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 ?country ?countryLabel WHERE {
  wd:Q1215310 wdt:P17 ?country .
  OPTIONAL {
    ?country rdfs:label ?countryLabel .
    FILTER ( LANG( ?countryLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| country        | countryLabel |
| -------------- | ------------ |
| Cuba (wd:Q241) | Cuba (en)    |

The Battle of San Juan Hill took place in Cuba.

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

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

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

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

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

[User] what country did the battle of san juan hill take place?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
what states does the missouri river touch?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5419 wdt:P131 + ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q107390 .
}

Using entities:
federated state, also known as state in a federation, state of a federation, state, federal state, constituent state (wd:Q107390): territorial and constitutional community forming part of a federal union
Missouri River, also known as Missouri, The Missouri (wd:Q5419): major river in central United States

Using properties:
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 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
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
where does portuguese originate?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5146 wdt:P279 ?x .
}

Using entities:
Portuguese, also known as Portuguese language, pt (wd:Q5146): Western Romance language of the Indo-European language family

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

Example 3:
Question:
when was the last superbowl win for the steelers?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?y wdt:P31 / wdt:P279 * wd:Q32096 ; wdt:P1346 wd:Q191477 ; wdt:P585 ?x .
}
ORDER BY DESC ( ?x )
LIMIT 1

Using entities:
Pittsburgh Steelers, also known as Pittsburgh Pirates, Rooneymen, Steelers (wd:Q191477): professional American football team based in Pittsburgh, Pennsylvania
Super Bowl, also known as AFL–NFL World Championship Game (wd:Q32096): National Football League championship game

Using properties:
winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as wdt): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)

[Assistant] Based on the examples, we need to identify the entity for the Battle of San Juan Hill and then find the country where it took place. Let's start by searching for the entity "Battle of San Juan Hill".

[Tool]
Top 10 entity alternatives:
1. Battle of San Juan Hill, also known as Battle for the San Juan Heights (wd:Q1215310): 1898 decisive battle of the Spanish–American War
2. The Battle of San Juan Hill (wd:Q3985806): 1913 film by Francis Ford
3. San Juan Hill order of battle (wd:Q7414586)
4. Battle of San Juan and Chorrillos, also known as Battle of Chorrillos, Battle of San Juan (wd:Q3772977): 1881 battle of the War of the Pacific
5. Battle of San Juan (wd:Q656046): 1797 battle
6. Battle of San Juan (wd:Q4872281): Spanish victory during the Anglo–Spanish War
7. Battle of San Juan (wd:Q4872279): 1625 battle in Puerto Rico
8. Battle of San Juan (wd:Q4872278): 1598 English force of 20 ships took San Juan from Spain for 65 days
9. Battle of San Juan Bautista (wd:Q4872282): 1864 battle
10. Second Battle of San Juan (wd:Q7443113): naval battle during the Spanish-American War (1898)

[Assistant]
The correct entity for the Battle of San Juan Hill is `wd:Q1215310`. Now, let's find out the country where this battle took place. We need to look for a property that indicates the location of the battle. A common property for this would be `wdt:P17` (country).

Let's construct a SPARQL query to find the country where the Battle of San Juan Hill took place.

```sparql
SELECT ?country ?countryLabel
WHERE {
  wd:Q1215310 wdt:P17 ?country .
  OPTIONAL { ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }
}
```

I will now execute this query.

[Tool]
Got 1 row and 2 columns:
| country        | countryLabel |
| -------------- | ------------ |
| Cuba (wd:Q241) | Cuba (en)    |

[Assistant]
The Battle of San Juan Hill took place in Cuba.

Here is the final SPARQL query and answer:

```sparql
SELECT ?country ?countryLabel
WHERE {
  wd:Q1215310 wdt:P17 ?country .
  OPTIONAL { ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }
}
```

Answer: The Battle of San Juan Hill took place in Cuba.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The provided SPARQL query correctly identifies the country where the Battle of San Juan Hill took place. The answer is accurate and complete.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT DISTINCT ?coach ?startTime ?endTime WHERE {
  wd:Q330120 p:P286 ?statement .
  ?statement ps:P286 ?coach .
  OPTIONAL {
    ?statement pq:P580 ?startTime .
  }
  OPTIONAL {
    ?statement pq:P582 ?endTime .
  }
}

The coaches of the Carolina Panthers are: Matt Rhule (2020-2022), Ron Rivera (2011-2019), Dave Canales (2024-present), Frank Reich (2023), Chris Tabor (2023), Perry Fewell (2019), John Fox (2002-2010), and Steven Wilks (2022).

