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/>
SELECT ?timeZone ?timeZoneLabel WHERE {
  wd:Q49247 wdt:P421 ?timeZone .
  OPTIONAL {
    ?timeZone rdfs:label ?timeZoneLabel .
    FILTER ( LANG( ?timeZoneLabel ) = "en" )
  }
}

The time zone for Anaheim, California is UTC−08:00 (Pacific Time).

[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 time zone is anaheim california?

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

[Tool]
Example 1:
Question:
what time zone is it in california?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q99 wdt:P421 ?x .
}

Using entities:
California, also known as US-CA, State of California, The Golden State, Calif., Cali. (wd:Q99): 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

Example 2:
Question:
what is my timezone in california?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q99 wdt:P421 ?x .
}

Using entities:
California, also known as US-CA, State of California, The Golden State, Calif., Cali. (wd:Q99): 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

Example 3:
Question:
what is the time zone in california called?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q99 wdt:P421 ?x .
}

Using entities:
California, also known as US-CA, State of California, The Golden State, Calif., Cali. (wd:Q99): 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] From the examples, we can see that the property `located in time zone` (wdt:P421) is used to find the time zone of a place. However, these examples are for the entire state of California. We need to find the specific time zone for Anaheim, California. Let's first find the entity for Anaheim, California.

[Tool]
Top 10 entity alternatives:
1. Anaheim, also known as Anaheim, CA, Anaheim, California (wd:Q49247): city in Orange County, California, United States
2. Anaheim Hills, also known as Anaheim Hills, Anaheim, California, Anaheim Hills, California, Anaheim Hills, CA (wd:Q4750886): neighborhood of Anaheim, California, United States of America
3. Anaheim Resort, also known as Anaheim Resort, Anaheim, California (wd:Q4750892): district of Anaheim, California, United States of America
4. South Anaheim, also known as South Anaheim, CA, South Anaheim, California (wd:Q122543853): populated place in Orange County, California, United States
5. timeline of Anaheim, California (wd:Q21028367): timeline of the history of Anaheim, California, United States
6. 2017 Anaheim, California protests (wd:Q28864574)
7. 2020 COVID-19 pandemic in Anaheim, California, also known as COVID-19 pandemic in Anaheim, California, Anaheim, California COVID-19 pandemic, 2020 COVID pandemic in Anaheim, California, 2020 Anaheim, California COVID-19 pandemic, 2020 coronavirus outbreak in Anaheim, California (wd:Q95681856): pandemic in Anaheim, California
8. economy of Anaheim, California (wd:Q106020266): economy of the region
9. Mayor of Anaheim, California (wd:Q109339715): political office in the United States
10. West Anaheim Junction, also known as West Anaheim Junction, CA, West Anaheim Junction, California (wd:Q122599118): populated place in Orange County, California, United States

[Assistant]
The top result for "Anaheim, California" is `wd:Q49247`, which represents the city of Anaheim. Now that we have the entity for Anaheim, let's check if it has a direct time zone property (wdt:P421).

If it does not, we will fall back to checking the time zone of Orange County or the broader area of California, since Anaheim is part of Orange County and follows the same time zone as the rest of California.

Let's start by checking Anaheim directly:

```sparql
SELECT ?timeZone WHERE {
  wd:Q49247 wdt:P421 ?timeZone .
}
```

If this query returns no results, we will then check the time zone for Orange County or California.

[Tool]
Got 1 row and 1 column:
| timeZone             |
| -------------------- |
| UTC−08:00 (wd:Q2204) |

[Assistant]
The query returned the time zone for Anaheim, California, which is `UTC−08:00`. This corresponds to the Pacific Time Zone.

To provide a more human-readable label, we can include an optional clause to fetch the label of the time zone.

Here is the final SPARQL query:

```sparql
SELECT ?timeZone ?timeZoneLabel WHERE {
  wd:Q49247 wdt:P421 ?timeZone .
  OPTIONAL { ?timeZone rdfs:label ?timeZoneLabel . FILTER(LANG(?timeZoneLabel) = "en") }
}
```

Let's execute this query to get both the IRI and the label of the time zone.

[Tool]
Got 1 row and 2 columns:
| timeZone             | timeZoneLabel  |
| -------------------- | -------------- |
| UTC−08:00 (wd:Q2204) | UTC−08:00 (en) |

