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 ?coach ?coachLabel WHERE {
  {
    ?coach wdt:P6087 wd:Q330120
  } UNION {
    wd:Q330120 wdt:P286 ?coach
  }
  OPTIONAL {
    ?coach rdfs:label ?coachLabel FILTER ( LANG( ?coachLabel ) = 'en' )
  }
}

This query retrieves all individuals who have coached the Carolina Panthers (including head and interim coaches, if present in Wikidata), returning their IRIs and English labels only.

[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 coached the carolina panthers?

[Assistant]
Let's break down the question:

1. The user wants to know which people have coached the Carolina Panthers.
2. We need to identify:
   - The entity for "Carolina Panthers".
   - The property for "coach" or "head coach".

Step 1: Search for the entity "Carolina Panthers".

[Tool]
Top 10 entity alternatives:
1. Carolina Panthers (wd:Q330120): American football team
2. history of the Carolina Panthers, also known as Carolina Panthers history, the Carolina Panthers history (wd:Q5869201): aspect of history
3. Carolina Panthers Cheerleaders (wd:Q130385213): cheerleading squad of the Carolina Panthers
4. 2021 Carolina Panthers season (wd:Q104869609): 27th season in franchise history
5. 2022 Carolina Panthers season (wd:Q110445399): 28th season in franchise history
6. 2020 Carolina Panthers season (wd:Q80995958): 26th season in franchise history
7. 2018 Carolina Panthers season (wd:Q48843395): 24th season in franchise history
8. 2015 Carolina Panthers season (wd:Q18701993): NFL team 21st season(lost Super Bowl)
9. 2019 Carolina Panthers season (wd:Q60525825): 25th season in franchise history
10. 2023 Carolina Panthers season (wd:Q116170055): 29th season in franchise history

[Assistant]
The main entity for the Carolina Panthers is wd:Q330120 (Carolina Panthers, American football team).

Next, I need to find the appropriate property for "coach" or "head coach" to identify people who have coached this team. I will search for properties related to "coach".

[Tool]
Top 10 property alternatives:
1. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person
2. coach of sports team, also known as trainer of sports team, club manager of sports team, trainer of, team manager of sports team, team manager of (wd:P6087 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): sports club or team for which this person is or was on-field manager or coach
3. PlaymakerStats.com coach ID, also known as PlaymakerStats.com manager ID, TheFinalBall coach ID (wd:P6316 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): identifier for an association football (soccer) coach at PlaymakerStats.com (formerly TheFinalBall.com)
4. LNB Coach id, also known as LNB Pro A coach ID (wd:P6743 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): identifier for a coach in the French basketball championship
5. trained by, also known as personal trainer, trainer (wd:P10449 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): personal trainer of the athlete, student of
6. LevskiSofia.info coach ID (wd:P6410 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): identifier for a coach at the LevskiSofia.info
7. TuttoCalciatori.net coach ID (wd:P7035 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): identifier of a football coach in the website TuttoCalciatori.net
8. Soccerdonna coach ID, also known as Soccerdonna trainer ID (wd:P8134 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): identifier for a coach at the Soccerdonna
9. LegaBasket.it coach ID (wd:P5612 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): identifier for a coach at legabasket.it
10. VBL people ID, also known as VBL coach ID, VBL player ID, VBL staff ID (wd:P4298 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): identifier for a volleyball player on the website of the German Volleyball Federation

[Assistant]
The most relevant properties are:
- head coach (wd:P286): on-field manager or head coach of a sports club
- coach of sports team (wd:P6087): sports club or team for which this person is or was on-field manager or coach

Since we want to find people who have coached the Carolina Panthers, we should check both:
- People who have been head coach of the Carolina Panthers (using wdt:P286)
- People who have been coach of the Carolina Panthers (using wdt:P6087)

I will first check which of these properties is actually used for the Carolina Panthers entity. I will list triples with the Carolina Panthers as object for both properties.

[Tool]
Got 1 row and 3 columns:
| subject                  | property                         | object                         |
| ------------------------ | -------------------------------- | ------------------------------ |
| Ron Rivera (wd:Q1991889) | coach of sports team (wdt:P6087) | Carolina Panthers (wd:Q330120) |

[Tool] Got no rows and 3 columns

[Assistant]
Only the property "coach of sports team" (wdt:P6087) is used with the Carolina Panthers as the object, and it currently returns Ron Rivera (wd:Q1991889) as a coach.

To ensure completeness, I will check if there are other people who have coached the Carolina Panthers by searching for all subjects with wdt:P6087 pointing to wd:Q330120.

[Tool]
Got 1 row and 1 column:
| coach                    |
| ------------------------ |
| Ron Rivera (wd:Q1991889) |

[Assistant]
Based on the data in Wikidata, the only person listed as having coached the Carolina Panthers (using the "coach of sports team" property) is Ron Rivera (wd:Q1991889).

Here is the SPARQL query that returns the identifiers of people who have coached the Carolina Panthers:

```sparql
SELECT ?coach WHERE {
  ?coach wdt:P6087 wd:Q330120
}
```

Final answer: Ron Rivera is the only person listed as having coached the Carolina Panthers in Wikidata.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query only returns Ron Rivera as a coach of the Carolina Panthers, but it is likely that there have been multiple coaches throughout the team's history. The query should be refined to ensure it retrieves all individuals who have coached the Carolina Panthers, not just one. Additionally, the query should return the IRIs of the coaches and may optionally include their labels using OPTIONAL { ?coach rdfs:label ?coachLabel }. Please check if there are other coaches in Wikidata and ensure the query retrieves all of them.

[Assistant]
Thank you for the feedback. You are correct: the Carolina Panthers have had multiple coaches throughout their history, and the query should retrieve all of them.

My previous approach only checked for the "coach of sports team" property (wdt:P6087) pointing to the Carolina Panthers. However, there may be other relevant properties or qualifiers, such as "head coach" (wdt:P286) or statements where the Carolina Panthers are the subject and a coach is the object.

To be thorough, I will:
1. Check if the Carolina Panthers entity (wd:Q330120) has statements for "head coach" (wdt:P286).
2. Check if there are statements using the generic "coach" property (wdt:P286) in either direction.
3. Check for qualifiers on "member of sports team" or "position held" that might indicate a coaching role.
4. Ensure the query retrieves all relevant coaches and includes their IRIs and optionally their labels.

First, I will list all properties used with the Carolina Panthers as the subject to see if there are any coaching-related properties.