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

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

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

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

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

[User] who has coached the carolina panthers?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
who plays batman in 2012?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?w ; wdt:P580 ?y ; wdt:P582 ?z .
  ?w ps:P161 ?x ; pq:P453 wd:Q2695156 .
  FILTER ( ( ?y >= "2012-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z < "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
Batman, also known as the Bat-Man, the Batman, the Caped Crusader, the Bat, Sir Hemingford Grey (wd:Q2695156): fictional character in DC Comics, chief executive officer, businessperson, martial artist, philanthropist, vigilante, detective, superhero

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as ps/p): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
start time, also known as start date, since, valid, join time, joined (wd:P580 as wdt): time an entity begins to exist or a statement starts being valid, point in time
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as wdt): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 2:
Question:
what team did deion sanders play for in baseball?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q954184 wdt:P54 ?x .
}

Using entities:
Deion Sanders, also known as Deion Luwynn Sanders Sr., Prime Time, Neon Deion (wd:Q954184): American football and baseball player and football coach, American football player, American football coach, baseball player

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

Example 3:
Question:
who is the head coach of the tennessee titans?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q320484 wdt:P286 ?x .
}

Using entities:
Tennessee Titans, also known as Houston Oilers, Tennessee Oilers, Titans (wd:Q320484): National Football League Franchise located in Nashville, Tennessee

Using properties:
head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt): 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

[Assistant] Based on the examples, it seems like we need to identify the Carolina Panthers team and then look for the head coach property (P286). Let's first search for the Carolina Panthers entity.

[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 top result is the Carolina Panthers team itself, which is what we're looking for. Now let's check if the head coach property (P286) is associated with this entity.

[Tool]
Top 10 property alternatives:
1. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as p/wdt): 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. sport, also known as play, plays, sport played, sports (wd:P641 as p/wdt): sport that the subject participates or participated in or is associated with
3. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as p/wdt): owner of the subject
4. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as p/wdt): home stadium or venue of a sports team or applicable performing arts organization, location
6. 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
7. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as p/wdt): league or competition in which team or player has played, or in which an event occurs, participant in
8. Flashscore.com team ID, also known as flashscore.com/team/, FlashScore.com team ID, https://www.flashscore.com/team/, www.flashscore.com/team/ (wd:P7876 as p/wdt): identifier for a sports team in the FlashScore.com database
9. owner of, also known as owns, owns property, shareholder of (wd:P1830 as p/wdt): entities owned by the subject
10. mascot (wd:P822 as p/wdt): mascot of an organization, e.g. a sports team or university

No other items found

[Assistant]
The head coach property (P286) is indeed associated with the Carolina Panthers entity. We can now construct a SPARQL query to find out who has coached the Carolina Panthers.

Let's run the query:

```sparql
SELECT DISTINCT ?coach WHERE {
  wd:Q330120 wdt:P286 ?coach .
}
```

This query will return the coaches of the Carolina Panthers.

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

[Assistant]
The query returned only one coach, Dave Canales. However, this seems incomplete because the Carolina Panthers have had multiple head coaches throughout their history. Let's refine the query to include all historical head coaches by checking for the start and end times of their tenures.

We can use the `pq:P580` (start time) and `pq:P582` (end time) qualifiers to get a more comprehensive list.

Let's update the query:

```sparql
SELECT DISTINCT ?coach ?startTime ?endTime WHERE {
  wd:Q330120 p:P286 ?statement .
  ?statement ps:P286 ?coach .
  OPTIONAL { ?statement pq:P580 ?startTime . }
  OPTIONAL { ?statement pq:P582 ?endTime . }
}
```

This query will return the coaches along with the start and end times of their tenures.

[Tool]
Got 8 rows and 3 columns:
| coach                       | startTime                           | endTime                             |
| --------------------------- | ----------------------------------- | ----------------------------------- |
| Matt Rhule (wd:Q14950994)   | 2020-01-01T00:00:00Z (xsd:dateTime) | 2022-01-01T00:00:00Z (xsd:dateTime) |
| Ron Rivera (wd:Q1991889)    | 2011-01-01T00:00:00Z (xsd:dateTime) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| Dave Canales (wd:Q47456134) | 2024-01-01T00:00:00Z (xsd:dateTime) |                                     |
| Frank Reich (wd:Q5489177)   | 2023-01-01T00:00:00Z (xsd:dateTime) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Chris Tabor (wd:Q57242442)  | 2023-01-01T00:00:00Z (xsd:dateTime) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Perry Fewell (wd:Q7169776)  | 2019-01-01T00:00:00Z (xsd:dateTime) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| John Fox (wd:Q719030)       | 2002-01-01T00:00:00Z (xsd:dateTime) | 2010-01-01T00:00:00Z (xsd:dateTime) |
| Steven Wilks (wd:Q7615391)  | 2022-01-01T00:00:00Z (xsd:dateTime) | 2022-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The updated query has returned a more comprehensive list of head coaches for the Carolina Panthers, including their start and end times. Here are the coaches:

1. **Matt Rhule** (2020-2022)
2. **Ron Rivera** (2011-2019)
3. **Dave Canales** (2024-present)
4. **Frank Reich** (2023)
5. **Chris Tabor** (2023)
6. **Perry Fewell** (2019)
7. **John Fox** (2002-2010)
8. **Steven Wilks** (2022)

Now, let's provide the final SPARQL query and the answer to the user's question.

```sparql
SELECT DISTINCT ?coach ?startTime ?endTime WHERE {
  wd:Q330120 p:P286 ?statement .
  ?statement ps:P286 ?coach .
  OPTIONAL { ?statement pq:P580 ?startTime . }
  OPTIONAL { ?statement pq:P582 ?endTime . }
}
```

The coaches of the Carolina Panthers are:
- Matt Rhule (2020-2022)
- Ron Rivera (2011-2019)
- Dave Canales (2024-present)
- Frank Reich (2023)
- Chris Tabor (2023)
- Perry Fewell (2019)
- John Fox (2002-2010)
- Steven Wilks (2022)

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is well-formed and returns the correct information. It retrieves the coaches of the Carolina Panthers along with their respective start and end times. The human-readable answer is accurate and comprehensive, listing all the coaches and their tenures. No further refinements are 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 ?language ?languageLabel WHERE {
  wd:Q794 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel .
    FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

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

The official language of Iran is Persian.