[Assistant]
The time zone for Anaheim, California is `UTC−08:00`, which is commonly known as Pacific Time.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?timeZone ?timeZoneLabel WHERE {
  wd:Q49247 wdt:P421 ?timeZone .
  OPTIONAL { ?timeZone rdfs:label ?timeZoneLabel . FILTER(LANG(?timeZoneLabel) = "en") }
}
```

Answer: The time zone for Anaheim, California is `UTC−08:00` (Pacific Time).

[Tool] Stopped generation process


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

The current head coach of the Carolina Panthers is Dave Canales.

[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 coaches the carolina panthers?

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

[Tool]
Example 1:
Question:
who has coached the baltimore ravens?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q276539 wdt:P286 ?x .
}

Using entities:
Baltimore Ravens (wd:Q276539): National Football League franchise in Baltimore, Maryland

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

Example 2:
Question:
what is the name of the pittsburgh steelers head coach?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q191477 wdt:P286 ?x .
}

Using entities:
Pittsburgh Steelers, also known as Pittsburgh Pirates, Rooneymen, Steelers (wd:Q191477): professional American football team based in Pittsburgh, Pennsylvania

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

Example 3:
Question:
who has coached the minnesota vikings?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q221150 wdt:P286 ?x .
}

Using entities:
Minnesota Vikings, also known as Vikings, Vikes (wd:Q221150): National Football League team

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] From the examples, we can see that the property `head coach` (wdt:P286) is used to link a sports team to its head coach. We need to find the entity for the Carolina Panthers and then use this property to find their current head coach.

[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 correct entity for the Carolina Panthers is `wd:Q330120`. Now, let's use the `head coach` property (wdt:P286) to find out who the current head coach of the Carolina Panthers is.

I'll run a simple SPARQL query to get this information.

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

[Assistant]
The current head coach of the Carolina Panthers is Dave Canales.

To ensure this is the most recent and accurate information, I will also check if there are any qualifiers or additional details about the coaching period.

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

[Assistant]
Based on the results, the current head coach of the Carolina Panthers is Dave Canales, who started his tenure on January 1, 2024.

Here is the final SPARQL query and answer:

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

The current head coach of the Carolina Panthers is **Dave Canales**.

[Tool] Stopped generation process


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT DISTINCT ?actor WHERE {
  ?production p:P161 ?statement .
  ?statement ps:P161 ?actor ; pq:P453 wd:Q16311 .
}

Got 5 rows and 1 column:
| actor                        |
| ---------------------------- |
| William Shatner (wd:Q16297)  |
| Sam Witwer (wd:Q18918)       |
| Chris Pine (wd:Q23466)       |
| Paul Wesley (wd:Q270149)     |
| Lloyd Ahlquist (wd:Q6662247) |

The actors who played James T. Kirk include William Shatner, Sam Witwer, Chris Pine, Paul Wesley, and Lloyd Ahlquist.

[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 played kirk?

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

[Tool]
Example 1:
Question:
who played captain kirk in star trek?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q16311 .
}

Using entities:
James T. Kirk, also known as James Kirk, James Tiberius Kirk, Jim Kirk, Captain Kirk, Captain James Tiberius Kirk (wd:Q16311): fictional character from Star Trek, spaceship captain, tactician, explorer

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)

Example 2:
Question:
where does kirk cameron live now?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q471858 wdt:P551 ?x .
}

Using entities:
Kirk Cameron (wd:Q471858): television producer, television actor, American actor, film producer, screenwriter, voice actor, comedian, composer, dancer, singer, actor

Using properties:
residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as wdt): the place where the person is or has been, resident, location

Example 3:
Question:
who played kitt in knight rider?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q464009 p:P725 ?p .
  ?p ps:P725 ?x ; pq:P453 wd:Q1088996 .
}

Using entities:
KITT, also known as K.I.T.T., Knight Industries Two Thousand (wd:Q1088996): fictional car in the 1980s television series Knight Rider
Knight Rider (wd:Q464009): 1982–1986 American television series

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

[Assistant] Based on the similar examples, it seems like we need to identify the character "Kirk" and then find out who played him. Let's first search for the entity "Kirk" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. church building, also known as christian temple, church, church meetinghouse, kirk, meetinghouse (wd:Q16970): building for Christian worship
2. Kirk, also known as Kirk, CO, Kirk, Colorado (wd:Q6415372): census-designated place in Yuma County, Colorado
3. Thomas Kirk, also known as T. Kirk, Kirk (wd:Q930525): New Zealand botanist and botanical collector (1828-1898), botanical collector, horticulturist, botanist, writer
4. Kirk (wd:Q4667452): human settlement in Azerbaijan
5. Kirksville Regional Airport, also known as IRK, KIRK (wd:Q6415839): airport in Missouri, United States
6. Kirk (wd:Q1743473): family name
7. Kirk (wd:Q68764325): 2019 album by DaBaby
8. Kirk, also known as Kirk (given name), Kirk (first name) (wd:Q19819758): male given name
9. Kirk (wd:Q22154110): crater on Charon
10. Thomas Kirk, also known as Kirk (wd:Q7791550): British artist (1765-1797), illustrator, printmaker, painter

[Assistant] None of these options seem to refer to the character "Kirk" from Star Trek. Let's try searching specifically for "James T. Kirk" or "Captain Kirk".

[Tool]
Top 10 entity alternatives:
1. James T. Kirk, also known as James Kirk, James Tiberius Kirk, Jim Kirk, Captain Kirk, Captain James Tiberius Kirk (wd:Q16311): fictional character from Star Trek, spaceship captain, tactician, explorer
2. James T. Kirk, also known as James Thompson Kirk (wd:Q6143939): Union Army officer (1826–1886), military officer, merchant
3. James T. Kirk, also known as James T. Kirk (alternate reality) (wd:Q119138548): character in Star Trek played by Chris Pine, spaceship captain
4. James Thomas Kirk, also known as James T. Kirk (wd:Q106802878): Mayor of Elizabeth, New Jersey, politician
5. James Thomas Kirk (wd:Q110717345): PhD, University of Washington, 2014
6. Timothy James Kirk (wd:Q75419123): Peerage person ID=129835
7. TJ Kirk, also known as The Amazing Atheist, Thomas James Kirk III (wd:Q28968045): American YouTube personality and author, television producer, podcaster, YouTuber
8. Timothy Kirkpatrick, also known as Timothy James Kirkpatrick, Tim Kirkpatrick (wd:Q111751712): American drummer, songwriter, musician, drummer
9. The Autobiography of James T. Kirk (wd:Q54826009)
10. The Autobiography of James T. Kirk (wd:Q54826008)

[Assistant]
The first option, "James T. Kirk" (wd:Q16311), is the character from Star Trek. Now let's find out who played this character. Based on the examples, we can use the property `P161` (cast member) with the qualifier `P453` (character role).

Let's construct a SPARQL query to find the actor who played James T. Kirk.