[Tool]
Got 259 rows and 3 columns, showing the first 10 rows below:
| subject                        | property                           | object                                |
| ------------------------------ | ---------------------------------- | ------------------------------------- |
| Carolina Panthers (wd:Q330120) | instance of (wdt:P31)              | American football team (wd:Q17156793) |
| Carolina Panthers (wd:Q330120) | country (wdt:P17)                  | United States (wd:Q30)                |
| Carolina Panthers (wd:Q330120) | Commons category (wdt:P373)        | Carolina Panthers                     |
| Carolina Panthers (wd:Q330120) | part of (wdt:P361)                 | NFC South (wd:Q934745)                |
| Carolina Panthers (wd:Q330120) | inception (wdt:P571)               | 1993-10-26T00:00:00Z (xsd:dateTime)   |
| Carolina Panthers (wd:Q330120) | sport (wdt:P641)                   | American football (wd:Q41323)         |
| Carolina Panthers (wd:Q330120) | official website (wdt:P856)        | <http://www.panthers.com>             |
| Carolina Panthers (wd:Q330120) | owned by (wdt:P127)                | David Tepper (wd:Q459538)             |
| Carolina Panthers (wd:Q330120) | topic's main category (wdt:P910)   | wd:Q9091794                           |
| Carolina Panthers (wd:Q330120) | social media followers (wdt:P8687) | 3087165 (xsd:decimal)                 |
| ...                            | ...                                | ...                                   |

[Tool]
Got 1 row and 3 columns:
| subject                        | property              | object                      |
| ------------------------------ | --------------------- | --------------------------- |
| Carolina Panthers (wd:Q330120) | head coach (wdt:P286) | Dave Canales (wd:Q47456134) |

[Tool] Got no rows and 3 columns

[Tool]
Got 1 row and 3 columns:
| subject                  | property                         | object                         |
| ------------------------ | -------------------------------- | ------------------------------ |
| Ron Rivera (wd:Q1991889) | coach of sports team (wdt:P6087) | Carolina Panthers (wd:Q330120) |

[Tool]
Got 56,436 rows and 3 columns, showing the first 10 rows below:
| subject                                      | property              | object                        |
| -------------------------------------------- | --------------------- | ----------------------------- |
| Tohid Asadian Kojabadi (wd:Q113799385)       | head coach (wdt:P286) | Iran (wd:Q794)                |
| Tagir Abdulaev (wd:Q21635228)                | head coach (wdt:P286) | Vladimir Putin (wd:Q7747)     |
| Lionel Messi (wd:Q615)                       | head coach (wdt:P286) | Jordi Roura Solà (wd:Q106136) |
| Roger Federer (wd:Q1426)                     | head coach (wdt:P286) | José Higueras (wd:Q1348847)   |
| Rafael Nadal (wd:Q10132)                     | head coach (wdt:P286) | Carlos Moyá (wd:Q193361)      |
| Novak Djokovic (wd:Q5812)                    | head coach (wdt:P286) | Marián Vajda (wd:Q1291378)    |
| Real Madrid CF (wd:Q8682)                    | head coach (wdt:P286) | Carlo Ancelotti (wd:Q174614)  |
| FC Barcelona (wd:Q7156)                      | head coach (wdt:P286) | Hansi Flick (wd:Q577384)      |
| Manchester United F.C. (wd:Q18656)           | head coach (wdt:P286) | Ruben Amorim (wd:Q368682)     |
| 2019–20 Real Madrid CF season (wd:Q63036025) | head coach (wdt:P286) | Zinedine Zidane (wd:Q1835)    |
| ...                                          | ...                   | ...                           |

[Tool]
Got 16,603 rows and 3 columns, showing the first 10 rows below:
| subject                            | property                         | object                             |
| ---------------------------------- | -------------------------------- | ---------------------------------- |
| Heimir Hallgrímsson (wd:Q15229580) | coach of sports team (wdt:P6087) | Jamaica (wd:Q766)                  |
| Diego Maradona (wd:Q17515)         | coach of sports team (wdt:P6087) | Dorados de Sinaloa (wd:Q1243720)   |
| Guus Hiddink (wd:Q484534)          | coach of sports team (wdt:P6087) | Valencia (wd:Q8818)                |
| Kirk Kilgour (wd:Q3815595)         | coach of sports team (wdt:P6087) | volleyball (wd:Q1734)              |
| Toni Nadal (wd:Q2118577)           | coach of sports team (wdt:P6087) | Rafael Nadal (wd:Q10132)           |
| Riccardo Piatti (wd:Q23039404)     | coach of sports team (wdt:P6087) | Novak Djokovic (wd:Q5812)          |
| David Aznar (wd:Q107355705)        | coach of sports team (wdt:P6087) | Real Madrid CF (wd:Q8682)          |
| Jordi Roura Solà (wd:Q106136)      | coach of sports team (wdt:P6087) | FC Barcelona (wd:Q7156)            |
| Ryan Giggs (wd:Q10524)             | coach of sports team (wdt:P6087) | Manchester United F.C. (wd:Q18656) |
| Arne Slot (wd:Q1029223)            | coach of sports team (wdt:P6087) | Liverpool F.C. (wd:Q1130849)       |
| ...                                | ...                              | ...                                |

[Tool]
Got 1 row and 1 column:
| coach                    |
| ------------------------ |
| Ron Rivera (wd:Q1991889) |

[Tool]
Got 1 row and 1 column:
| coach                       |
| --------------------------- |
| Dave Canales (wd:Q47456134) |

[Tool]
Got 2 rows and 1 column:
| coach                       |
| --------------------------- |
| Ron Rivera (wd:Q1991889)    |
| Dave Canales (wd:Q47456134) |

[Tool]
Got 44 rows and 2 columns, showing the first 5 and last 5 rows below:
| coach                       | coachLabel        |
| --------------------------- | ----------------- |
| Ron Rivera (wd:Q1991889)    | Ron Rivera (ace)  |
| Ron Rivera (wd:Q1991889)    | Ron Rivera (ast)  |
| Ron Rivera (wd:Q1991889)    | Ron Rivera (bjn)  |
| Ron Rivera (wd:Q1991889)    | Ron Rivera (bug)  |
| Ron Rivera (wd:Q1991889)    | Ron Rivera (ca)   |
| ...                         | ...               |
| Dave Canales (wd:Q47456134) | Dave Canales (ga) |
| Dave Canales (wd:Q47456134) | Dave Canales (it) |
| Dave Canales (wd:Q47456134) | Dave Canales (nl) |
| Dave Canales (wd:Q47456134) | Dave Canales (sq) |
| Dave Canales (wd:Q47456134) | Dave Canales (sv) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query is mostly correct in terms of retrieving coaches of the Carolina Panthers using both directions of the coaching relationship (P6087 and P286). However, the query currently returns multiple rows for each coach due to retrieving all available rdfs:label values in different languages. To improve the output, the query should use a language filter (e.g., FILTER(LANG(?coachLabel) = 'en')) to return only English labels, or group by coach to avoid duplicate rows. Additionally, ensure that all relevant coaching roles (e.g., interim coaches, assistant coaches if relevant) are considered if the question scope includes them.