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

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

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

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

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

[User] what kind of language do they speak in iran?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
what kind of currency does jamaica use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q766 wdt:P38 ?x .
}

Using entities:
Jamaica, also known as JA, JM, JAM, Commonwealth of Jamaica (wd:Q766): island state in the Caribbean Sea

Using properties:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

Example 2:
Question:
what language do argentina use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q414 wdt:P37 ?x .
}

Using entities:
Argentina, also known as Argentine Republic, Republic of Argentina, Republica Argentina (wd:Q414): sovereign state in South America

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 3:
Question:
what time zone is the uk in right now?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q145 wdt:P421 ?x .
}

Using entities:
United Kingdom, also known as U.K., UK, U. K., U K, United Kingdom of Great Britain and Northern Ireland (wd:Q145): country in north-west Europe

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

[Assistant] Based on the examples, we can see that the property `P37` is used to denote the official language of a country. Let's first identify the entity for Iran.

[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 correct entity for Iran is `wd:Q794`. Now let's check if the property `P37` (official language) is used for this entity.

[Tool]
Got 1 row and 3 columns:
| subject        | property                    | object             |
| -------------- | --------------------------- | ------------------ |
| Iran (wd:Q794) | official language (wdt:P37) | Persian (wd:Q9168) |

[Assistant]
The official language of Iran is Persian (`wd:Q9168`). To confirm this and provide a more complete answer, let's run a SPARQL query to get the label of the language as well.

Here is the SPARQL query:

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

Let's execute this query.

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

[Assistant]
The official language of Iran is Persian.

Here is the final SPARQL query and answer:

```sparql
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.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the official language of Iran as Persian, and the human-readable answer is accurate.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?college WHERE {
  wd:Q134262 wdt:P69 ?college .
}

Got 6 rows and 1 column:
| college                                                |
| ------------------------------------------------------ |
| University of Iowa (wd:Q182973)                        |
| University of Missouri (wd:Q579968)                    |
| The New School (wd:Q599316)                            |
| Soldan International Studies High School (wd:Q7557201) |
| Washington University in St. Louis (wd:Q777403)        |
| University City High School (wd:Q7894583)              |

Tennessee Williams attended the following institutions: University of Iowa, University of Missouri, The New School, Soldan International Studies High School, Washington University in St. Louis, and University City High School.

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

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

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

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

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

[User] where did tennessee williams go to college?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
who voice acts peter griffin?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P725 ?y .
  ?y ps:P725 ?x ; pq:P453 wd:Q28465 .
}

Using entities:
Peter Griffin, also known as Justin Peter Griffin, The Fat Man, Peter Löwenbräu Griffin, Sr., Peter Löwenbräu Griffin Sr., Peter Lowenbrau Griffin, Sr. (wd:Q28465): fictional character from the Family Guy franchise

Using properties:
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as ps/p): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member

Example 2:
Question:
what do israeli people speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q801 wdt:P37 ?x .
}

Using entities:
Israel, also known as Yisrael, State of Israel, IL, ISR, il (wd:Q801): country in Western Asia

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 3:
Question:
who does jamie campbell bower play in breaking dawn?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q60506 p:P161 ?p .
  ?p ps:P161 wd:Q313283 ; pq:P453 ?x .
}

Using entities:
Jamie Campbell Bower, also known as James Metcalfe Campbell Bower, Jamie, James Campbell M Bower (wd:Q313283): television actor, British actor, stage actor, film actor, singer, actor, model
The Twilight Saga: Breaking Dawn – Part 1, also known as The Twilight Saga: Breaking Dawn Part 1, Twilight Saga: Breaking Dawn – Part 1 (wd:Q60506): 2011 film by Bill Condon

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as ps/p): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

[Assistant] Based on the examples, we need to identify the entity for Tennessee Williams and the property for college/university attended. Let's first search for the entity "Tennessee Williams".

[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 is `wd:Q134262`. Next, let's search for the property that represents "college/university attended".

[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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): educational institution attended by subject, affiliation
2. academic major, also known as academic subject, college major, field of study, major, studied (wd:P812 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): major someone studied at college/university
3. studied in, also known as is studied by, studied by, science, that studies, researched in, researched by (wd:P2579 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): subject is studied by this science or domain, field of work
4. conferred by, also known as presented by, officiated by, issued by, granted by, given by (wd:P1027 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): person or organization who grants an award, certification, grant, or role
5. academic degree, also known as academic diploma, degree, diploma (wd:P512 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): academic degree that the person holds
6. student of, also known as professor, studied under, pupil of, tutor, mentor (wd:P1066 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): person who has taught this person, significant person
7. athletics program, also known as school district athletics program, school district sports program, school sports program, sports program, university athletics program (wd:P10607 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): the name of a school's athletics program, as opposed to individual teams in particular sports, represented by
8. interested in, also known as area of interest, area of research, field of interest, field of research, field of study (wd:P2650 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): item of special or vested interest to this person or organisation
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): specialization of a person or organization; see P106 for the occupation, interested in
10. has role in modeling, also known as has role in modelling, used for investigating, used for researching, used for studying, used to investigate (wd:P6530 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): relation between a research artefact and an entity that is used ... its replicating or approximating features of the studied entity

[Assistant]
The property "educated at" (`wd:P69`) seems to be the most relevant for representing the colleges or universities that Tennessee Williams attended. Now, let's construct a SPARQL query to find out where Tennessee Williams went to college.

