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 DISTINCT ?item ?itemLabel WHERE {
  {
    wd:Q95 wdt:P1056 ?item .
    OPTIONAL {
      ?item rdfs:label ?itemLabel FILTER ( lang( ?itemLabel ) = "en" )
    }
  } UNION {
    wd:Q95 wdt:P355 ?item .
    OPTIONAL {
      ?item rdfs:label ?itemLabel FILTER ( lang( ?itemLabel ) = "en" )
    }
  }
}

Got 54 rows and 2 columns, showing the first 5 and last 5 rows below:
| item                               | itemLabel               |
| ---------------------------------- | ----------------------- |
| Google China (wd:Q1011981)         | Google China (en)       |
| DoubleClick (wd:Q1053674)          | DoubleClick (en)        |
| Google Open Source (wd:Q111351974) | Google Open Source (en) |
| Picnik (wd:Q1114200)               | Picnik (en)             |
| Software tools (wd:Q111897729)     | Software tools (en)     |
| ...                                | ...                     |
| Google Poland (wd:Q9274518)        | Google Poland (en)      |
| Gmail (wd:Q9334)                   | Gmail (en)              |
| Motorola Mobility (wd:Q934853)     | Motorola Mobility (en)  |
| Google Search (wd:Q9366)           | Google Search (en)      |
| Waze (wd:Q942327)                  | Waze (en)               |

Google offers a wide range of products and services to customers, including (but not limited to): Google Search, Gmail, Google Maps, Google Ads, Google Pay, Google Voice, Google Workspace, Google Cloud Platform, Waze, Blogger, YouTube, DoubleClick, and more. The query returns both the Wikidata IRIs and English labels for each product or service, including those offered directly and through subsidiaries.

[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 http://amur:7001

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]
Let's break down the question:

1. The main entity is "Google".
2. The question asks about "products and/or services" that Google offers to customers.

Step 1: Identify the entity for Google in Wikidata.
Step 2: Identify properties related to products and services offered by a company.
Step 3: Construct a query to find products and services offered by Google.

First, let's search for the entity "Google" in Wikidata.

[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 main entity for Google as a company is wd:Q95.

Next, I need to identify properties in Wikidata that relate to products and services offered by a company. I will search for properties related to "product" and "service".

[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

[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. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as p/wdt): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
3. 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
4. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as p/wdt): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
5. terms of service URL, also known as terms of service, terms of use, terms of use URL, TOS, ToS URL (wd:P7014 as p/wdt): URL linking to terms of service of the subject, URL
6. motto text, also known as mission statement, travel slogan, tourism slogan, tagline, strapline (wd:P1451 as p/wdt): short motivation sentence associated to item
7. 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.)
8. 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
9. 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])
10. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as p/wdt): location where a group or organization was formed, location of creation

No other items found

[Tool]
Got 8 rows and 3 columns:
| subject         | property                                                       | object                         |
| --------------- | -------------------------------------------------------------- | ------------------------------ |
| Google (wd:Q95) | product, material, or service produced or provided (wdt:P1056) | Google Search (wd:Q9366)       |
| Google (wd:Q95) | product, material, or service produced or provided (wdt:P1056) | Gmail (wd:Q9334)               |
| Google (wd:Q95) | product, material, or service produced or provided (wdt:P1056) | Google Maps (wd:Q12013)        |
| Google (wd:Q95) | product, material, or service produced or provided (wdt:P1056) | search engine (wd:Q4182287)    |
| Google (wd:Q95) | product, material, or service produced or provided (wdt:P1056) | Google Ads (wd:Q271982)        |
| Google (wd:Q95) | product, material, or service produced or provided (wdt:P1056) | Google Pay (wd:Q19834616)      |
| Google (wd:Q95) | product, material, or service produced or provided (wdt:P1056) | Google Voice (wd:Q51712)       |
| Google (wd:Q95) | product, material, or service produced or provided (wdt:P1056) | Software tools (wd:Q111897729) |

[Tool]
Got 8 rows and 2 columns:
| product                        | productLabel        |
| ------------------------------ | ------------------- |
| 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)  |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves products and services offered by Google using the property 'product, material, or service produced or provided' (wdt:P1056). However, the query only returns the IRIs of the products/services and does not include their labels, which would make the answer more human-readable. Additionally, the answer summary omits 'search engine' (wd:Q4182287), which appears in the query results but is not explicitly listed in the answer. To improve, add OPTIONAL { ?product rdfs:label ?productLabel. FILTER (lang(?productLabel) = "en") } to the query to retrieve English labels, and ensure all results are reflected in the answer summary.