[Assistant]
Thank you for the feedback. To address the issues:

1. The query currently returns multiple rows per coach due to multiple rdfs:label values in different languages. I will add a FILTER to only include English labels (FILTER(LANG(?coachLabel) = 'en')).
2. Regarding scope: The original question asks "who has coached," which typically refers to head coaches and interim head coaches, but not assistant coaches unless specified. The properties P286 (head coach) and P6087 (coach of sports team) are the most relevant for head and interim coaches. If there are other properties or qualifiers for interim coaches, I will check for them.
3. I will ensure the query is concise and returns only unique coaches with their English label.

First, I will check if there are any properties or qualifiers for "interim coach" or similar roles.

[Tool]
Top 10 property alternatives:
1. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person
2. coach of sports team, also known as trainer of sports team, club manager of sports team, trainer of, team manager of sports team, team manager of (wd:P6087 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): sports club or team for which this person is or was on-field manager or coach
3. backup or reserve team or crew, also known as backup crew, backup team, reserve crew, reserve team (wd:P3015 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): team or crew that is kept ready to act as reserve
4. represented by, also known as agent, managed by, manager, managing agent, rep (wd:P1875 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): person or agency that represents or manages the subject
5. director / manager, also known as leader, manager, manager/director, managing director, Officer-in-Charge (wd:P1037 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): person who manages any kind of group, significant person
6. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): person, profession, organization or entity that operates the equipment, facility, or service, used by
7. 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
8. position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): persons who hold and/or held the position
9. UEFA coach ID (archived), also known as UEFA manager ID (archived) (wd:P7360 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): identifier for a coach at the UEFA
10. appointed by, also known as named by (wd:P748 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): who appointed the person to the office, can be used as a qualifier

[Assistant]
There is no specific property for "interim coach" in the top results, and the main properties for coaching roles are still P286 (head coach) and P6087 (coach of sports team). Interim coaches are often listed under these properties, sometimes with qualifiers, but Wikidata's structure may not always distinguish interim from permanent head coaches.

I will now refine the query to:
- Use both P286 and P6087 for the Carolina Panthers.
- Retrieve only English labels for coaches.
- Return unique coaches.

Here is the improved SPARQL query:

[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 DISTINCT ?language ?languageLabel WHERE {
  {
    wd:Q794 wdt:P37 ?language .
  } UNION {
    wd:Q794 wdt:P2936 ?language .
  }
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( lang( ?languageLabel ) = "en" )
  }
}

Got 68 rows and 2 columns, showing the first 5 and last 5 rows below:
| language                        | languageLabel         |
| ------------------------------- | --------------------- |
| Southern Balochi (wd:Q12634001) | Southern Balochi (en) |
| Western Balochi (wd:Q12645561)  | Western Balochi (en)  |
| Eshtehardi (wd:Q12952418)       | Eshtehardi (en)       |
| Southern Luri (wd:Q12952748)    | Southern Luri (en)    |
| Rudbari (wd:Q12953072)          | Rudbari (en)          |
| ...                             | ...                   |
| Soi (wd:Q7930463)               | Soi (en)              |
| Armenian (wd:Q8785)             | Armenian (en)         |
| Persian (wd:Q9168)              | Persian (en)          |
| Turkmen (wd:Q9267)              | Turkmen (en)          |
| Azerbaijani (wd:Q9292)          | Azerbaijani (en)      |

In Iran, many languages are spoken. The official language is Persian (wd:Q9168), but other languages spoken in Iran include Azerbaijani (wd:Q9292), Kurdish (wd:Q36206), Armenian (wd:Q8785), Turkmen (wd:Q9267), Southern Balochi (wd:Q12634001), Western Balochi (wd:Q12645561), Eshtehardi (wd:Q12952418), Southern Luri (wd:Q12952748), Rudbari (wd:Q12953072), Soi (wd:Q7930463), and many more. The full list can be retrieved from the query.

[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 kind of language do they speak in iran?

[Assistant]
Let's break down the question:

1. The user is asking about the language(s) spoken in Iran.
2. We need to identify the entity for Iran and the property that relates a country to its language(s).

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

[Tool]
Top 10 entity alternatives:
1. Iran, also known as ir, IRI, IRN, Islamic Rep. Iran, Islamic Republic of Iran (wd:Q794): country in Western Asia
2. Qajar Iran, also known as Guarded Domains of Persia, Sublime State of Persia, Qajar Persia, Persia, Iran (wd:Q63158027): country in Western Asia (1789–1925)
3. Iran (wd:Q2043606): village in North Ossetia, Russia
4. Iran, also known as Īrān (wd:Q10859757): Iranian newspaper
5. IRAN, also known as Iran: Journal of the British Institute of Persian Studies (wd:Q5973372): academic journal
6. Irane Man, also known as Iran (wd:Q100939484): 2018 studio by Homayoun Shajarian & Sohrab Pournazeri
7. IRAN (wd:Q108434787): herbarium
8. Iran, also known as Iran (first name), Iran (given name) (wd:Q21286079): male given name
9. Iran, also known as IMO 5327817 (wd:Q101778560): ship built in 1941
10. Iran (wd:Q96382820): About Iran

[Assistant]
The most relevant entity for the country Iran is wd:Q794.

Next, I need to find the property that links a country to its spoken language(s). Commonly, this is "official language" or "language spoken".

I'll search for properties related to "language" for the entity wd:Q794 (Iran).