```sparql
SELECT ?college WHERE {
  wd:Q134262 wdt:P69 ?college .
}
```

Let's execute this query.

[Tool]
Got 6 rows and 1 column:
| college                                                |
| ------------------------------------------------------ |
| University of Iowa (wd:Q182973)                        |
| University of Missouri (wd:Q579968)                    |
| The New School (wd:Q599316)                            |
| Soldan International Studies High School (wd:Q7557201) |
| Washington University in St. Louis (wd:Q777403)        |
| University City High School (wd:Q7894583)              |

[Assistant]
The SPARQL query has returned the following institutions where Tennessee Williams attended:

- University of Iowa (wd:Q182973)
- University of Missouri (wd:Q579968)
- The New School (wd:Q599316)
- Soldan International Studies High School (wd:Q7557201)
- Washington University in St. Louis (wd:Q777403)
- University City High School (wd:Q7894583)

These are the colleges and high schools that Tennessee Williams attended. Let's provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns all the educational institutions Tennessee Williams attended. The answer provided is accurate and complete.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?coordinates ?label WHERE {
  wd:Q8321 wdt:P625 ?coordinates .
  OPTIONAL {
    wd:Q8321 rdfs:label ?label .
    FILTER ( LANG( ?label ) = "en" )
  }
}

The Illinois River is located at the following coordinates: 1. POINT(-90.454200 38.970300) 2. POINT(-88.260300 41.393600). These coordinates can be used to plot the river on a map.

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

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

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

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

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

[User] where is the illinois river on a map?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
who founded the new democratic party?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q129634 wdt:P112 ?x .
}

Using entities:
New Democratic Party (wd:Q129634): 1967–1980 political party in South Korea

Using properties:
founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt): founder or co-founder of this organization, religion, place or entity, creator

Example 2:
Question:
what was robert hooke's contributions to science?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P61 wd:Q46830 .
}

Using entities:
Robert Hooke, also known as Hooke (wd:Q46830): English natural philosopher, architect and polymath (1635 — 1703), university teacher, philosopher, naturalist, astronomer, biologist, architect, physicist, inventor, diarist

Using properties:
discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as wdt): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory

Example 3:
Question:
what time is kansas in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1558 wdt:P421 ?x .
}

Using entities:
Kansas, also known as Kan., Kans., Kansas, United States of America, US-KS, KS (wd:Q1558): state of the United States of America

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

[Assistant] Based on the examples, we need to identify the entity for the Illinois River and the property that would give us its location. Let's start by searching for the entity "Illinois River".

[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 top result is the Illinois River (wd:Q8321), which is the Illinois tributary of the Mississippi River in the United States. Now, let's find the property that gives us the location of the Illinois River. We can search for properties related to "location" or "geographical position" for the Illinois River.

[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. 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
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. length, also known as size, long, LOA, distance, dimension (wd:P2043 as p/wdt): measured dimension of an object
6. 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
7. mouth of the watercourse, also known as flows into, watercourse outflow, watercourse ends in, watercourse drain, tributary of (wd:P403 as p/wdt): the body of water to which the watercourse drains

No other items found

[Assistant]
The property `coordinate location` (wd:P625) seems to be the most appropriate for getting the geographical location of the Illinois River. Let's construct a SPARQL query to retrieve the coordinates of the Illinois River.

Here is the initial SPARQL query:

```sparql
SELECT ?coordinates WHERE {
  wd:Q8321 wdt:P625 ?coordinates .
}
```

Let's execute this query to see if it returns the expected results.

[Tool]
Got 2 rows and 1 column:
| coordinates                                  |
| -------------------------------------------- |
| POINT(-90.454200 38.970300) (geo:wktLiteral) |
| POINT(-88.260300 41.393600) (geo:wktLiteral) |

[Assistant]
The query returned two sets of coordinates for the Illinois River. These coordinates represent points along the river. To provide a more complete answer, we can also include the label of the Illinois River in the result. However, since the user did not explicitly request the label, we will keep it optional.

Here is the refined SPARQL query:

```sparql
SELECT ?coordinates ?label WHERE {
  wd:Q8321 wdt:P625 ?coordinates .
  OPTIONAL { wd:Q8321 rdfs:label ?label . FILTER(LANG(?label) = "en") }
}
```

Let's execute this query to see if it includes the label.

[Tool]
Got 2 rows and 2 columns:
| coordinates                                  | label               |
| -------------------------------------------- | ------------------- |
| POINT(-90.454200 38.970300) (geo:wktLiteral) | Illinois River (en) |
| POINT(-88.260300 41.393600) (geo:wktLiteral) | Illinois River (en) |

[Assistant]
The query has successfully returned the coordinates and the label of the Illinois River. The coordinates are:

1. POINT(-90.454200 38.970300)
2. POINT(-88.260300 41.393600)

These points represent different locations along the Illinois River. Since the user asked for the location of the Illinois River on a map, these coordinates can be used to plot the river on a map.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?coordinates ?label WHERE {
  wd:Q8321 wdt:P625 ?coordinates .
  OPTIONAL { wd:Q8321 rdfs:label ?label . FILTER(LANG(?label) = "en") }
}
```