[Assistant]
Thank you for the feedback. Here’s my step-by-step plan to refine the answer:

1. The property wdt:P1056 ("product, material, or service produced or provided") is correct for retrieving products and services offered by Google (wd:Q95).
2. To make the results more human-readable, I will include OPTIONAL { ?product rdfs:label ?productLabel. FILTER (lang(?productLabel) = "en") } in the query to retrieve English labels for each product/service.
3. I will ensure that all results, including 'search engine', are reflected in the answer summary.

Here is the improved SPARQL query and answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is generally correct and returns a reasonable set of products and services offered by Google using the property 'product, material, or service produced or provided' (wdt:P1056). However, this property may not capture the full breadth of Google's offerings, as some products or services might be linked via other properties such as 'offers' (P859), 'has part' (P527), or even 'subsidiary' (P355) for services operated under different entities. Consider expanding the query to include these properties or cross-checking for additional relevant properties to provide a more comprehensive answer. Also, ensure that the query does not miss any major Google products or services that are well-known but not linked via P1056.

[Assistant]
Thank you for the detailed feedback. To address it, I will:

1. Identify additional properties that could link Google to its products/services, such as 'offers' (P859), 'has part' (P527), and 'subsidiary' (P355).
2. Check if these properties are used for Google (wd:Q95) to link to products/services.
3. Expand the SPARQL query to include results from these properties, in addition to 'product, material, or service produced or provided' (P1056).
4. Ensure the query returns both IRIs and English labels for all results.

First, I will check if Google uses 'offers' (P859), 'has part' (P527), or 'subsidiary' (P355) to link to additional products or services.

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool]
Got 48 rows and 3 columns, showing the first 10 rows below:
| subject         | property                  | object                               |
| --------------- | ------------------------- | ------------------------------------ |
| Google (wd:Q95) | has subsidiary (wdt:P355) | Blogger (wd:Q171186)                 |
| Google (wd:Q95) | has subsidiary (wdt:P355) | Google DeepMind (wd:Q15733006)       |
| Google (wd:Q95) | has subsidiary (wdt:P355) | Google Ads (wd:Q271982)              |
| Google (wd:Q95) | has subsidiary (wdt:P355) | Google Workspace (wd:Q509284)        |
| Google (wd:Q95) | has subsidiary (wdt:P355) | Motorola Mobility (wd:Q934853)       |
| Google (wd:Q95) | has subsidiary (wdt:P355) | Waymo (wd:Q15330)                    |
| Google (wd:Q95) | has subsidiary (wdt:P355) | Boston Dynamics (wd:Q2298325)        |
| Google (wd:Q95) | has subsidiary (wdt:P355) | Waze (wd:Q942327)                    |
| Google (wd:Q95) | has subsidiary (wdt:P355) | Google Cloud Platform (wd:Q17054505) |
| Google (wd:Q95) | has subsidiary (wdt:P355) | X Development (wd:Q133928)           |
| ...             | ...                       | ...                                  |

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 137 for token UNION with content 'UNION' (the input most likely does not follow the grammar)

[Assistant]
It appears that my previous query failed due to incorrect placement of the OPTIONAL clause with UNION. In SPARQL, each branch of a UNION must be a complete pattern, including its own OPTIONALs.

I will rewrite the query so that each branch of the UNION includes its own OPTIONAL clause for the label. I will also include DISTINCT to avoid duplicates.