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as p/wdt): language designated as official by this item, language used
2. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as p/wdt): language widely used (spoken or written) in this place or at this event or organisation
3. 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)
4. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
5. culture, also known as archaeological culture, civilisation, civilization (wd:P2596 as p/wdt): human culture or people (or several cultures) associated with this item, part of
6. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as p/wdt): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
7. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
9. Libraries Australia ID, also known as CNLKIN, NLA Kinetica Service identifier, NLA (Australia) identifier, NLA (Australia) ID, Libraries Australia identifier (wd:P409 as p/wdt): identifier issued by the National Library of Australia (see also...F component. Format: 1-12 digits, removing leading zero-padding.
10. Unicode character, also known as emoji, emote, pictograph, Unicode symbol (wd:P487 as p/wdt): Unicode character representing the item (only if this is not a c...acter or a compatiblity character: in that case, use only P4213)

No other items found

[Assistant]
The most relevant properties are:
- official language (wdt:P37)
- language used (wdt:P2936)

For a country, "official language" is usually the most direct answer to "what kind of language do they speak". However, "language used" could include minority and regional languages.

I'll start by querying the official language(s) of Iran (wd:Q794) using wdt:P37, and also include optional labels for human readability.

[Tool]
Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| Persian (wd:Q9168) | Persian (en)  |

[Assistant]
The official language spoken in Iran is Persian.

Here is the SPARQL query that finds this information:

SELECT ?language ?languageLabel WHERE { wd:Q794 wdt:P37 ?language . OPTIONAL { ?language rdfs:label ?languageLabel FILTER (lang(?languageLabel) = "en") } }

Answer: The official language of Iran is Persian (wd:Q9168).

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the official language of Iran (Persian) using property P37. However, the user's question asks about the kind of language spoken in Iran, which could imply not only the official language but also other languages spoken in the country. To provide a more comprehensive answer, the query should also consider other properties such as 'languages spoken or written' (P2936) or 'language used' (P407) to list all significant languages spoken in Iran, not just the official one. Please refine the query to include all languages spoken in Iran, not only the official language.

[Assistant]
Thank you for the feedback. You are correct: the user's question could refer to all languages spoken in Iran, not just the official one. Based on the previous property search, "language used" (wdt:P2936) is relevant for capturing all languages spoken or written in Iran.

To provide a comprehensive answer, I will refine the query to include both the official language (wdt:P37) and all languages used (wdt:P2936) in Iran. I will use a UNION to combine results from both properties and ensure that all unique languages are included. I will also include optional English labels for readability.

Let's construct and execute this refined query.

[Tool]
Got 68 rows and 2 columns, showing the first 5 and last 5 rows below:
| language                        | languageLabel         |
| ------------------------------- | --------------------- |
| Southern Balochi (wd:Q12634001) | Southern Balochi (en) |
| Western Balochi (wd:Q12645561)  | Western Balochi (en)  |
| Eshtehardi (wd:Q12952418)       | Eshtehardi (en)       |
| Southern Luri (wd:Q12952748)    | Southern Luri (en)    |
| Rudbari (wd:Q12953072)          | Rudbari (en)          |
| ...                             | ...                   |
| Soi (wd:Q7930463)               | Soi (en)              |
| Armenian (wd:Q8785)             | Armenian (en)         |
| Persian (wd:Q9168)              | Persian (en)          |
| Turkmen (wd:Q9267)              | Turkmen (en)          |
| Azerbaijani (wd:Q9292)          | Azerbaijani (en)      |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves both the official language (Persian) and other widely spoken languages in Iran using the appropriate properties (P37 for official language and P2936 for languages used). The query returns the IRIs of the languages as required, and the answer accurately summarizes the results. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?college WHERE {
  wd:Q134262 wdt:P69 ?college .
  ?college wdt:P31 / wdt:P279 * ?type .
  VALUES ?univOrCollege {
    wd:Q3918 wd:Q189004
  }
  FILTER ( ?type = ?univOrCollege )
}

Got 4 rows and 1 column:
| college                                         |
| ----------------------------------------------- |
| University of Iowa (wd:Q182973)                 |
| University of Missouri (wd:Q579968)             |
| The New School (wd:Q599316)                     |
| Washington University in St. Louis (wd:Q777403) |

Tennessee Williams attended the following colleges and universities: University of Iowa (wd:Q182973), University of Missouri (wd:Q579968), The New School (wd:Q599316), and Washington University in St. Louis (wd:Q777403).

[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] where did tennessee williams go to college?

[Assistant]
Let's break down the question:

1. The entity is "Tennessee Williams".
2. The property is "educated at" or "college attended".

First, I will search for the entity "Tennessee Williams" in Wikidata to get the correct identifier.

[Tool]
Top 10 entity alternatives:
1. Tennessee Williams, also known as Thomas Lanier Williams III, Thomas Williams (wd:Q134262): American playwright (1911–1983), screenwriter, playwright, novelist, writer, poet
2. Tennessee Williams (wd:Q55896325)
3. Tennessee Williams (wd:Q47513341): painting by Buffie Johnson
4. Tennessee Williams (wd:Q47510960): painting by Bernard Safran
5. Tennessee Williams (wd:Q33979787): scientific article
6. Williamsport, also known as Williamsport, Tennessee, Williamsport, TN (wd:Q8021260): unincorporated community in Maury County, Tennessee
7. allée Tennessee Williams (wd:Q111588984): alley in Thiais, France
8. Tennessee Williams Canal (wd:Q49269468): canal in St. James Parish, Louisiana, United States of America
9. NOTEBOOKS: TENNESSEE WILLIAMS (wd:Q113218921): scientific article published on 19 May 2022
10. NOTEBOOKS: TENNESSEE WILLIAMS (wd:Q113214712): scientific article published on 05 February 2022

[Assistant]
The correct entity for Tennessee Williams, the American playwright, is wd:Q134262.

Next, I need to find the property for "college attended" or "educated at". I will search for properties related to "educated at" for this entity.

[Tool]
Top 10 property alternatives:
1. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
2. student of, also known as professor, studied under, pupil of, tutor, mentor (wd:P1066 as p/wdt): person who has taught this person, significant person
3. influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as p/wdt): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”
4. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as p/wdt): specialization of a person or organization; see P106 for the occupation, interested in
5. employer, also known as working at, working for, working place, works at, works for (wd:P108 as p/wdt): person or organization for which the subject works or worked, affiliation
6. 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)
7. 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
8. 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
9. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
10. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as p/wdt): notable scientific, artistic or literary work, or other work of significance among subject's works

No other items found

[Assistant]
The property "educated at" (wdt:P69) is the correct one to use for finding where Tennessee Williams went to college.

Now, I will construct a SPARQL query to find the educational institutions attended by Tennessee Williams (wd:Q134262) using the property "educated at" (wdt:P69). I will also try to get the label of the institution for clarity.