Answer: The Illinois River is located at the following coordinates:
1. POINT(-90.454200 38.970300)
2. POINT(-88.260300 41.393600)

These coordinates can be used to plot the river on a map.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query returns the coordinates of the Illinois River, which can be used to plot it on a map. The query follows all the rules and guidelines provided.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT ?work ?workLabel ?role WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
  ?work wdt:P161 wd:Q587156 .
  OPTIONAL {
    ?work rdfs:label ?workLabel .
    FILTER ( LANG( ?workLabel ) = "en" )
  }
  OPTIONAL {
    wd:Q587156 p:P161 [ ps:P161 ?work ; pq:P453 ?role ]
  }
}

Got 12 rows and 3 columns, showing the first 5 and last 5 rows below:
| work                                               | workLabel                                 | role |
| -------------------------------------------------- | ----------------------------------------- | ---- |
| The Car (wd:Q1197355)                              | The Car (en)                              |      |
| Escape to Witch Mountain (wd:Q1212511)             | Escape to Witch Mountain (en)             |      |
| Return from Witch Mountain (wd:Q1925695)           | Return from Witch Mountain (en)           |      |
| Raid on Entebbe (wd:Q2305094)                      | Raid on Entebbe (en)                      |      |
| Tuff Turf (wd:Q2362823)                            | Tuff Turf (en)                            |      |
| ...                                                | ...                                       | ...  |
| Black Snake Moan (wd:Q468660)                      | Black Snake Moan (en)                     |      |
| Hello, Larry (wd:Q5708520)                         | Hello, Larry (en)                         |      |
| No Deposit, No Return (wd:Q7044096)                | No Deposit, No Return (en)                |      |
| The Real Housewives of Beverly Hills (wd:Q7759591) | The Real Housewives of Beverly Hills (en) |      |
| Race to Witch Mountain (wd:Q922006)                | Race to Witch Mountain (en)               |      |

Kim Richards was in 'Nanny and the Professor' (wd:Q3824558).

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

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

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

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

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

[User] what was kim richards in?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
what is there to do in palm springs?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q570116 ; wdt:P131 wd:Q488004 .
}

Using entities:
Palm Springs, also known as Palm City, Palm Springs, CA, Palm Springs, California (wd:Q488004): resort city in Riverside County, southern California, United States
tourist attraction, also known as attraction for tourists, POI for tourists, tourism attraction, touristic attraction, tourist place (wd:Q570116): place of interest where tourists visit

Using properties:
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 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
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
who was the president of the united states during ww2?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q11696 ; pq:P580 ?y .
  wd:Q362 wdt:P580 ?w ; wdt:P582 ?v .
  FILTER ( ( ( ?y >= ?w ) && ( ?y <= ?v ) ) )
}

Using entities:
President of the United States, also known as US President, U.S. President, United States President, the president of the United States, President of the U.S. (wd:Q11696): head of state and head of government of the United States of America
World War II, also known as 2nd World War, WWII, WW II, WW2, WW 2 (wd:Q362): 1939–1945 global conflict

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/p): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq/wdt): time an entity begins to exist or a statement starts being valid, point in time
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as wdt): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 3:
Question:
who is jeremy sumpter?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q316964 wdt:P106 ?x .
}

Using entities:
Jeremy Sumpter, also known as Jeremy Robert Myron Sumpter (wd:Q316964): television actor, American actor, child actor, film actor, actor, model

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

[Assistant] Based on the examples, it seems like we need to identify Kim Richards and then find out what she was involved in, such as movies, TV shows, or other activities. Let's first search for Kim Richards in the knowledge graph.

[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 the American actress and television personality, which seems to be the correct person we're looking for. Now, let's find out what she was involved in, such as movies, TV shows, or other activities. We can look for properties related to her roles or occupations.

Let's start by listing the properties associated with Kim Richards (wd:Q587156).

[Tool]
Got 303 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                         | object                                                                                |
| ------------------------- | -------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| Kim Richards (wd:Q587156) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Kim Richards (wd:Q587156) | occupation (wdt:P106)            | actor (wd:Q33999)                                                                                |
| Kim Richards (wd:Q587156) | sex or gender (wdt:P21)          | female (wd:Q6581072)                                                                                |
| Kim Richards (wd:Q587156) | given name (wdt:P735)            | Kim (wd:Q637123)                                                                                |
| Kim Richards (wd:Q587156) | date of birth (wdt:P569)         | 1964-09-19T00:00:00Z (xsd:dateTime)                                                                            |
| Kim Richards (wd:Q587156) | Commons category (wdt:P373)      | Kim Richards                                                                                |
| Kim Richards (wd:Q587156) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Nanny%20and%20the%20Professor%20Kim%20Richards%201970.jpg> |
| Kim Richards (wd:Q587156) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                                |
| Kim Richards (wd:Q587156) | family name (wdt:P734)           | Richards (wd:Q608991)                                                                                |
| Kim Richards (wd:Q587156) | place of birth (wdt:P19)         | Mineola (wd:Q2349502)                                                                                |
| ...                       | ...                              | ...                                                                                |

[Assistant]
From the list of properties, we can see that Kim Richards is an actor. To find out what she was in, we need to look for specific works or productions she was involved in. We can use the `work` or `filmography` properties to find this information.

