career.
4. participating team, also known as teams (wd:P1923 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): like 'Participant' (P710) but for teams. For an event like a cyc...member of sports team' (P54) as a qualifier for the individuals), participant
5. number of wins, also known as games won, won, wins, W, sporting wins (wd:P1355 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): number of sporting matches, games or events won
6. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): league or competition in which team or player has played, or in which an event occurs, participant in
7. sports league level, also known as league level, sport league level, level on sport league pyramid, level on league pyramid, level on pyramid (wd:P3983 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): the level of the sport league in the sport league system
8. sports season of league or competition, also known as sport season, seasons of, edition of annual athletics meeting, season of sports tournament, season of sports league (wd:P3450 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): property that shows the competition of which the item is a season. Use P5138 for "season of club or team"., part of
9. sports discipline competed in, also known as sport discipline competed in, weight class competed in, sports event, sports disciplines competed in, sports discipline (wd:P2416 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): discipline an athlete competed in within a sport, field of work
10. season of club or team, also known as season of athletics program, season of club, season of team, sports season of club or team (wd:P5138 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): club or team that played the season

[Assistant]
The property "member of sports team" (P54) is indeed the correct property to use for identifying the teams a player has played for.

### Step 3: Construct the SPARQL Query
Now, let's construct a SPARQL query to find the teams that Pudge Rodríguez (Iván Rodríguez) has played for.

```sparql
SELECT ?team WHERE {
  wd:Q706908 wdt:P54 ?team .
}
```

This query will return the teams that Pudge Rodríguez has been a member of.

Let's execute this query to get the results.

[Tool]
Got 5 rows and 1 column:
| ?team                             |
| --------------------------------- |
| New York Yankees (wd:Q213417)     |
| Texas Rangers (wd:Q329816)        |
| Detroit Tigers (wd:Q650855)       |
| Washington Nationals (wd:Q825838) |
| Houston Astros (wd:Q848117)       |

[Assistant]
The SPARQL query has successfully returned the teams that Pudge Rodríguez (Iván Rodríguez) has played for. These teams are:

- New York Yankees (wd:Q213417)
- Texas Rangers (wd:Q329816)
- Detroit Tigers (wd:Q650855)
- Washington Nationals (wd:Q825838)
- Houston Astros (wd:Q848117)

### Final Answer
Pudge Rodríguez has played for the New York Yankees, Texas Rangers, Detroit Tigers, Washington Nationals, and Houston Astros.

Let's provide the final answer with the SPARQL query and the list of teams.

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?voiceActor ?startTime ?endTime WHERE {
  wd:Q908772 p:P725 ?voiceActorStatement .
  ?voiceActorStatement ps:P725 ?voiceActor .
  OPTIONAL {
    ?voiceActorStatement pq:P580 ?startTime .
  }
  OPTIONAL {
    ?voiceActorStatement pq:P582 ?endTime .
  }
}

Lacey Chabert (wd:Q232910) was the original voice actor for Meg Griffin on Family Guy.

[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 find out who originally voiced Meg on Family Guy, we need to identify the character "Meg" from the show and then find the voice actor associated with her, particularly during the original run of the show. Let's start by searching for the entity "Meg Griffin" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Stewie Griffin: The Untold Story, also known as Bang-o Was His Name-o, Stewie B. Goode, Stewie and Stu's Excellent Adventure, Family Guy Presents Stewie Griffin: The Untold Story, Bango Was His Name, Oh! (wd:Q684288): 2005 American adult animated Driect-to-DVD film Directed by Peter Michels and Peter Shin
2. Family Guy (wd:Q5930): American adult animated sitcom
3. Family Guy (wd:Q5930): American adult animated sitcom
4. 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
5. Griffin family (wd:Q10860912): fictional family from the animated series Family Guy
6. Family Guy (wd:Q5433143): pinball table
7. Family Guy, also known as Family Guy franchise (wd:Q55012102): American media franchise
8. Meg Griffin (wd:Q6807983): American radio disc jockey, radio personality, disc jockey
9. Family Guy: Peter Griffin's Guide to the Holidays, also known as Peter Griffin's Guide to the Holidays (wd:Q5433141): book by Danny Smith
10. Family Guy (wd:Q108370888): video game series

[Assistant]
From the search results, the correct entity for Meg Griffin from Family Guy is "Meg Griffin" (wd:Q908772). Now, let's find the voice actor associated with this character. We'll look for properties related to voice acting and then use those properties to find the voice actor.

First, let's search for properties related to voice acting.