[Tool]
Got 6 rows and 2 columns:
| college                                                | collegeLabel                                  |
| ------------------------------------------------------ | --------------------------------------------- |
| University of Iowa (wd:Q182973)                        | University of Iowa (en)                       |
| University of Missouri (wd:Q579968)                    | University of Missouri (en)                   |
| The New School (wd:Q599316)                            | The New School (en)                           |
| Soldan International Studies High School (wd:Q7557201) | Soldan International Studies High School (en) |
| Washington University in St. Louis (wd:Q777403)        | Washington University in St. Louis (en)       |
| University City High School (wd:Q7894583)              | University City High School (en)              |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves all educational institutions attended by Tennessee Williams using the 'educated at' (wdt:P69) property. However, the answer should be refined to only include colleges and universities, as the question specifically asks about where he went to college. The current result includes high schools (Soldan International Studies High School and University City High School), which should be filtered out. Please refine the SPARQL query to only include institutions that are instances of (or subclasses of) 'university' or 'college'.

[Assistant]
Thank you for the feedback. You are correct: the answer should only include colleges and universities, not high schools.

To refine the SPARQL query, I need to:
- Filter the results so that only institutions that are instances of (wdt:P31) or subclasses of (wdt:P279) 'university' (wd:Q3918) or 'college' (wd:Q189004) are included.

I will use a query pattern that checks if the institution is an instance of or subclass of university or college, either directly or indirectly.

Here is my plan:
1. For each institution attended by Tennessee Williams, check if it is an instance of (wdt:P31) or subclass of (wdt:P279) university (wd:Q3918) or college (wd:Q189004).
2. Use the property paths to include subclasses.
3. Return the IRIs and optional English labels.

Now, I will write and execute the refined SPARQL query.

[Tool]
Got 7 rows and 2 columns:
| college                                         | collegeLabel                            |
| ----------------------------------------------- | --------------------------------------- |
| University of Iowa (wd:Q182973)                 | University of Iowa (en)                 |
| University of Iowa (wd:Q182973)                 | University of Iowa (en)                 |
| University of Missouri (wd:Q579968)             | University of Missouri (en)             |
| University of Missouri (wd:Q579968)             | University of Missouri (en)             |
| The New School (wd:Q599316)                     | The New School (en)                     |
| The New School (wd:Q599316)                     | The New School (en)                     |
| Washington University in St. Louis (wd:Q777403) | Washington University in St. Louis (en) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The answer correctly lists the colleges and universities attended by Tennessee Williams, and the SPARQL query returns the correct IRIs. However, the query returns duplicate entries for some colleges. To refine the output, add a DISTINCT modifier to the SELECT clause (SELECT DISTINCT ?college WHERE { ... }) to ensure each college appears only once in the result. This will make the answer more precise and avoid redundant information.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?river ?coord ?image ?osmRelation WHERE {
  VALUES ?river {
    wd:Q8321
  }
  OPTIONAL {
    ?river wdt:P625 ?coord
  }
  OPTIONAL {
    ?river wdt:P18 ?image
  }
  OPTIONAL {
    ?river wdt:P402 ?osmRelation
  }
}

The Illinois River (wd:Q8321) is located at coordinates POINT(-90.454200 38.970300) and POINT(-88.260300 41.393600). You can view it on a map using its OpenStreetMap relation ID: 2182434, or see an image here: http://commons.wikimedia.org/wiki/Special:FilePath/Illinois%20River%2C%20seen%20from%20Starved%20Rock.jpg.

[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] where is the illinois river on a map?

[Assistant]
Let's break down the question:

1. The user is asking about the location of the Illinois River on a map.
2. This implies we need to find the entity for the Illinois River and retrieve its geographic coordinates or a map location property.

Step 1: Find the entity for "Illinois River" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Illinois River (wd:Q8321): Illinois tributary of the Mississippi River in the United States
2. Illinois River (wd:Q1309881): tributary of the Rogue River in Curry and Josephine counties in Oregon, United States
3. Illinois River (wd:Q5999628): Colorado tributary of the Michigan River
4. Illinois River (wd:Q5999623): river in Arkansas and Oklahoma
5. Chicago River, also known as Chicago river, Chicago (river, Illinois), Chicago River main stem, Chicago River (United States) (wd:Q643284): river in Chicago, Illinois, United States
6. Wood River, also known as Wood River, IL, Wood River (Illinois), Wood River, Illinois (wd:Q185601): city in Illinois, United States
7. River Forest, also known as River Forest, IL, River Forest, Illinois (wd:Q2299339): village in Cook County, Illinois, United States
8. River Grove, also known as River Grove, IL, River Grove, Illinois (wd:Q783421): village in Cook County, Illinois, United States of America
9. Apple River, also known as Apple River, Illinois (wd:Q621346): human settlement in Illinois, United States of America
10. Riverside, also known as Riverside, Illinois, Riverside IL, Riverside, IL (wd:Q2462183): village in Cook County, Illinois, United States

[Assistant]
The most relevant entity for the Illinois River (the main tributary of the Mississippi River in Illinois) is wd:Q8321.

Next, I need to find the property in Wikidata that gives the geographic coordinates or map location for a river. I'll search for properties related to "coordinates" or "location."

[Tool]
Top 10 property alternatives:
1. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
2. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
3. length, also known as size, long, LOA, distance, dimension (wd:P2043 as p/wdt): measured dimension of an object
4. 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)
5. 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)
6. GeoNames ID, also known as GeoNames, Geonames Id (wd:P1566 as wdtn/p/wdt): identifier in the GeoNames geographical database
7. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
8. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as wdtn/p/wdt): identifier from an international authority file of names, subjects, and organizations
9. OpenStreetMap relation ID, also known as OpenStreetMap relation, OpenStreetMap relation identifier, OSM relation, OSM relation ID, osm rel id (wd:P402 as wdtn/p/wdt): identifier for a relation in OpenStreetMap

No other items found

[Tool]
Got 2 rows and 3 columns:
| subject                   | property                       | object                                       |
| ------------------------- | ------------------------------ | -------------------------------------------- |
| Illinois River (wd:Q8321) | coordinate location (wdt:P625) | POINT(-90.454200 38.970300) (geo:wktLiteral) |
| Illinois River (wd:Q8321) | coordinate location (wdt:P625) | POINT(-88.260300 41.393600) (geo:wktLiteral) |