Let's search for properties related to her works or films.

[Tool]
Top 10 property alternatives:
1. 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)
2. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as p/wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
3. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as p/wdt): language in which the writer has written their work, languages spoken, written or signed
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. 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
6. 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)
7. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
8. 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
9. sibling, also known as is sister of, is the brother of, is the sibling of, is the sister of, sib (wd:P3373 as p/wdt): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), relative
10. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant]
It seems that the properties related to her works or films are not directly listed. However, we can try to find the specific works or films she was involved in by looking for properties like `part of` or `cast member of`.

Let's search for properties related to her involvement in films or TV shows.

[Tool]
Top 10 property alternatives:
1. 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)
2. 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)
3. 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)
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. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
6. 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
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
8. 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)
9. 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
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

[Assistant]
It appears that the properties related to her involvement in films or TV shows are not directly listed. However, we can try to find the specific works or productions she was involved in by looking for properties like `cast member of` or `part of`.

Let's search for properties related to her involvement in films or TV shows more broadly.

[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

[Assistant]
It seems that the properties related to her involvement in films or TV shows are not directly listed. However, we can try to find the specific works or productions she was involved in by looking for properties like `cast member of` or `part of` more generally.

Let's try a different approach and search for the specific works or productions she was involved in by looking for properties like `cast member of` or `part of` in the context of films and TV shows.

We can use the `wdt:P161` property, which is commonly used to indicate that someone is a cast member of a film or TV show.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the `wdt:P161` property did not return any results for Kim Richards. This might be because the data is structured differently or the property is not directly linked to her.

Let's try another approach by searching for properties related to her filmography or works more broadly. We can also look for properties that indicate her involvement in specific productions, such as `part of` or `cast member of` in a more general sense.

Let's try using the `wdt:P800` property, which indicates notable works or achievements, and see if it provides any results.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the `wdt:P800` property also did not return any results for Kim Richards. This suggests that the data might be structured differently or the properties we are using might not be the right ones.

Let's try a more comprehensive approach by looking for any properties that might indicate her involvement in films or TV shows. We can use a broader query to find any works or productions she was involved in, including roles, performances, or other contributions.

We can use the `wdt:P106` property to confirm her occupation as an actor and then look for any related works or productions.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that even with a more comprehensive approach, we are not getting any results for Kim Richards' involvement in specific works or productions. This might be due to the data not being structured in a way that directly links her to these works.

Let's try a different approach by searching for specific works or productions she is known to have been in, such as "Nanny and the Professor" or "The Shining," and then see if we can find a connection through those works.

First, let's search for "Nanny and the Professor" and "The Shining" in the knowledge graph and see if we can find any connections to Kim Richards.

[Tool]
Top 10 entity alternatives:
1. Nanny and the Professor (wd:Q3824558): television series
2. Nanny and the Professor (wd:Q17507182): 1972 television film
3. The Nanny and the Professor, also known as The Gilmore Girls S04E10 (wd:Q6145613): episode of Gilmore Girls
4. Nanny and the Professor, season 1 (wd:Q97274140): season of television series
5. Nanny and the Professor, season 2 (wd:Q97274149): season of television series
6. Nanny and the Professor, season 3 (wd:Q97274158): season of television series
7. The Professor and the Madman, also known as Professor and the Madman (wd:Q27961908): 2019 film directed by Farhad Safinia
8. The Housekeeper and the Professor (wd:Q1072975): 2003 novel by Yoko Ogawa
9. The Surgeon of Crowthorne, also known as The Professor and the Madman (wd:Q3818805): book by Simon Winchester
10. The Professor and the Siren, also known as Lighea (wd:Q17333244): Novella

[Assistant]
The top result for "Nanny and the Professor" is the television series (wd:Q3824558). Let's check if Kim Richards is listed as a cast member of this series.

We can use the `wdt:P161` property to find the cast members of "Nanny and the Professor" and see if Kim Richards is among them.

Let's execute this query:

[Tool]
Got 5 rows and 1 column:
| actor                       |
| --------------------------- |
| Richard Long (wd:Q339593)   |
| Juliet Mills (wd:Q444988)   |
| David Doremus (wd:Q5233030) |
| Kim Richards (wd:Q587156)   |
| Trent Lehman (wd:Q7838420)  |

[Assistant]
Great! The query confirms that Kim Richards (wd:Q587156) was indeed a cast member of "Nanny and the Professor" (wd:Q3824558).

Now, let's also check if she was involved in "The Shining" to see if that is another work she was in. First, let's search for "The Shining" in the knowledge graph.

Let's search for "The Shining" and see if we can find any connections to Kim Richards.

[Tool]
Top 10 entity alternatives:
1. The Shining, also known as Shining (wd:Q186341): 1980 film directed by Stanley Kubrick
2. The Shining (wd:Q470937): 1977 novel by Stephen King
3. The Shining, also known as Shining, Stephen King's The Shining (wd:Q1811161): 1997 American television miniseries
4. The Shining (wd:Q5229426): album by J Dilla
5. The Shining (wd:Q1373482): English rock band
6. The Shining (wd:Q7763823): album by Violent J
7. The Shining (wd:Q22986315): 1989 studio album by Gandalf & Galadriel
8. The Shining (wd:Q11897302): single
9. The Shining (wd:Q16955658): album by RBX
10. The Shining (wd:Q25218646): American opera based on the novel by Stephen King

[Assistant]
The top result for "The Shining" is the 1980 film directed by Stanley Kubrick (wd:Q186341). Let's check if Kim Richards is listed as a cast member of this film.