Here is the revised approach:
- Retrieve products/services via wdt:P1056 (product, material, or service produced or provided)
- Retrieve subsidiaries via wdt:P355 (has subsidiary)
- For each, get the English label

Let's try again.

[Tool]
Got 54 rows and 2 columns, showing the first 5 and last 5 rows below:
| item                               | itemLabel               |
| ---------------------------------- | ----------------------- |
| Google China (wd:Q1011981)         | Google China (en)       |
| DoubleClick (wd:Q1053674)          | DoubleClick (en)        |
| Google Open Source (wd:Q111351974) | Google Open Source (en) |
| Picnik (wd:Q1114200)               | Picnik (en)             |
| Software tools (wd:Q111897729)     | Software tools (en)     |
| ...                                | ...                     |
| Google Poland (wd:Q9274518)        | Google Poland (en)      |
| Gmail (wd:Q9334)                   | Gmail (en)              |
| Motorola Mobility (wd:Q934853)     | Motorola Mobility (en)  |
| Google Search (wd:Q9366)           | Google Search (en)      |
| Waze (wd:Q942327)                  | Waze (en)               |

[Tool] Stopped generation process


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 (wd:Q190618) and the Texas Longhorns football team (wd:Q7707821).

[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 http://amur:7001

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]
Let's break down the question:

1. The user is asking which teams Tom Landry played for.
2. We need to identify the entity for Tom Landry and the property that links a person to the teams they played for.

First, I will 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 most relevant entity for Tom Landry, the American football coach and player, is wd:Q1374361.

Next, I need to find the property that links a person to the teams they played for. I will search for properties related to "team played for".

[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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): sport that the subject participates or participated in or is associated with
3. supported sports team, also known as Fan of sports team, team supported, Supports sports team, Sports team supported, is a fan of team (wd:P6758 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): sports team for which a person or a group is a supporter
4. participating team, also known as teams (wd:P1923 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): person or organization occupying property, used by
6. promoted, also known as competitor promoted, player promoted, promotion, team promoted (wd:P2881 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): competitor or team promoted during competition
7. number of wins, also known as games won, won, wins, W, sporting wins (wd:P1355 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): number of sporting matches, games or events won
8. number of matches played/races/starts, also known as gp, starts, races, number of games played, mp (wd:P1350 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): matches or games a player or a team played during an event. Also...matches a player officially appeared in during the whole career.
9. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): league or competition in which team or player has played, or in which an event occurs, participant in
10. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): position or specialism of a player on a team

[Assistant]
The property "member of sports team" (wdt:P54) is the most relevant for finding out which teams Tom Landry played for.

Now, I will construct a SPARQL query to find all teams that Tom Landry (wd:Q1374361) was a member of, using the property wdt:P54. I will also try to retrieve 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=refine):
The SPARQL query correctly retrieves the teams Tom Landry played for by using the property 'member of sports team' (wdt:P54). However, the query only returns the IRIs of the teams and does not provide any human-readable labels, which would improve the answer's clarity. To refine the query, add OPTIONAL clauses to retrieve the rdfs:label for each team. This will make the result more user-friendly and complete, especially since the answer provided includes the team names.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the teams that Tom Landry played for by using the appropriate property (wdt:P54) and the correct entity (wd:Q1374361). The query returns the IRIs of the teams as required, and the answer accurately reflects the query results. 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:Q1028 wdt:P38 ?currency .
  OPTIONAL {
    ?currency rdfs:label ?currencyLabel .
    FILTER ( LANG( ?currencyLabel ) = "en" )
  }
}

The currency you should take to Morocco is the Moroccan dirham (wd:Q200192).

[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 http://amur:7001

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]
Let's break down the question:

1. The user wants to know what currency is used in Morocco.
2. We need to identify the entity for Morocco and the property for "currency".

Step 1: Find the entity for Morocco.
I'll search for "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 correct entity for Morocco as a country is wd:Q1028.

Step 2: Find the property for "currency" used by a country.
I'll search for the property "currency" in Wikidata.