[Tool]
Got 1 row and 3 columns:
| subject                   | property        | object                                                                                |
| ------------------------- | --------------- | ----------------------------------------------------------------------------------------------------------- |
| Illinois River (wd:Q8321) | image (wdt:P18) | <http://commons.wikimedia.org/wiki/Special:FilePath/Illinois%20River%2C%20seen%20from%20Starved%20Rock.jpg> |

[Tool]
Got 1 row and 3 columns:
| subject                   | property                             | object  |
| ------------------------- | ------------------------------------ | ------- |
| Illinois River (wd:Q8321) | OpenStreetMap relation ID (wdt:P402) | 2182434 |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the Illinois River's Wikidata identifier, its coordinate locations, an image, and its OpenStreetMap relation ID. The answer provides all relevant information for locating the Illinois River on a map, and the query follows the required guidelines. 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 ?work ?workLabel ?type ?typeLabel WHERE {
  ?work wdt:P161 wd:Q587156 .
  OPTIONAL {
    ?work rdfs:label ?workLabel FILTER ( lang( ?workLabel ) = "en" )
  }
  OPTIONAL {
    ?work wdt:P31 ?type .
    OPTIONAL {
      ?type rdfs:label ?typeLabel FILTER ( lang( ?typeLabel ) = "en" )
    }
  }
}

Got 12 rows and 4 columns, showing the first 5 and last 5 rows below:
| work                                               | workLabel                                 | type                            | typeLabel              |
| -------------------------------------------------- | ----------------------------------------- | ------------------------------- | ---------------------- |
| The Car (wd:Q1197355)                              | The Car (en)                              | film (wd:Q11424)                | film (en)              |
| Escape to Witch Mountain (wd:Q1212511)             | Escape to Witch Mountain (en)             | film (wd:Q11424)                | film (en)              |
| Return from Witch Mountain (wd:Q1925695)           | Return from Witch Mountain (en)           | film (wd:Q11424)                | film (en)              |
| Raid on Entebbe (wd:Q2305094)                      | Raid on Entebbe (en)                      | film (wd:Q11424)                | film (en)              |
| Tuff Turf (wd:Q2362823)                            | Tuff Turf (en)                            | film (wd:Q11424)                | film (en)              |
| ...                                                | ...                                       | ...                             | ...                    |
| Black Snake Moan (wd:Q468660)                      | Black Snake Moan (en)                     | film (wd:Q11424)                | film (en)              |
| Hello, Larry (wd:Q5708520)                         | Hello, Larry (en)                         | television series (wd:Q5398426) | television series (en) |
| No Deposit, No Return (wd:Q7044096)                | No Deposit, No Return (en)                | film (wd:Q11424)                | film (en)              |
| The Real Housewives of Beverly Hills (wd:Q7759591) | The Real Housewives of Beverly Hills (en) | television series (wd:Q5398426) | television series (en) |
| Race to Witch Mountain (wd:Q922006)                | Race to Witch Mountain (en)               | film (wd:Q11424)                | film (en)              |

Kim Richards appeared in the following works (with type):
- The Car (film)
- Escape to Witch Mountain (film)
- Return from Witch Mountain (film)
- Raid on Entebbe (film)
- Tuff Turf (film)
- Black Snake Moan (film)
- Hello, Larry (television series)
- No Deposit, No Return (film)
- The Real Housewives of Beverly Hills (television series)
- Race to Witch Mountain (film)
...and others. The query now returns IRIs, labels, and types for each work.

[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 was kim richards in?

[Assistant]
Let's break down the question:

1. The user is asking about "Kim Richards" and what she was "in"—likely referring to movies, TV shows, or other works she participated in.
2. First, I need to identify the correct entity for Kim Richards in Wikidata.
3. Then, I need to find the property that links a person to works they have acted in (such as "cast member", "actor in", or similar).
4. Finally, I will construct a query to retrieve the works Kim Richards was in.

Let's start by searching for the entity "Kim Richards".

[Tool]
Top 10 entity alternatives:
1. Kim Richards, also known as Kimberley Richards, Kim Erica Richards (wd:Q587156): American actress and television personality (born 1964), television actor, film actor, actor
2. Kim Richards, also known as Kim Elizabeth Richards (wd:Q44115773): Australian politician, politician
3. Kim Richards, also known as NanoKim, NanoSounds (wd:Q123745576): content creator, Twitch streamer
4. Kim Richards (wd:Q76151754): Peerage person ID=566462
5. Kim Richardson, also known as Kimberly Ann Richardson (wd:Q19668126): Canadian actor and singer, jazz musician, actor
6. Kim Lahaie Richards, also known as Kim Lahaie (wd:Q26276511): American drag racer, crew chief, racing automobile driver
7. Kim Michele Richardson (wd:Q100598285): American writer, literary critic, writer
8. Sibel Kekilli, also known as Dilara, Sybel, Kim (wd:Q63682): German actress, actor
9. Kim, also known as Kim, CO (wd:Q2275070): Statutory Town in Las Animas County, Colorado, United States
10. Kim (wd:Q589868): picaresque novel by Rudyard Kipling

[Assistant]
The top result for "Kim Richards" is wd:Q587156, who is an American actress and television personality. This matches the context of the question.

Next, I need to find the property that links an actor to the works they have appeared in. Common properties for this are "cast member", "actor", or "participant in".

I'll search for properties related to "filmography" or "cast member" to find the most appropriate one.

[Tool]
Top 10 property alternatives:
1. TMDB person ID, also known as TMDb person identifier, the movie db person id, themoviedb.org person identifier, themoviedb.org person ID, The Movie Database person identifier (wd:P4985 as p/wdt): identifier for a person at The Movie Database
2. Swedish Film Database person ID, also known as Swedish Film Database person ID, svenskfilmdatabas.se/sv/item/?type=person, SFI person ID, SFDb person ID, Svensk Filmdatabas person ID (wd:P2168 as p/wdt): identifier for a person on the Swedish Film Database (SFDb)
3. IMDb ID, also known as IMDb identifier, Internet Movie Database identifier (wd:P345 as p/wdt): identifier for the IMDb (with prefix 'tt', 'nm', 'co', 'ev', 'ch' or 'ni')
4. Danish National Filmography person ID, also known as Danish National Filmography name, DNF person ID, DNF name, DNF ID (person), DFI person ID (wd:P2626 as p/wdt): identifier for a person in the Danish National Filmography
5. AllMovie person ID, also known as AllMovie ID (wd:P2019 as p/wdt): identifier for a person on the AllMovie film database
6. Ciné-Ressources person ID, also known as Cine person ID, Ciné-Ressources person identifier, cineressources.net person identifier, cineressources.net person ID, Cine person identifier (wd:P3204 as p/wdt): page of a person on the website "Ciné-Ressources"
7. MYmovies person ID (wd:P9995 as p/wdt): identifier for a person on the MYmovies film database
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. Kinobox person ID, also known as https://www.kinobox.cz/osobnosti/, kinobox.cz/osobnosti/, www.kinobox.cz/osobnosti/ (wd:P12098 as p/wdt): identifier for a person on the Kinobox.cz website
10. 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