We can use the `wdt:P161` property to find the cast members of "The Shining" and see if Kim Richards is among them.

Let's execute this query:

[Tool]
Got 12 rows and 1 column, showing the first 5 and last 5 rows below:
| actor                         |
| ----------------------------- |
| Tony Burton (wd:Q1337159)     |
| Joe Turkel (wd:Q1691628)      |
| Philip Stone (wd:Q1804810)    |
| Manning Redwood (wd:Q1890742) |
| Shelley Duvall (wd:Q235478)   |
| ...                           |
| Barry Nelson (wd:Q443790)     |
| Anne Jackson (wd:Q454394)     |
| Scatman Crothers (wd:Q501996) |
| Barry Dennen (wd:Q809029)     |
| Danny Lloyd (wd:Q959299)      |

[Assistant]
The query results show the cast members of "The Shining" (1980 film directed by Stanley Kubrick), but Kim Richards (wd:Q587156) is not listed among them.

Based on the information we have gathered, Kim Richards was a cast member of "Nanny and the Professor" (wd:Q3824558), but she was not a cast member of "The Shining" (wd:Q186341).

To provide a comprehensive answer, we can conclude that Kim Richards was involved in "Nanny and the Professor."

Let's finalize the answer with a SPARQL query that confirms her involvement in "Nanny and the Professor."

Here is the final SPARQL query:

```sparql
SELECT ?work WHERE {
  wd:Q587156 wdt:P161 ?work .
  FILTER(?work = wd:Q3824558)
}
```

This query will return the work "Nanny and the Professor" (wd:Q3824558) as the result, confirming that Kim Richards was involved in this production.

Let's execute this final query and provide the answer.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the final query did not return any results, which is unexpected since we previously confirmed that Kim Richards was a cast member of "Nanny and the Professor." This might be due to a minor issue in the query structure or data consistency.

Let's simplify the query to just confirm her involvement in "Nanny and the Professor" without the filter, and then we can manually verify the result.

Here is the simplified query:

```sparql
SELECT ?work WHERE {
  wd:Q587156 wdt:P161 ?work .
}
```

This query will return all works she was involved in, and we can manually verify that "Nanny and the Professor" is among them.

Let's execute this simplified query and provide the answer.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that even the simplified query did not return any results, which is unexpected. This suggests that the data might be structured differently or there might be an issue with the specific properties we are using.

Given the previous results, we know that Kim Richards was indeed a cast member of "Nanny and the Professor" (wd:Q3824558). Let's manually construct the final answer based on this information.

Here is the final SPARQL query that confirms her involvement in "Nanny and the Professor":

```sparql
SELECT ?work WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
}
```

This query will return the work "Nanny and the Professor" (wd:Q3824558) as the result, confirming that Kim Richards was involved in this production.

Let's execute this final query and provide the answer.

```sparql
SELECT ?work WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
}
```

[Tool]
Got 1 row and 1 column:
| work |
| ---- |

[Assistant]
The query confirms that Kim Richards (wd:Q587156) was indeed a cast member of "Nanny and the Professor" (wd:Q3824558).

Therefore, the answer to the question "What was Kim Richards in?" is that she was in "Nanny and the Professor."

Here is the final SPARQL query and answer:

```sparql
SELECT ?work WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
}
```

Answer: Kim Richards was in "Nanny and the Professor."

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

```json
{
  "kg": "wikidata",
  "sparql": "SELECT ?work WHERE { wd:Q3824558 wdt:P161 wd:Q587156 . }",
  "answer": "Kim Richards was in 'Nanny and the Professor'."
}
```

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is correct in identifying that Kim Richards was in 'Nanny and the Professor'. However, the query could be improved to return the label of the work for better readability. Additionally, it would be beneficial to include the role she played in the show if that information is available.

[Assistant]
Thank you for the feedback. Let's improve the SPARQL query to return the label of the work for better readability and, if possible, include the role she played in the show.

First, let's modify the query to return the label of the work. We can use the `rdfs:label` property to get the label of the work.

Next, we will check if there is information about the role she played in the show. We can use the `wdt:P453` property, which indicates the role or character played by an actor in a production.

Here is the improved SPARQL query:

```sparql
SELECT ?work ?workLabel ?role WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
  OPTIONAL { wd:Q3824558 rdfs:label ?workLabel . FILTER(LANG(?workLabel) = "en") }
  OPTIONAL { wd:Q587156 p:P161 [ ps:P161 wd:Q3824558 ; pq:P453 ?role ] }
}
```

This query will return the work, its label, and the role she played, if available.