```sparql
SELECT DISTINCT ?actor WHERE {
  ?production p:P161 ?statement .
  ?statement ps:P161 ?actor ;
             pq:P453 wd:Q16311 .
}
```

This query will find the actor who played the character James T. Kirk in any production.

Let's execute this query.

[Tool]
Got 5 rows and 1 column:
| actor                        |
| ---------------------------- |
| William Shatner (wd:Q16297)  |
| Sam Witwer (wd:Q18918)       |
| Chris Pine (wd:Q23466)       |
| Paul Wesley (wd:Q270149)     |
| Lloyd Ahlquist (wd:Q6662247) |

[Assistant]
The query returned multiple actors who have played the character James T. Kirk in different productions:

- William Shatner (wd:Q16297)
- Sam Witwer (wd:Q18918)
- Chris Pine (wd:Q23466)
- Paul Wesley (wd:Q270149)
- Lloyd Ahlquist (wd:Q6662247)

Since the question is broad and doesn't specify a particular production, we can list all of these actors. However, the most well-known actor who played James T. Kirk is William Shatner.

Let's provide the final answer.

[Tool] Stopped generation process


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/>
SELECT ?placeOfDeath ?placeOfDeathLabel WHERE {
  wd:Q1317 wdt:P20 ?placeOfDeath .
  OPTIONAL {
    ?placeOfDeath rdfs:label ?placeOfDeathLabel .
    FILTER ( LANG( ?placeOfDeathLabel ) = 'en' )
  }
}

Osama bin Laden was killed at his compound in Abbottabad, Pakistan.

[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 was osama bin laden killed?

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

[Tool]
Example 1:
Question:
what country did osama bin laden live in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1317 p:P551 ?p .
  ?p ps:P551 ?y .
  ?y wdt:P17 ?x .
}

Using entities:
Osama bin Laden, also known as Usama bin Laden, Usāmah bin Muḥammad bin ‘Awaḍ bin Lādin, Osama bin Mohammed bin Awad bin Laden, Crankshaft (wd:Q1317): Saudi terrorist and co-founder of al-Qaeda (1957–2011), businessperson, civil engineer, terrorist, jihadist

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as ps/p): the place where the person is or has been, resident, location

Example 2:
Question:
what country was bin laden from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1317 wdt:P27 ?x .
}

Using entities:
Osama bin Laden, also known as Usama bin Laden, Usāmah bin Muḥammad bin ‘Awaḍ bin Lādin, Osama bin Mohammed bin Awad bin Laden, Crankshaft (wd:Q1317): Saudi terrorist and co-founder of al-Qaeda (1957–2011), businessperson, civil engineer, terrorist, jihadist

Using properties:
country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt): the object is a country that recognizes the subject as its citizen, country

Example 3:
Question:
what city was robert kennedy killed in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q25310 wdt:P20 ?x .
}

Using entities:
Robert F. Kennedy, also known as Robert Kennedy, Robert Francis Kennedy, RFK, Bobby Kennedy (wd:Q25310): United States politician, military officer, politician, lawyer, writer

Using properties:
place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location

[Assistant] From the examples, we can see that the property `place of death` (P20) is relevant to our question. Let's first confirm the entity for Osama bin Laden.

[Tool]
Top 10 entity alternatives:
1. Osama bin Laden, also known as Usama bin Laden, Usāmah bin Muḥammad bin ‘Awaḍ bin Lādin, Osama bin Mohammed bin Awad bin Laden, Crankshaft (wd:Q1317): Saudi terrorist and co-founder of al-Qaeda (1957–2011), businessperson, civil engineer, terrorist, jihadist
2. Osama bin Laden (wd:Q10612826): rogue bull elephant in India
3. death of Osama bin Laden, also known as Geronimo EKIA, killing of Bin Laden, killing of Osama bin Laden, Operation Neptune Spear, Osama bin Laden death (wd:Q19085): U.S. military operation in Abbottabad, Pakistan
4. Osama bin Laden bodyguards (wd:Q7105668): bodyguards of Osama Bin Laden
5. Osama Bin Laden Tape (wd:Q110056559): sketch from Saturday Night Live
6. Meeting Osama Bin Laden (wd:Q129687082): 2004 Television film
7. Operation Osama Bin Laden (wd:Q122824240): 2021 video game
8. Targeted: Osama Bin Laden (wd:Q129687094): 2004 Television film
9. Fatwas of Osama bin Laden (wd:Q5437340)
10. 2007 Osama bin Laden video (wd:Q4609081): 2007 film

[Assistant] The correct entity for Osama bin Laden is `wd:Q1317`. Now let's use the property `place of death` (P20) to find out where he was killed.

[Tool]
Got 1 row and 1 column:
| placeOfDeath                                           |
| ------------------------------------------------------ |
| Osama bin Laden's compound in Abbottabad (wd:Q3065522) |

[Assistant]
The place where Osama bin Laden was killed is his compound in Abbottabad, Pakistan.

Now, let's get the label for the place to provide a more human-readable answer.

[Tool]
Got 1 row and 2 columns:
| placeOfDeath                                           | placeOfDeathLabel                             |
| ------------------------------------------------------ | --------------------------------------------- |
| Osama bin Laden's compound in Abbottabad (wd:Q3065522) | Osama bin Laden's compound in Abbottabad (en) |

[Assistant]
The place where Osama bin Laden was killed is his compound in Abbottabad, Pakistan.

Here is the final SPARQL query and answer:

```sparql
SELECT ?placeOfDeath ?placeOfDeathLabel WHERE {
  wd:Q1317 wdt:P20 ?placeOfDeath .
  OPTIONAL { ?placeOfDeath rdfs:label ?placeOfDeathLabel . FILTER(LANG(?placeOfDeathLabel) = 'en') }
}
```

Answer: Osama bin Laden was killed at his compound in Abbottabad, Pakistan.

[Tool] Stopped generation process


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/>
SELECT ?coordinates ?location ?locationLabel WHERE {
  wd:Q5680 wdt:P625 ?coordinates .
  OPTIONAL {
    wd:Q5680 wdt:P131 ?location .
  }
  OPTIONAL {
    ?location rdfs:label ?locationLabel .
    FILTER ( LANG( ?locationLabel ) = "en" )
  }
}

Nineveh is located at coordinates POINT(43.150000 36.366667) in Mosul, Iraq.

[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 nineveh city?

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

[Tool]
Example 1:
Question:
where is the capital city of assyrians?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q41137 wdt:P36 ?x .
}

Using entities:
Assyrian Empire, also known as Assyria, Early Period (wd:Q41137): major Mesopotamian East Semitic kingdom

Using properties:
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

Example 2:
Question:
what is the capital city of assyrian empire?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q41137 wdt:P36 ?x .
}

Using entities:
Assyrian Empire, also known as Assyria, Early Period (wd:Q41137): major Mesopotamian East Semitic kingdom

Using properties:
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

Example 3:
Question:
what city became the capital of the assyrian empire?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q41137 wdt:P36 ?x .
}

Using entities:
Assyrian Empire, also known as Assyria, Early Period (wd:Q41137): major Mesopotamian East Semitic kingdom

Using properties:
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

[Assistant] From the examples, we can see that the property `wdt:P36` is used to find the capital of a country or region. However, Nineveh is not mentioned directly in these examples. Let's search for the entity "Nineveh" to find its IRI.

[Tool]
Top 10 entity alternatives:
1. Nineveh (wd:Q5680): ancient Assyrian city, capital of the Neo-Assyrian Empire
2. Upper Mesopotamia, also known as Nineveh, Northwestern Iraq, كهاف الخيل, Jazira, Assyria (wd:Q311819): northern portion of region between Tigris and Euphrates rivers, now part of Iraq, Syria and Turkey
3. Nineveh, also known as Nineveh, IN, Nineveh, Indiana (wd:Q14688715): unincorporated community in Johnson County, Indiana
4. Nineveh, also known as Nineveh, New York, Nineveh, NY (wd:Q3477846): human settlement in New York, United States of America
5. Nineveh, also known as Nineveh, New York, Nineveh, NY (wd:Q3477846): human settlement in New York, United States of America
6. Nineveh, also known as Nineveh, Missouri, Nineveh, MO (wd:Q18353599): human settlement in Adair County, Missouri, United States
7. Nineveh, also known as Nineveh, England (wd:Q14955822): name of multiple places in England, UK
8. Nineveh, also known as Nineveh, Lunenburg, Nova Scotia (wd:Q7038584): human settlement in Lunenburg County, Nova Scotia, Canada
9. Nineveh, also known as Nineveh, Pennsylvania (wd:Q24259678): human settlement in Greene County, Pennsylvania, United States
10. Nineveh, also known as Nineveh (song), Nineveh (Brooke Ligertwood song) (wd:Q111036727): 2022 song by Brooke Ligertwood

[Assistant]
The correct entity for the ancient Assyrian city of Nineveh is `wd:Q5680`. Now, let's check if there is a property that indicates the location or coordinates of this city.

I will search for properties related to the location of Nineveh.

[Tool]
Top 10 property alternatives:
1. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): 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 wdt/p): 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. geoshape, also known as Commons map data, geographic data, geographic shape, .map, map data (wd:P3896 as wdt/p): geographic data from Wikimedia Commons
4. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
6. heritage designation, also known as legal protection, protection, protected status, listing, listed status (wd:P1435 as wdt/p): heritage designation of a cultural or natural site, has part(s), instance of
7. culture, also known as archaeological culture, civilisation, civilization (wd:P2596 as wdt/p): human culture or people (or several cultures) associated with this item, part of
8. capital of, also known as national capital of, parish seat of, provincial capital of, seat of, state capital (wd:P1376 as wdt/p): country, state, department, canton or other administrative division of which the municipality is the governmental seat, located in the administrative territorial entity
9. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
10. Schoenberg Database of Manuscripts place ID, also known as SDBM place authority ID, SDBM place ID, Schoenberg Database of Manuscripts place authority ID (wd:P9757 as wdt/p): identifier for a place in the Schoenberg Database of Manuscripts

No other items found

[Assistant]
The property `wdt:P625` (coordinate location) seems to be the most relevant for finding the location of Nineveh. Let's construct a SPARQL query to retrieve the coordinates of Nineveh.

```sparql
SELECT ?coordinates WHERE {
  wd:Q5680 wdt:P625 ?coordinates .
}
```

Now, let's execute this query to get the coordinates of Nineveh.

[Tool]
Got 1 row and 1 column:
| coordinates                                 |
| ------------------------------------------- |
| POINT(43.150000 36.366667) (geo:wktLiteral) |

[Assistant]
The coordinates of Nineveh are `POINT(43.150000 36.366667)`. To provide a more human-readable location, we can also look for the administrative territorial entity where Nineveh is located using the property `wdt:P131`.

Let's extend the query to include the administrative territorial entity:

```sparql
SELECT ?coordinates ?location WHERE {
  wd:Q5680 wdt:P625 ?coordinates .
  OPTIONAL { wd:Q5680 wdt:P131 ?location . }
}
```

Now, let's execute this query to get both the coordinates and the location of Nineveh.

[Tool]
Got 1 row and 2 columns:
| coordinates                                 | location          |
| ------------------------------------------- | ----------------- |
| POINT(43.150000 36.366667) (geo:wktLiteral) | Mosul (wd:Q83317) |

[Assistant]
The coordinates of Nineveh are `POINT(43.150000 36.366667)`, and it is located in Mosul (wd:Q83317).

To provide a complete answer, we can also include the label of Mosul for better readability. Let's modify the query to include the label of the location:

```sparql
SELECT ?coordinates ?location ?locationLabel WHERE {
  wd:Q5680 wdt:P625 ?coordinates .
  OPTIONAL { wd:Q5680 wdt:P131 ?location . }
  OPTIONAL { ?location rdfs:label ?locationLabel . FILTER(LANG(?locationLabel) = "en") }
}
```

Now, let's execute this query to get the coordinates, the location, and the label of the location of Nineveh.

[Tool]
Got 1 row and 3 columns:
| coordinates                                 | location          | locationLabel |
| ------------------------------------------- | ----------------- | ------------- |
| POINT(43.150000 36.366667) (geo:wktLiteral) | Mosul (wd:Q83317) | Mosul (en)    |

[Assistant]
The coordinates of Nineveh are `POINT(43.150000 36.366667)`, and it is located in Mosul, Iraq.

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