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): identifier for a currency per ISO 4217
3. price, also known as cost, exchange rate, list price, MSRP, published price (wd:P2284 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): amount in a specific currency
5. cash (wd:P2232 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): the value of cash and securities held by a state government
6. currency symbol description (wd:P489 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): qualifier to define a property constraint in combination with "property constraint" (P2302)
10. numeric value, also known as numerical value, value (wd:P1181 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): numerical value of a number, a mathematical constant, or a physical constant

[Assistant]
The property for "currency" used by a country is wd:P38.

Step 3: Construct a SPARQL query to find the currency used by Morocco (wd:Q1028) using the property "currency" (wdt:P38). I will also try to get the label of the currency for clarity, but will put it in an OPTIONAL clause.

Here's the query I will use:
```
SELECT ?currency ?currencyLabel WHERE {
  wd:Q1028 wdt:P38 ?currency .
  OPTIONAL { ?currency rdfs:label ?currencyLabel . FILTER(LANG(?currencyLabel) = "en") }
}
```
Now, let's execute this query to confirm the result.

[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 answer is correct and complete. The SPARQL query retrieves the currency used in Morocco (wd:Q1028) via the property 'currency' (wd:P38), and also optionally retrieves the English label for the currency. The result correctly identifies the Moroccan dirham (wd:Q200192) as the currency to take to Morocco. All rules for SPARQL queries are followed, and the answer is accurate and relevant to the question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?language WHERE {
  wd:Q148 wdt:P37 ?language
}

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

Wikidata lists the following official languages for China: Standard Chinese (Mandarin) (wd:Q727694), Chinese (wd:Q7850), and languages of China (wd:Q835866). However, Wikidata does not explicitly distinguish which is the 'primary' language. In practice, Standard Chinese (Mandarin) is universally recognized as the main language used in government, education, and media in China.

[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 http://amur:7001

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]
Let's break down the question:

1. The user is asking for the primary language of China.
2. I need to identify the entity for "China" and the property for "primary language" or "official language".

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 most relevant entity for "China" as a country is "People's Republic of China" (wd:Q148).

Next, I need to find the property for "primary language" or "official language" for a country. I will search for properties related to "official language".

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language status identifier by Ethnologue.com using EGIDS scale
4. language regulatory body, also known as language authority, regulatory body (wd:P1018 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language in which the writer has written their work, languages spoken, written or signed

[Assistant]
The property "official language" (wdt:P37) is the most relevant for finding the primary language of a country.

Now, I will construct a SPARQL query to find the official language(s) of the People's Republic of China (wd:Q148) using the property wdt:P37. I will also try to get the label of the language for clarity.

[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 returns three entities as official languages for China: "Standard Chinese" (wd:Q727694), "Chinese" (wd:Q7850), and "languages of China" (wd:Q835866). Among these, "Standard Chinese" (also known as Mandarin) is the primary official language.

Here is the final SPARQL query and answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query retrieves all values for the official language (P37) of China (wd:Q148), which is correct. However, the answer only mentions Standard Chinese (Mandarin), while the query result also includes 'Chinese' (wd:Q7850) and 'languages of China' (wd:Q835866). The answer should clarify why Standard Chinese is considered the primary language, or at least mention all official languages returned by the query for completeness. Additionally, if the user's intent is specifically the 'primary' language, some justification or filtering for the main official language (Standard Chinese) should be provided, possibly by checking for the main language used in government or education. The current answer is sensible but needs refinement for completeness and clarity.

[Assistant]
Thank you for the feedback. Here’s how I’ll refine the approach:

1. The SPARQL query correctly retrieves all official languages of China (wd:Q148) via wdt:P37, returning Standard Chinese (Mandarin), Chinese, and languages of China.
2. The user asked for the "primary" language, which is not always directly encoded in Wikidata, but Standard Chinese (Mandarin) is widely recognized as the main official language used in government, education, and media.
3. For completeness, I should mention all official languages returned, and clarify why Standard Chinese is considered the primary one.
4. I will also check if there is a property or qualifier that distinguishes the "main" or "primary" official language, such as "main language" or "language used in government".