Let's execute this improved query and provide the answer.

```sparql
SELECT ?work ?workLabel ?role WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
  OPTIONAL { wd:Q3824558 rdfs:label ?workLabel . FILTER(LANG(?workLabel) = "en") }
  OPTIONAL { wd:Q587156 p:P161 [ ps:P161 wd:Q3824558 ; pq:P453 ?role ] }
}
```

[Tool]
Got 1 row and 3 columns:
| work | workLabel                    | role |
| ---- | ---------------------------- | ---- |
|      | Nanny and the Professor (en) |      |

[Assistant]
The improved query confirms that Kim Richards was in "Nanny and the Professor," and it also returns the label of the work for better readability. However, it does not return the specific role she played in the show, which might not be available in the knowledge graph.

Here is the final SPARQL query and answer:

```sparql
SELECT ?work ?workLabel ?role WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
  OPTIONAL { wd:Q3824558 rdfs:label ?workLabel . FILTER(LANG(?workLabel) = "en") }
  OPTIONAL { wd:Q587156 p:P161 [ ps:P161 wd:Q3824558 ; pq:P453 ?role ] }
}
```

Answer: Kim Richards was in 'Nanny and the Professor'.

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

```json
{
  "kg": "wikidata",
  "sparql": "SELECT ?work ?workLabel ?role WHERE { wd:Q3824558 wdt:P161 wd:Q587156 . OPTIONAL { wd:Q3824558 rdfs:label ?workLabel . FILTER(LANG(?workLabel) = \"en\") } OPTIONAL { wd:Q587156 p:P161 [ ps:P161 wd:Q3824558 ; pq:P453 ?role ] } }",
  "answer": "Kim Richards was in 'Nanny and the Professor'."
}
```

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct, but it does not return the role Kim Richards played in 'Nanny and the Professor'. The role should be included in the result. Additionally, the work IRI should be returned in the result, even if the label is also provided.

[Assistant]
Thank you for the feedback. Let's refine the SPARQL query to ensure it returns both the work IRI and the role Kim Richards played in 'Nanny and the Professor'. If the role is not available, it should still return the work IRI and label.

Here is the refined SPARQL query:

```sparql
SELECT ?work ?workLabel ?role WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
  ?work wdt:P161 wd:Q587156 .
  OPTIONAL { ?work rdfs:label ?workLabel . FILTER(LANG(?workLabel) = "en") }
  OPTIONAL { wd:Q587156 p:P161 [ ps:P161 ?work ; pq:P453 ?role ] }
}
```

This query ensures that the work IRI is returned, along with its label and the role, if available.

Let's execute this refined query and provide the answer.

```sparql
SELECT ?work ?workLabel ?role WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
  ?work wdt:P161 wd:Q587156 .
  OPTIONAL { ?work rdfs:label ?workLabel . FILTER(LANG(?workLabel) = "en") }
  OPTIONAL { wd:Q587156 p:P161 [ ps:P161 ?work ; pq:P453 ?role ] }
}
```

[Tool]
Got 12 rows and 3 columns, showing the first 5 and last 5 rows below:
| work                                               | workLabel                                 | role |
| -------------------------------------------------- | ----------------------------------------- | ---- |
| The Car (wd:Q1197355)                              | The Car (en)                              |      |
| Escape to Witch Mountain (wd:Q1212511)             | Escape to Witch Mountain (en)             |      |
| Return from Witch Mountain (wd:Q1925695)           | Return from Witch Mountain (en)           |      |
| Raid on Entebbe (wd:Q2305094)                      | Raid on Entebbe (en)                      |      |
| Tuff Turf (wd:Q2362823)                            | Tuff Turf (en)                            |      |
| ...                                                | ...                                       | ...  |
| Black Snake Moan (wd:Q468660)                      | Black Snake Moan (en)                     |      |
| Hello, Larry (wd:Q5708520)                         | Hello, Larry (en)                         |      |
| No Deposit, No Return (wd:Q7044096)                | No Deposit, No Return (en)                |      |
| The Real Housewives of Beverly Hills (wd:Q7759591) | The Real Housewives of Beverly Hills (en) |      |
| Race to Witch Mountain (wd:Q922006)                | Race to Witch Mountain (en)               |      |

[Assistant]
The query results show multiple works in which Kim Richards has been involved, but it does not specify the role she played in each. However, it confirms that she was indeed in "Nanny and the Professor" (wd:Q3824558).

Since the role information is not available for "Nanny and the Professor," we will include the work IRI and label in the final answer.

Here is the final SPARQL query and answer:

```sparql
SELECT ?work ?workLabel ?role WHERE {
  wd:Q3824558 wdt:P161 wd:Q587156 .
  ?work wdt:P161 wd:Q587156 .
  OPTIONAL { ?work rdfs:label ?workLabel . FILTER(LANG(?workLabel) = "en") }
  OPTIONAL { wd:Q587156 p:P161 [ ps:P161 ?work ; pq:P453 ?role ] }
}
```

Answer: Kim Richards was in 'Nanny and the Professor' (wd:Q3824558).

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

```json
{
  "kg": "wikidata",
  "sparql": "SELECT ?work ?workLabel ?role WHERE { wd:Q3824558 wdt:P161 wd:Q587156 . ?work wdt:P161 wd:Q587156 . OPTIONAL { ?work rdfs:label ?workLabel . FILTER(LANG(?workLabel) = \"en\") } OPTIONAL { wd:Q587156 p:P161 [ ps:P161 ?work ; pq:P453 ?role ] } }",
  "answer": "Kim Richards was in 'Nanny and the Professor' (wd:Q3824558)."
}
```

[Tool] Stopped generation process