No other items found

[Tool]
Top 10 property alternatives:
1. 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
2. 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
3. TMDB person ID, also known as TMDb person identifier, the movie db person id, themoviedb.org person identifier, themoviedb.org person ID, The Movie Database person identifier (wd:P4985 as p/wdt): identifier for a person at The Movie Database
4. 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
5. Ciné-Ressources person ID, also known as Cine person ID, Ciné-Ressources person identifier, cineressources.net person identifier, cineressources.net person ID, Cine person identifier (wd:P3204 as p/wdt): page of a person on the website "Ciné-Ressources"
6. TCM Movie Database person ID, also known as TCMDb person ID, TCM person ID, Turner Classic Movies person ID (wd:P3056 as p/wdt): identifier for a person (cast or crew member) in the Turner Classic Movies movie database
7. CineMagia person ID, also known as CineMagia actor ID, CineMagia actor identifier, CineMagia person identifier, Cinemagia.ro person ID, Cinemagia.ro person identifier (wd:P4666 as p/wdt): identifier for a person on the Cinemagia.ro website
8. Film.ru person ID, also known as Film.ru actor ID, Film.ru person identifier, Film.ru actor identifier, Film.ru director ID (wd:P10302 as p/wdt): identifier for people in the Russian film database on film.ru
9. IMDb ID, also known as IMDb identifier, Internet Movie Database identifier (wd:P345 as p/wdt): identifier for the IMDb (with prefix 'tt', 'nm', 'co', 'ev', 'ch' or 'ni')
10. Swedish Film Database person ID, also known as Swedish Film Database person ID, svenskfilmdatabas.se/sv/item/?type=person, SFI person ID, SFDb person ID, Svensk Filmdatabas person ID (wd:P2168 as p/wdt): identifier for a person on the Swedish Film Database (SFDb)

No other items found

[Tool]
Top 10 property alternatives:
1. agent of action, also known as being done by, initiator, initiated by, done by, doer (wd:P12995 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): particular item that initiates this action or class of actions
2. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
3. cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
4. agents of action have role, also known as actors have role, agent has role, agent of action has role, agents have role, done by agent(s) with role (wd:P12993 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): role that agents of this action take on in the context of this action
5. describes actor of (wd:P12027 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): predicate sense whose actor (an agent or a cause—basically the instigator of an action) is denoted by this sense
6. character role, also known as role, plays, performer of, as, acting role (wd:P453 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
7. class of agent(s) of action, also known as agent class of action, done by agent(s) of class, class of doer(s), agent selectional restriction, agent selectional preference (wd:P12994 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): class of items that may initiate this action or class of actions
8. depicted by, also known as acted by, shown in, seen in, portrayed by, played by (wd:P1299 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): object depicting this subject (object being creative works such as books, films, paintings)
9. used by, also known as armiger, user, played by, of (wd:P1535 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): item or concept that makes use of the subject (use sub-properties when appropriate)
10. notable role, also known as notable character role, notable for character role, notable for role (wd:P10606 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): role in a theatrical, motion picture, television, or other work that a performer is particularly known for, notable work

[Tool]
Got 12 rows and 3 columns, showing the first 10 rows below:
| subject                                            | property               | object                    |
| -------------------------------------------------- | ---------------------- | ------------------------- |
| Race to Witch Mountain (wd:Q922006)                | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| Assault on Precinct 13 (wd:Q434718)                | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| Black Snake Moan (wd:Q468660)                      | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| The Car (wd:Q1197355)                              | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| Escape to Witch Mountain (wd:Q1212511)             | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| Return from Witch Mountain (wd:Q1925695)           | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| Raid on Entebbe (wd:Q2305094)                      | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| The Real Housewives of Beverly Hills (wd:Q7759591) | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| Tuff Turf (wd:Q2362823)                            | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| No Deposit, No Return (wd:Q7044096)                | cast member (wdt:P161) | Kim Richards (wd:Q587156) |
| ...                                                | ...                    | ...                       |

[Tool]
Got 12 rows and 1 column, showing the first 5 and last 5 rows below:
| work                                               |
| -------------------------------------------------- |
| The Car (wd:Q1197355)                              |
| Escape to Witch Mountain (wd:Q1212511)             |
| Return from Witch Mountain (wd:Q1925695)           |
| Raid on Entebbe (wd:Q2305094)                      |
| Tuff Turf (wd:Q2362823)                            |
| ...                                                |
| Black Snake Moan (wd:Q468660)                      |
| Hello, Larry (wd:Q5708520)                         |
| No Deposit, No Return (wd:Q7044096)                |
| The Real Housewives of Beverly Hills (wd:Q7759591) |
| Race to Witch Mountain (wd:Q922006)                |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves works in which Kim Richards appeared by using the 'cast member' property (wdt:P161). However, the query only returns the IRIs of the works without any human-readable labels or types. For a more informative answer, it would be helpful to include optional labels (using rdfs:label) and possibly the type of work (e.g., film, TV series) to distinguish between different kinds of appearances. Additionally, the query should use OPTIONAL clauses for these extra pieces of information, as per the guidelines. Please refine the query to include these improvements.

[Assistant]
Thank you for the feedback. To improve the query:

1. I will add OPTIONAL clauses to retrieve the rdfs:label for each work, so the results are more human-readable.
2. I will also attempt to retrieve the type of each work (e.g., film, television series) by including its instance of (wdt:P31) property, and the label for that type.
3. These additions will be OPTIONAL, so the query remains robust even if some works lack labels or type information.

Here is my refined approach:

- For each work (?work) where Kim Richards (wd:Q587156) is a cast member (wdt:P161), retrieve:
  - The work's IRI
  - OPTIONAL: The work's rdfs:label
  - OPTIONAL: The work's type (wdt:P31) and its rdfs:label

Now, I will write and execute the refined SPARQL query.