First, I will search for properties related to "main language" or "language used in government" to see if I can filter for the primary language.

[Tool]
Top 10 property alternatives:
1. 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
2. programmed in, also known as language, programming language, written in (wd:P277 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): the programming language(s) in which the software is developed
3. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language(s) that a person or a people speaks, writes or signs, including the native language(s)
4. main subject, also known as primary topic, primary subject, primary keyword, plot keyword, of (wd:P921 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): primary topic of a work (see also P180: depicts), depicts
5. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): notable scientific, artistic or literary work, or other work of significance among subject's works
6. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): main Wikimedia category
7. facet of, also known as subitem of, topic of, subtopic of, subject in, section in (wd:P1269 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): topic of which this item is an aspect; item that offers a broader perspective on the same topic
8. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language or languages a person has learned from early childhood, languages spoken, written or signed
9. foundational text, also known as main text, treaty, organic law, founding document, establishing document (wd:P457 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): text through which an institution or object has been created or established
10. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language widely used (spoken or written) in this place or at this event or organisation

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language designated as official by this item, language used
2. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language widely used (spoken or written) in this place or at this event or organisation
3. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language(s) that a person or a people speaks, writes or signs, including the native language(s)
4. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): label for the items in their official language  or their original language, name
5. language style, also known as manner, term register, obsolete, register, sense register (wd:P6191 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): to denote of the way a sense of a word is used, e.g., slang, vulgarism, babytalk, colloquialism, etc.
6. 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
7. language regulatory body, also known as language authority, regulatory body (wd:P1018 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): regulatory body of a language
8. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language in which the writer has written their work, languages spoken, written or signed
9. basic form of government, also known as form of government, government, type of government (wd:P122 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): subject's government
10. programmed in, also known as language, programming language, written in (wd:P277 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): the programming language(s) in which the software is developed

[Tool]
Got 279 rows and 2 columns, showing the first 5 and last 5 rows below:
| language                            | languageLabel              |
| ----------------------------------- | -------------------------- |
| Wutun (wd:Q1012917)                 | Wutun (en)                 |
| Sani (wd:Q1055287)                  | Sani (en)                  |
| Chinese Sign Language (wd:Q1094190) | Chinese Sign Language (en) |
| Ache Yi (wd:Q10949828)              | Ache Yi (en)               |
| A-Hmao (wd:Q1108934)                | A-Hmao (en)                |
| ...                                 | ...                        |
| Kazakh (wd:Q9252)                   | Kazakh (en)                |
| Kyrgyz (wd:Q9255)                   | Kyrgyz (en)                |
| Chadong (wd:Q926742)                | Chadong (en)               |
| Hlai (wd:Q934738)                   | Hlai (en)                  |
| U (wd:Q953082)                      | U (en)                     |

[Assistant]
The property "language used" (wdt:P2936) returns a large number of languages spoken or used in China, reflecting the country's linguistic diversity. However, this does not help us filter for the "primary" or main official language, as it includes many minority and regional languages.

Given this, the most authoritative property for the official language remains wdt:P37, which returns:
- Standard Chinese (wd:Q727694)
- Chinese (wd:Q7850)
- languages of China (wd:Q835866)

Among these, Standard Chinese (Mandarin) is universally recognized as the main language used in government, education, and media in China. The broader "Chinese" and "languages of China" refer to the language family and the set of all languages spoken in China, respectively.

I will now provide a refined answer, listing all official languages returned by the query, and explaining why Standard Chinese is considered the primary language. Here is the improved SPARQL query and answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the official languages of China using the appropriate property (wdt:P37). However, the question specifically asks for the 'primary language' of China, not all official languages. While the answer text does clarify that Standard Chinese (Mandarin) is the primary language, the SPARQL query itself does not distinguish between primary and other official languages. If possible, the query should be refined to prioritize or filter for the main official language (Standard Chinese/Mandarin), perhaps by checking for additional qualifiers or by providing a ranked or filtered result. If such a distinction cannot be made in Wikidata, the answer should clearly state this limitation.