[Tool]
Top 10 property alternatives:
1. voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member
2. Behind The Voice Actors person ID, also known as behindthevoiceactors.com person ID, BTVA person ID, BTVA ID (wd:P5007 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): identifier of a person on the website Behind The Voice Actors
3. Deutsche Synchronkartei dubbing voice actor ID, also known as Synchronkartei dubbing voice actor identifier, Synchronkartei dubbing voice actor ID, Deutsche Synchronkartei dubbing voice actor identifier (wd:P4727 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): identifier for a dubbing voice actor, in the synchronisation (dubbing) database Deutsche Synchronkartei
4. Behind The Voice Actors short ID, also known as BTVA short ID (wd:P7318 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): identifier of a short on the website Behind The Voice Actors
5. Behind The Voice Actors character ID, also known as Behind The Voice Actors character identifier, BTVA character ID, BTVA character identifier (wd:P5107 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): identifier of a character from the Behind The Voice Actors website
6. Behind The Voice Actors franchise ID, also known as BTVA franchise ID (wd:P5382 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): identifier of a franchise in Behind the Voice Actors
7. Behind The Voice Actors film ID, also known as Behind The Voice Actors movie ID, BTVA movie ID (wd:P5384 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): identifier of a film on the website Behind The Voice Actors
8. MyAnimeList people ID, also known as MyAnimeList actor ID, MyAnimeList voice actor ID, MyAnimeList staff ID, MyAnimeList person ID, MAL voice actor ID (wd:P4084 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): identifier for a person or group of people on MyAnimeList
9. audio recording of the subject's spoken voice, also known as voice recording, audio clip, spoken voice, speaking voice, recording of the subject's spoken voice (wd:P990 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): audio file representing the speaking voice of a person; or of an animated cartoon or other fictitious character, audio
10. voice type, also known as range of voice, register, tessitura, type of voice, vocal type (wd:P412 as prv/p/psn/psv/pqn/wdtn/wdt/prn/pqv/pq/ps/pr): person's voice type. expected values: soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass (and derivatives)

[Assistant]
The property "voice actor" (wd:P725) is the most relevant for our purpose. Now, let's use this property to find the voice actor for Meg Griffin (wd:Q908772).

I'll construct a simple SPARQL query to retrieve the voice actor for Meg Griffin.

```sparql
SELECT ?voiceActor WHERE {
  wd:Q908772 wdt:P725 ?voiceActor .
}
```

Let's execute this query.

[Tool]
Got 2 rows and 1 column:
| ?voiceActor                |
| -------------------------- |
| Lacey Chabert (wd:Q232910) |
| Mila Kunis (wd:Q37628)     |

[Assistant]
The query returned two voice actors for Meg Griffin: Lacey Chabert (wd:Q232910) and Mila Kunis (wd:Q37628). To determine who originally voiced Meg, we need to check the time periods during which each actor voiced the character.

Let's find the time periods for each voice actor. We can use the `pq:P580` (start time) and `pq:P582` (end time) qualifiers to get this information.

I'll construct a more detailed SPARQL query to include these qualifiers.

```sparql
SELECT ?voiceActor ?startTime ?endTime WHERE {
  wd:Q908772 p:P725 ?voiceActorStatement .
  ?voiceActorStatement ps:P725 ?voiceActor .
  OPTIONAL { ?voiceActorStatement pq:P580 ?startTime . }
  OPTIONAL { ?voiceActorStatement pq:P582 ?endTime . }
}
```

Let's execute this query.

[Tool]
Got 2 rows and 3 columns:
| ?voiceActor                | ?startTime           | ?endTime             |
| -------------------------- | -------------------- | -------------------- |
| Mila Kunis (wd:Q37628)     | 1999-12-26T00:00:00Z |                      |
| Lacey Chabert (wd:Q232910) | 1999-01-31T00:00:00Z | 1999-09-30T00:00:00Z |

[Assistant]
The query results show that:

- Mila Kunis (wd:Q37628) started voicing Meg Griffin on December 26, 1999, and there is no end date specified, indicating she has been the primary voice actor since then.
- Lacey Chabert (wd:Q232910) voiced Meg Griffin from January 31, 1999, to September 30, 1999.

Based on these dates, Lacey Chabert was the original voice actor for Meg Griffin, but Mila Kunis took over the role shortly after.

Therefore, the original voice actor for Meg Griffin on Family Guy is Lacey Chabert.

Here is the final SPARQL query and answer:

```sparql
SELECT ?voiceActor ?startTime ?endTime WHERE {
  wd:Q908772 p:P725 ?voiceActorStatement .
  ?voiceActorStatement ps:P725 ?voiceActor .
  OPTIONAL { ?voiceActorStatement pq:P580 ?startTime . }
  OPTIONAL { ?voiceActorStatement pq:P582 ?endTime . }
}
```

Answer: Lacey Chabert (wd:Q232910) was the original voice actor for Meg Griffin on Family Guy.

[Tool] Stopped generation process