```sparql
SELECT ?coordinates ?location ?locationLabel WHERE {
  wd:Q5680 wdt:P625 ?coordinates .
  OPTIONAL { wd:Q5680 wdt:P131 ?location . }
  OPTIONAL { ?location rdfs:label ?locationLabel . FILTER(LANG(?locationLabel) = "en") }
}
```

Answer: Nineveh is located at coordinates `POINT(43.150000 36.366667)` in Mosul, Iraq.

[Tool] Stopped generation process


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?actor WHERE {
  wd:Q213081 p:P161 ?statement .
  ?statement ps:P161 ?actor ; pq:P453 wd:Q16311 .
}

Chris Pine

[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 played captain kirk in star trek movie?

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

[Tool]
Example 1:
Question:
who played captain kirk in star trek?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q16311 .
}

Using entities:
James T. Kirk, also known as James Kirk, James Tiberius Kirk, Jim Kirk, Captain Kirk, Captain James Tiberius Kirk (wd:Q16311): fictional character from Star Trek, spaceship captain, tactician, explorer

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)

Example 2:
Question:
who is playing hawkeye in the avengers movie?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q182218 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q24026688 .
}

Using entities:
The Avengers, also known as Marvel's The Avengers, Marvel Avengers Assemble, Avengers, Avengers Assemble (wd:Q182218): 2012 film directed by Joss Whedon
Clint Barton, also known as Hawkeye (wd:Q24026688): fictional character from the Marvel Cinematic Universe

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)

Example 3:
Question:
who played obi wan kenobi in phantom menace?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q165713 p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q51740 .
}

Using entities:
Star Wars: Episode I – The Phantom Menace, also known as Star Wars Episode I, Star Wars Episode I - The Phantom Menace, The Phantom Menace, Star Wars: Episode I - The Phantom Menace, Star Wars: Episode I -- The Phantom Menace (wd:Q165713): 1999 film directed by George Lucas
Obi-Wan Kenobi, also known as Master Kenobi, Obi Wan Kenobi, Obi-Wan "Ben" Kenobi, Obi-Wan, Obi Wan (wd:Q51740): fictional character in the Star Wars universe, Jedi

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 Captain Kirk and the Star Trek movies. Let's first search for Captain Kirk.

[Tool]
Top 10 entity alternatives:
1. James T. Kirk, also known as James Kirk, James Tiberius Kirk, Jim Kirk, Captain Kirk, Captain James Tiberius Kirk (wd:Q16311): fictional character from Star Trek, spaceship captain, tactician, explorer
2. William Kirkpatrick, also known as Colonel Kirkpatrick, William Kirkpatrick (1754-1812), William Kirkpatrick (1756-1812), Captain Kirkpatrick, Col. Kirkpatrick (wd:Q18672883): British army officer in the East India Company and diplomat (1754 or 1756-1812), military personnel, orientalist, diplomat
3. Captain Kirk Douglas, also known as Kirk Douglass, Kirk Douglas (guitarist), Hundred Watt Heart, "Captain" Kirk Douglas (wd:Q5036706): American guitarist, guitarist, musician
4. Where's Captain Kirk? (wd:Q7993095): 1979 song performed by Spizzenergi
5. Duncan Kirk, also known as Captain Duncan Kirk (wd:Q75400490): Peerage person ID=118534
6. Maurice Kirk, also known as Captain Maurice Kirk, Maurice Wrottesley Kirk (wd:Q75822804): British army captain
7. Captain Kirk: Cold Warrior (wd:Q58447877)
8. I Am Captain Kirk (wd:Q113976373)
9. Duncan Kinloch Kirk, also known as Captain Duncan Kinloch Kirk (wd:Q75243859): Peerage person ID=5744
10. Who Killed Captain Kirk? (wd:Q111739107)

[Assistant] The correct entity for Captain Kirk is the first one, `wd:Q16311`. Now let's search for the Star Trek movies.

[Tool]
Top 10 entity alternatives:
1. Star Trek film, also known as Star Trek movie (wd:Q61283808): film of the Star Trek film franchise
2. Star Trek Movie Memories (wd:Q7601044): William Shatner memoir written  with Chris Kreski
3. Star Trek, also known as StarTrek, Star Trek franchise (wd:Q1092): science fiction media franchise
4. Star Trek, also known as Star Trek 09, Star Trek 11, Star Trek 2009 (wd:Q213081): 2009 film directed by J. J. Abrams
5. Star Trek: The Original Series, also known as Those Old Scientists, TOS, ST: TOS, Star Trek: TOS, Star Trek TOS (wd:Q1077): American science fiction television series (1966–1969)
6. Star Trek III: The Search for Spock, also known as Search for Spock, Star Trek, Star Trek 3, The Search for Spock (wd:Q221305): 1984 film directed by Leonard Nimoy
7. movie star, also known as cinema star, film star (wd:Q1337738): celebrity who is famous for starring in motion pictures
8. Star Trek, also known as Star Trek (1971) (wd:Q662253): 1971 command line computer game
9. Star Trek, also known as Star Trek Films (wd:Q1102217): film series
10. Star Trek, also known as 2013 Star Trek, Star Trek The Video Game (wd:Q7601031): 2013 video game

[Assistant]
The entity for the Star Trek movies is `wd:Q61283808` (Star Trek film). However, since we want to know who played Captain Kirk specifically in the Star Trek movies, we should look at individual films. We'll start with the original Star Trek film from 2009, which is `wd:Q213081`.

Now, let's construct a SPARQL query to find out who played Captain Kirk in the 2009 Star Trek film.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the 2009 Star Trek film does not have a direct statement linking the actor to the role of Captain Kirk. Let's try another approach by searching for the cast members of the 2009 Star Trek film and then filtering by the role of Captain Kirk.

We'll list the cast members of the 2009 Star Trek film and see if we can find the role of Captain Kirk.

[Tool]
Got 16 rows and 2 columns, showing the first 5 and last 5 rows below:
| actor                       | role                          |
| --------------------------- | ----------------------------- |
| Karl Urban (wd:Q132430)     | Leonard McCoy (wd:Q16351)     |
| Anton Yelchin (wd:Q314133)  | Pavel Chekov (wd:Q385831)     |
| John Cho (wd:Q312705)       | Hikaru Sulu (wd:Q606202)      |
| Chris Pine (wd:Q23466)      | James T. Kirk (wd:Q119138548) |
| Chris Hemsworth (wd:Q54314) | George Kirk (wd:Q5877874)     |
| ...                         | ...                           |
| Zachary Quinto (wd:Q139642) | Spock (wd:Q119142880)         |
| Winona Ryder (wd:Q101797)   | Amanda Grayson (wd:Q1412447)  |
| Jacob Kogan (wd:Q1638065)   | Spock (wd:Q119142880)         |
| Leonard Nimoy (wd:Q16345)   | Spock (wd:Q16341)             |
| Simon Pegg (wd:Q238464)     | Montgomery Scott (wd:Q607489) |

[Assistant]
From the results, we can see that Chris Pine (wd:Q23466) played the role of James T. Kirk (wd:Q119138548) in the 2009 Star Trek film.

To finalize the answer, let's construct a SPARQL query that directly returns the actor who played Captain Kirk in the 2009 Star Trek film.

[Tool] Stopped generation process


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/>
SELECT DISTINCT ?country ?countryLabel WHERE {
  wd:Q855 wdt:P39 ?position .
  ?position wdt:P1001 ?country .
  OPTIONAL {
    ?country rdfs:label ?countryLabel .
    FILTER ( LANG( ?countryLabel ) = 'en' )
  }
}

Got 3 rows and 2 columns:
| country                                                 | countryLabel                                      |
| ------------------------------------------------------- | ------------------------------------------------- |
| Soviet Union (wd:Q15180)                                | Soviet Union (en)                                 |
| Russian Soviet Federative Socialist Republic (wd:Q2184) | Russian Soviet Federative Socialist Republic (en) |
| Communist Party of the Soviet Union (wd:Q79854)         | Communist Party of the Soviet Union (en)          |

Soviet Union

[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 was stalin in charge of?

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

[Tool]
Example 1:
Question:
what country did truman lead?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q11613 wdt:P39 ?y .
  ?y wdt:P1001 ?x .
}

Using entities:
Harry S. Truman, also known as H. Truman, President Truman, Harry Truman, Truman, H. S. Truman (wd:Q11613): president of the United States from 1945 to 1953; politician (1884-1972), military officer, businessperson, politician, diarist, judge

Using properties:
applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as wdt): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt): subject currently or formerly holds the object position or public office

Example 2:
Question:
what nation did hitler lead?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q352 wdt:P39 ?y .
  ?y wdt:P1001 ?x .
}

Using entities:
Adolf Hitler, also known as Bohemian Corporal (wd:Q352): dictator of Germany from 1933 to 1945, politician

Using properties:
applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as wdt): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt): subject currently or formerly holds the object position or public office

Example 3:
Question:
who was the leader of the soviet union in 1945?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q15180 p:P6 ?p .
  ?p ps:P6 ?x ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "1946-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "1945-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
Soviet Union, also known as Union of Soviet Socialist Republics, The USSR, URS, the Union of Soviet Socialist Republics, the Soviet Union (wd:Q15180): former country in Eurasia (1922–1991)

Using properties:
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): 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 pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as ps/p): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

[Assistant] Based on the examples, we can see that the SPARQL queries involve finding the position held by the person and then determining the jurisdiction that the position applies to. Let's first identify the entity for Stalin.

[Tool]
Top 10 entity alternatives:
1. Joseph Stalin, also known as Koba, Josef Stalin, Joseph Vissarionovitch Stalin, Joseph Vissarionovich Stalin, Uncle Joe (wd:Q855): leader of the Soviet Union from 1924 to 1953, opinion journalist, revolutionary, statesperson, politician, linguist
2. Donetsk, also known as Aleksandrovka, Hughesovka, Stalin, Stalino, Yuzovka (wd:Q43070): city in Ukraine
3. Varna, also known as Stalin, Odesos (wd:Q6506): city in Varna municipality, Varna oblast, Bulgaria
4. Stalin (wd:Q32235): 1992 film directed by Ivan Passer
5. Stalin (wd:Q7597248): 2006 film by A. R. Murugadoss
6. Stalin (wd:Q29437956): biography of Josef Stalin by Leon Trotsky
7. Samson, also known as Stalin (wd:Q4407024)
8. Stalin (wd:Q16281726): name that can be used either as a given name or as a surname
9. Stalin (wd:Q16605767): 1992 film by Kazimierz Kutz
10. Stalin (wd:Q18063553): family name

[Assistant] The top result for "Stalin" is Joseph Stalin, which is the entity we need. Now let's find out what positions he held.

[Tool]
Got 12 rows and 3 columns, showing the first 10 rows below:
| subject                 | property                | object                                                                     |
| ----------------------- | ----------------------- | -------------------------------------------------------------------------- |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | General Secretary of the Communist Party of the Soviet Union (wd:Q1048744) |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | Premier of the Soviet Union (wd:Q462189)                                   |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | Chairman of the Council of People's Commissars (wd:Q4376682)               |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | Chairman of the Council of Ministers of the USSR (wd:Q4376674)             |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | wd:Q107392550                                                              |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | Member of the Politburo of the CPSU Central Committee (wd:Q108495011)      |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | Secretary of the Communist Party of the Soviet Union (wd:Q115147301)       |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | deputy of the Supreme Soviet of the Soviet Union (wd:Q15628644)            |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | wd:Q2367317                                                                |
| Joseph Stalin (wd:Q855) | position held (wdt:P39) | Member of the Russian Constituent Assembly (wd:Q27491113)                  |
| ...                     | ...                     | ...                                                                        |

[Assistant]
We can see that Stalin held several positions, including General Secretary of the Communist Party of the Soviet Union and Premier of the Soviet Union. Next, we need to find out the jurisdiction these positions applied to.

Let's check the jurisdiction for the position of Premier of the Soviet Union.

[Tool]
Got 1 row and 3 columns:
| subject                                  | property                            | object                   |
| ---------------------------------------- | ----------------------------------- | ------------------------ |
| Premier of the Soviet Union (wd:Q462189) | applies to jurisdiction (wdt:P1001) | Soviet Union (wd:Q15180) |

[Assistant]
The position of Premier of the Soviet Union applies to the jurisdiction of the Soviet Union. Therefore, the country Stalin was in charge of was the Soviet Union.

Now, let's construct the final SPARQL query to confirm this.

[Tool]
Got 3 rows and 1 column:
| country                                                 |
| ------------------------------------------------------- |
| Soviet Union (wd:Q15180)                                |
| Russian Soviet Federative Socialist Republic (wd:Q2184) |
| Communist Party of the Soviet Union (wd:Q79854)         |

[Assistant]
The results show that the main country Stalin was in charge of was the Soviet Union. However, it also includes the Russian Soviet Federative Socialist Republic and the Communist Party of the Soviet Union. To refine the query, we can filter out non-country entities.

Let's refine the query to only include countries.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the refined query did not return any results. This might be because the Soviet Union is not directly classified as a country in the same way modern countries are. Let's try another approach by checking the type of the Soviet Union directly.

We can check if the Soviet Union is classified as a country or a similar entity.

[Tool]
Got 1 row and 3 columns:
| subject                  | property              | object                           |
| ------------------------ | --------------------- | -------------------------------- |
| Soviet Union (wd:Q15180) | instance of (wdt:P31) | historical country (wd:Q3024240) |

[Assistant]
The Soviet Union is classified as a historical country. Given this information, we can adjust our query to include historical countries as well.

Let's update the query to include both current and historical countries.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that even with the broader classification, the query did not return any results. Let's try a different approach by directly querying the positions and their jurisdictions without filtering by the type of country.

We can also include the labels for better readability.

[Tool]
Got 3 rows and 2 columns:
| country                                                 | countryLabel                                      |
| ------------------------------------------------------- | ------------------------------------------------- |
| Soviet Union (wd:Q15180)                                | Soviet Union (en)                                 |
| Russian Soviet Federative Socialist Republic (wd:Q2184) | Russian Soviet Federative Socialist Republic (en) |
| Communist Party of the Soviet Union (wd:Q79854)         | Communist Party of the Soviet Union (en)          |

[Assistant]
The results show that the main country Stalin was in charge of was the Soviet Union. The other entities listed are the Russian Soviet Federative Socialist Republic and the Communist Party of the Soviet Union, which are not countries but are part of the Soviet Union.

Therefore, the country Stalin was in charge of was the Soviet Union.

Here is the final SPARQL query and answer:

```sparql
SELECT DISTINCT ?country ?countryLabel WHERE {
  wd:Q855 wdt:P39 ?position .
  ?position wdt:P1001 ?country .
  OPTIONAL { ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = 'en') }
}
```

The answer to the question is: **Soviet Union**.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?language WHERE {
  wd:Q233 wdt:P37 ?language .
}

Got 2 rows and 1 column:
| language           |
| ------------------ |
| English (wd:Q1860) |
| Maltese (wd:Q9166) |

English and Maltese

[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 language do maltese speak?

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

[Tool]
Example 1:
Question:
what kind of language does switzerland speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q39 wdt:P37 ?x .
}

Using entities:
Switzerland, also known as Confoederatio Helvetica, Swiss, Swiss Confederation (wd:Q39): country in Central Europe

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 2:
Question:
what language do people speak in iceland?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q189 wdt:P37 ?x .
}

Using entities:
Iceland, also known as Republic of Iceland, ISL (wd:Q189): Nordic island country in the North Atlantic Ocean

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 do they speak iceland?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q189 wdt:P37 ?x .
}

Using entities:
Iceland, also known as Republic of Iceland, ISL (wd:Q189): Nordic island country in the North Atlantic Ocean

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

[Assistant] Based on the similar examples, it seems like we need to find the official language of Malta. Let's first identify the entity for Malta.

[Tool]
Top 10 entity alternatives:
1. Malta, also known as Republic of Malta, MT, MLT (wd:Q233): sovereign state in Southern Europe situated on an archipelago in the Mediterranean Sea
2. Malta (wd:Q193896): island of Malta
3. Malta, also known as Malta, Montana, Malta, MT (wd:Q963370): city in and county seat of Phillips County, Montana, United States
4. Malta, also known as Malta, Idaho, Malta, ID (wd:Q993877): city in Cassia County, Idaho, United States
5. Malta (wd:Q340115): municipality in Spittal an der Drau District, Carinthia, Austria
6. Malta, also known as Malta, OH (wd:Q2666766): village in Morgan County, Ohio, United States
7. Malta, also known as Malta, IL (wd:Q2672411): village in DeKalb County, Illinois, United States
8. Malta, also known as Santa Rita do Malta (wd:Q2329682): municipality in Paraíba, Brazil
9. Malta, also known as Malta, New York, Malta, NY (wd:Q3708930): town in Saratoga County, New York, United States
10. Malta, also known as Nova (wd:Q1632080): Swedish duo

[Assistant] The correct entity for Malta is the first one, `wd:Q233`. Now let's look for the official language of Malta using the property `wdt:P37`.

[Tool]
Got 2 rows and 1 column:
| language           |
| ------------------ |
| English (wd:Q1860) |
| Maltese (wd:Q9166) |

[Assistant]
Malta has two official languages: English and Maltese.

Here is the final SPARQL query:

```sparql
SELECT DISTINCT ?language WHERE {
  wd:Q233 wdt:P37 ?language .
}
```

And the answer is: **English** and **Maltese**.

[Tool] Stopped generation process


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/>
SELECT ?origin ?originLabel WHERE {
  wd:Q8216 wdt:P144 ?origin .
  OPTIONAL {
    ?origin rdfs:label ?originLabel .
    FILTER ( LANG( ?originLabel ) = 'en' )
  }
}

The Greek alphabet is based on the Phoenician script.

[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 the greek alphabet come from?

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

[Tool]
Example 1:
Question:
where does the roman language come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q397 wdt:P279 ?x .
}

Using entities:
Latin, also known as Latina, Latin language, Latinum (wd:Q397): Indo-European language of the Italic branch

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 2:
Question:
where does the spanish language come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1321 wdt:P279 ?x .
}

Using entities:
Spanish, also known as Castilian, Castilian language, es, esp, Español (wd:Q1321): Romance language originating in the Iberian Peninsula

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:
where did the name rome come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q220 wdt:P138 ?x .
}

Using entities:
Rome, also known as Roma, City of Seven Hills, Rome, Italy, The Eternal City (wd:Q220): capital and largest city of Italy

Using properties:
named after, also known as toponym, namesake, named in honor of, named for, etymology (wd:P138 as wdt): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one

[Assistant] From these examples, it seems like we might want to look at the origin or inspiration of the Greek alphabet. Let's first search for the entity representing the Greek alphabet.

[Tool]
Top 10 entity alternatives:
1. Greek alphabet, also known as Greek script, Greek (wd:Q8216): script used to write the Greek language
2. history of the Greek alphabet, also known as Greek alphabet history, the Greek alphabet history (wd:Q2627294): aspect of history
3. Greek Albanian alphabet (wd:Q3305475): Greek alphabet adapted for writing the Albanian language
4. Greek spelling alphabet (wd:Q17003959): spelling alphabet for Greek letters
5. extended greek alphabet (wd:Q3237041)
6. ancient Greek alphabet, also known as archaic Greek alphabet (wd:Q3611036): writing system
7. archaic Greek alphabets (wd:Q2839562): Local variants of the ancient Greek alphabet
8. Inscriptions in Greek Alphabet (wd:Q106814193): drawing - Sir Robert Smirke the younger (YCBA B1977.14.581)
9. Inscriptions in Greek Alphabet (wd:Q106814190): drawing - Sir Robert Smirke the younger
10. Ancient Inscriptions in Greek Alphabet (wd:Q106812515): drawing - Sir Robert Smirke the younger

[Assistant] The top result, `wd:Q8216`, represents the Greek alphabet. Now let's search for properties related to the origin or inspiration of the Greek alphabet.

[Tool]
Top 10 property alternatives:
1. location of creation, also known as manufactured in, manufacturing location, mint, minted at, photographed at (wd:P1071 as wdt/p): place where the item was conceived or made; where applicable, location of final assembly, significant place
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
3. based on, also known as modelled after, inspired by, iteration of, modeled after, fork of (wd:P144 as wdt/p): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, references work, tradition or theory, inspired by
4. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
5. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as wdt/p): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))

No other items found

[Assistant] The property `based on` (P144) seems relevant for finding what the Greek alphabet was inspired by or derived from. Let's construct a simple SPARQL query to find out what the Greek alphabet is based on.

[Tool]
Got 1 row and 1 column:
| origin                        |
| ----------------------------- |
| Phoenician script (wd:Q26752) |

[Assistant] The Greek alphabet is based on the Phoenician script. To provide a more complete answer, let's include the label of the Phoenician script in our final SPARQL query.

[Tool] Stopped generation process