[Assistant]
Thank you for the feedback. Here’s how I’ll proceed:

1. The property wdt:P37 (official language) returns multiple values, but does not distinguish which is the "primary" language.
2. The user specifically asks for the "primary language." Ideally, I would look for qualifiers or properties that indicate "main," "primary," or "most widely used" official language.
3. Previous searches for properties like "main language" or "language used in government" did not yield a property that directly marks Standard Chinese as the primary language for China.
4. Therefore, I will check if the statement for Standard Chinese as an official language of China has any qualifiers (such as "applies to jurisdiction," "ranking," or "official status") that could help identify it as the primary language.

I will list the full statement for China (wd:Q148) and official language (P37) to check for qualifiers.

[Tool]
Got 3 rows and 3 columns:
| subject                              | property                  | object                                      |
| ------------------------------------ | ------------------------- | ------------------------------------------- |
| People's Republic of China (wd:Q148) | official language (p:P37) | s:Q148-86ac73c7-4e1b-2436-3987-7a7d136cfeb9 |
| People's Republic of China (wd:Q148) | official language (p:P37) | s:q148-9F63023A-7B2E-4855-B1C7-E66B28F479E7 |
| People's Republic of China (wd:Q148) | official language (p:P37) | s:Q148-c8dd7d2b-4d21-6a6e-e92d-c52c6f6d7f45 |

[Assistant] There are three statement nodes for the official language of China. To check for qualifiers that might indicate "primary" or "main" status, I will list the properties and values for one of these statement nodes, starting with s:Q148-86ac73c7-4e1b-2436-3987-7a7d136cfeb9.

[Tool]
Got 5 rows and 3 columns:
| subject                                     | property                   | object                                       |
| ------------------------------------------- | -------------------------- | -------------------------------------------- |
| s:Q148-86ac73c7-4e1b-2436-3987-7a7d136cfeb9 | official language (ps:P37) | Chinese (wd:Q7850)                           |
| s:Q148-86ac73c7-4e1b-2436-3987-7a7d136cfeb9 | wikibase:rank              | wikibase:NormalRank                          |
| s:Q148-86ac73c7-4e1b-2436-3987-7a7d136cfeb9 | rdf:type                   | wikibase:BestRank                            |
| s:Q148-86ac73c7-4e1b-2436-3987-7a7d136cfeb9 | prov:wasDerivedFrom        | ref:e169dd96d3aefd5e6055e3cb12639c63bd3160db |
| s:Q148-86ac73c7-4e1b-2436-3987-7a7d136cfeb9 | rdf:type                   | wikibase:Statement                           |

[Tool]
Got 4 rows and 3 columns:
| subject                                     | property                   | object                        |
| ------------------------------------------- | -------------------------- | ----------------------------- |
| s:q148-9F63023A-7B2E-4855-B1C7-E66B28F479E7 | official language (ps:P37) | Standard Chinese (wd:Q727694) |
| s:q148-9F63023A-7B2E-4855-B1C7-E66B28F479E7 | wikibase:rank              | wikibase:NormalRank           |
| s:q148-9F63023A-7B2E-4855-B1C7-E66B28F479E7 | rdf:type                   | wikibase:BestRank             |
| s:q148-9F63023A-7B2E-4855-B1C7-E66B28F479E7 | rdf:type                   | wikibase:Statement            |

[Tool]
Got 5 rows and 3 columns:
| subject                                     | property                   | object                                       |
| ------------------------------------------- | -------------------------- | -------------------------------------------- |
| s:Q148-c8dd7d2b-4d21-6a6e-e92d-c52c6f6d7f45 | official language (ps:P37) | languages of China (wd:Q835866)              |
| s:Q148-c8dd7d2b-4d21-6a6e-e92d-c52c6f6d7f45 | wikibase:rank              | wikibase:NormalRank                          |
| s:Q148-c8dd7d2b-4d21-6a6e-e92d-c52c6f6d7f45 | rdf:type                   | wikibase:BestRank                            |
| s:Q148-c8dd7d2b-4d21-6a6e-e92d-c52c6f6d7f45 | prov:wasDerivedFrom        | ref:ca531df3baa8592e7de5c2a1c4cd4ebbf2311b2c |
| s:Q148-c8dd7d2b-4d21-6a6e-e92d-c52c6f6d7f45 | rdf:type                   | wikibase:Statement                           |

[Assistant]
None of the statement nodes for official language (P37) of China have qualifiers indicating "primary" or "main" status. All are of normal/best rank, and there is no further distinction.