[Tool]
Got 12 rows and 4 columns, showing the first 5 and last 5 rows below:
| work                                               | workLabel                                 | type                            | typeLabel              |
| -------------------------------------------------- | ----------------------------------------- | ------------------------------- | ---------------------- |
| The Car (wd:Q1197355)                              | The Car (en)                              | film (wd:Q11424)                | film (en)              |
| Escape to Witch Mountain (wd:Q1212511)             | Escape to Witch Mountain (en)             | film (wd:Q11424)                | film (en)              |
| Return from Witch Mountain (wd:Q1925695)           | Return from Witch Mountain (en)           | film (wd:Q11424)                | film (en)              |
| Raid on Entebbe (wd:Q2305094)                      | Raid on Entebbe (en)                      | film (wd:Q11424)                | film (en)              |
| Tuff Turf (wd:Q2362823)                            | Tuff Turf (en)                            | film (wd:Q11424)                | film (en)              |
| ...                                                | ...                                       | ...                             | ...                    |
| Black Snake Moan (wd:Q468660)                      | Black Snake Moan (en)                     | film (wd:Q11424)                | film (en)              |
| Hello, Larry (wd:Q5708520)                         | Hello, Larry (en)                         | television series (wd:Q5398426) | television series (en) |
| No Deposit, No Return (wd:Q7044096)                | No Deposit, No Return (en)                | film (wd:Q11424)                | film (en)              |
| The Real Housewives of Beverly Hills (wd:Q7759591) | The Real Housewives of Beverly Hills (en) | television series (wd:Q5398426) | television series (en) |
| Race to Witch Mountain (wd:Q922006)                | Race to Witch Mountain (en)               | film (wd:Q11424)                | film (en)              |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all works in which Kim Richards appeared, returning the IRIs of the works, their labels, types, and type labels. The answer is accurate, complete, and follows the required guidelines. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?writingSystem ?label WHERE {
  VALUES ?writingSystem {
    wd:Q8201
  }
  OPTIONAL {
    ?writingSystem rdfs:label ?label FILTER ( lang( ?label ) = "en" )
  }
}

Got 1 row and 2 columns:
| writingSystem                 | label                   |
| ----------------------------- | ----------------------- |
| Chinese characters (wd:Q8201) | Chinese characters (en) |

The Chinese writing system is called "Chinese characters" (wd:Q8201).

[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 do you call the chinese writing system?

[Assistant]
Let's break down the question:

1. The user is asking for the name of the Chinese writing system.
2. I need to identify the entity for "Chinese writing system" and find its canonical name or label.

Step 1: Search for the entity "Chinese writing system" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Journal of Chinese Writing Systems (wd:Q58234452): journal
2. Letter-word Phrases and Chinese Writing System (wd:Q120662500): scholarly article in Journal of Xiamen University (Arts & Social Sciences) no. 6, 2010
3. Image-based anti-interference ro...Chinese character writing system (wd:Q129332745): scholarly article
4. Bibliography of the Chinese language and writing system (wd:Q125242720)
5. writing system, also known as wenzi, ven-tsee, script, graphematics (wd:Q8192): any conventional method of visually representing verbal or signed communication
6. Chinese system, also known as Chinese operating system (wd:Q118876973): program that hooks into an operating system to add the ability to display and input CJK characters
7. Conjectures on Creative Writing ...iplinary System of Chinese Style (wd:Q118678085)
8. Chinese-English biliteracy acqui...uage and writing system transfer (wd:Q52040278): scientific article published on 30 December 2004
9. Chinese writing (wd:Q125357998): Book about Chinese palaeography
10. The Chinese-based writing system of the Zhuang language (wd:Q56915490): article

[Assistant]
The search results show that there is no single entity called "Chinese writing system," but there is a general entity for "writing system" (wd:Q8192) and several articles and books about the Chinese writing system. However, the user is likely referring to the specific script used for writing Chinese, which is commonly known as "Chinese characters" or "Han characters."

To confirm, I will search for "Chinese characters" as an entity in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Chinese characters, also known as wenzi, ven-tsee, traditional Vietnamese characters, traditional Korean characters, sinographs (wd:Q8201): logographic writing system with Han origin used in the Sinospher...r Chinese, Japanese, Korean and traditional Vietnamese languages
2. traditional Chinese characters, also known as Chinese characters, Hant, Hanzi, traditional characters, traditional Hanzi (wd:Q178528): late imperial Chinese characters still used for official purposes on Taiwan and in Hong Kong and Macau and informally elsewhere
3. Chinese Characters (wd:Q122342671): 2022 video game
4. simplified Chinese characters, also known as simplified Chinese script, 簡化字, 简化字, simplified Hanzi, simplified Han characters (wd:Q185614): standardized Chinese characters used in Mainland China, Malaysia and Singapore
5. variant sinogram, also known as variant Chinese characters, folk variant, semantic variant (wd:Q837611): different form of Han characters that equivalent in pronunciatio...application such as non-standard abbreviated or simplified forms
6. Singapore Chinese characters (wd:Q391025): writing system for Mandarin Chinese, as used in Singapore
7. abbreviated Chinese character, also known as abbreviated Chinese characters, abbreviated CJK ideograph, abbreviated CJK ideographs, CJKV simplified character, CJKV simplified characters (wd:Q125440195): abbreviated variant of a CJK ideograph
8. Ryukyuan Chinese characters, also known as Ryukyuan Kanji (wd:Q12594322)
9. Wu Chinese characters, also known as wuu-Hans, wuu-Hant (wd:Q6435454): Chinese characters used in the Wu Chinese language
10. Chinese whole characters (wd:Q122761535): complete characters in Chinese writing

[Assistant]
The top result, wd:Q8201 ("Chinese characters"), is described as a logographic writing system with Han origin used in the Sinosphere for Chinese, Japanese, Korean, and traditional Vietnamese languages. This matches the user's intent for the name of the Chinese writing system.

Now, to answer the question, I will write a SPARQL query to return the identifier for "Chinese characters" and its label.

[Tool]
Got 1 row and 2 columns:
| writingSystem                 | label                   |
| ----------------------------- | ----------------------- |
| Chinese characters (wd:Q8201) | Chinese characters (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer is correct and complete. The SPARQL query directly returns the IRI for 'Chinese characters' (wd:Q8201), which is the standard term for the Chinese writing system. The query also optionally retrieves the English label, which is appropriate. No further refinement is needed.