Therefore, it is not possible to distinguish the "primary" language of China using only qualifiers or ranks in Wikidata. The answer must clarify this limitation, and explain that Standard Chinese (Mandarin) is universally recognized as the primary language in practice.

I will now provide a final answer and SPARQL query, explicitly stating this limitation.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?owner WHERE {
  wd:Q156578 wdt:P127 ?owner
}

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

Volkswagen Group (the parent company of Volkswagen car company) is owned by 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 http://amur:7001

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]
Let's break down the question:

1. The main entity is "Volkswagen car company." I need to identify the correct Wikidata entity for Volkswagen.
2. The property of interest is "owns" or "ownership." I need to find the property that links a company to its owner(s).
3. I will then construct a SPARQL query to find the owner(s) of Volkswagen.

First, I will search for the entity "Volkswagen" 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:
- Volkswagen (wd:Q246): the automotive brand and manufacturing subsidiary.
- Volkswagen Group (wd:Q156578): the parent conglomerate.

Since the question asks about the "Volkswagen car company," it could refer to either the brand (wd:Q246) or the group (wd:Q156578). However, ownership is typically about the parent company, so I will focus on "Volkswagen Group" (wd:Q156578).

Next, I need to find the property that indicates ownership of a company. I will search for properties related to "owner."

[Tool]
Top 10 property alternatives:
1. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): owner of the subject
2. owner of, also known as owns, owns property, shareholder of (wd:P1830 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): entities owned by the subject
3. has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): main Wikidata property for this item
8. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): 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 psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): person or organisation that holds or was granted a lease on the subject, occupant

[Assistant]
The most relevant property for ownership is "owned by" (wdt:P127), which indicates the owner of the subject.

Now, I will construct a SPARQL query to find the owner(s) of Volkswagen Group (wd:Q156578) using the "owned by" property (wdt:P127). I will also try to retrieve optional labels for the owners.

[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 Volkswagen Group (wd:Q156578) using the 'owned by' property (wdt:P127), and the answer lists the actual IRIs of the owners as required. The answer is accurate and complete for 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: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)       |

Iván "Pudge" Rodríguez has played for the following teams: New York Yankees (wd:Q213417), Texas Rangers (wd:Q329816), Detroit Tigers (wd:Q650855), Washington Nationals (wd:Q825838), and Houston Astros (wd:Q848117).

[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 http://amur:7001

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]
Let's break down the question:

1. The user is asking about "Pudge Rodriguez," which is the nickname of Iván Rodríguez, a famous baseball player.
2. The question is about the teams he has played for.

Step 1: Find the entity for "Pudge Rodriguez" (Iván Rodríguez) in Wikidata.

I'll search for "Pudge Rodriguez" first.

[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 correct entity for "Pudge Rodriguez" is Iván Rodríguez (wd:Q706908), the Puerto Rican Hall of Fame baseball player.

Next, I need to find the property that links a baseball player to the teams they have played for. I'll search for properties related to "team" or "played for."

[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 the correct one to use for finding the teams Iván Rodríguez (Pudge Rodriguez) has played for.

Now, I will construct a SPARQL query to find all teams (with their IRIs and optionally their labels) that Iván Rodríguez has been a member of.

[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 teams that Iván "Pudge" Rodríguez has played for by using the appropriate entity (wd:Q706908) and property (wdt:P54). The query returns the IRIs of the teams as required, and the answer matches the execution result. No further refinement is necessary.