PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?date WHERE {
  wd:Q33132 wdt:P580 ?date
}

The Battle of Gettysburg started on July 1, 1863.

[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

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] When was the Battle of Gettysburg?

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

[Tool]
Example 1:
Question:
When did Operation Overlord commence?

SPARQL:
SELECT DISTINCT ?date WHERE {
  wd:Q8641370 wdt:P580 ?date .
}

Using entities:
Operation Overlord, also known as Battle of Normandy, Normandy landings (wd:Q8641370): 1944 successful Allied invasion of Nazi-held western Europe in World War II

Using properties:
start time, also known as start date, since, valid, join time, joined (wd:P580 as wdt): time an entity begins to exist or a statement starts being valid, point in time

[Assistant] The Battle of Gettysburg is an event, and we want to find the date it happened. Based on the similar example, the property "start time" (wdt:P580) is used to indicate when an event started. I will first search for the entity "Battle of Gettysburg" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Battle of Gettysburg (wd:Q33132): 1863 battle of the American Civil War
2. The Battle of Gettysburg, also known as Battle of Gettysburg (wd:Q3985807): 1913 film by Charles Giblyn, Thomas H. Ince
3. The Battle of Gettysburg, also known as Battle of Gettysburg (wd:Q7715862): 1955 documentary film by Herman Hoffman
4. Battle of Gettysburg order of battle (wd:Q124022501)
5. The battle of Gettysburg (wd:Q74684783): scientific article published on 01 August 1990
6. Gettysburg Confederate order of battle (wd:Q904364): 1863 American order of battle
7. Gettysburg Union order of battle (wd:Q840730)
8. Battle of Gettysburg, First Day (wd:Q841268): first day of the Battle of Gettysburg during the American Civil War
9. Battle of Gettysburg, Second Day (wd:Q905574): battle of the American Civil War
10. Battle of Gettysburg half dollar (wd:Q28104126): Background

[Assistant] The entity "Battle of Gettysburg" is wd:Q33132. Now I will query the start date (property wdt:P580) of this battle.

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 1863-07-01T00:00:00Z (xsd:dateTime) |

[Assistant] The Battle of Gettysburg started on July 1, 1863. I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the start date of the Battle of Gettysburg using the property 'start time' (wdt:P580) for the entity Battle of Gettysburg (wd:Q33132). The answer 'The Battle of Gettysburg started on July 1, 1863.' is accurate and matches the query result. The query follows the rules by returning the actual identifier and the date value. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?work ?workLabel WHERE {
  ?work wdt:P50 wd:Q72653 .
  OPTIONAL {
    ?work rdfs:label ?workLabel FILTER ( LANG( ?workLabel ) = "en" )
  }
}

Got 231 rows and 2 columns, showing the first 5 and last 5 rows below:
| work                                   | workLabel                   |
| -------------------------------------- | --------------------------- |
| wd:Q100257629                          |                             |
| Jewels (wd:Q10306884)                  | Jewels (en)                 |
| The Promise (wd:Q10381720)             | The Promise (en)            |
| The Sins of the Mother (wd:Q107074924) | The Sins of the Mother (en) |
| First Sight (wd:Q107074970)            | First Sight (en)            |
| ...                                    | ...                         |
| The Wedding (wd:Q7774042)              | The Wedding (en)            |
| Thurston House (wd:Q7799449)           | Thurston House (en)         |
| Toxic Bachelors (wd:Q7830354)          | Toxic Bachelors (en)        |
| Wanderlust (wd:Q7967238)               | Wanderlust (en)             |
| Sunset in St. Tropez (wd:Q951140)      | Sunset in St. Tropez (en)   |

This query retrieves all works authored by Danielle Steel (wd:Q72653), including those not explicitly marked as instances of 'book'. It also optionally retrieves English labels for better readability. This approach provides a more comprehensive list of her books and other works.

[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

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] Give me all books written by Danielle Steel.

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

[Tool]
Example 1:
Question:
Show me all books in Asimov's Foundation series.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1564644 wdt:P527 ?uri
}

Using entities:
Foundation series, also known as The Foundation Series (wd:Q1564644): series of science fiction books by Isaac Asimov

Using properties:
has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).

Example 2:
Question:
Show me the book that Muhammad Ali wrote.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q571 .
  ?uri wdt:P50 wd:Q36107 .
}

Using entities:
Muhammad Ali, also known as Cassius Clay, The Greatest, Muhammad Ali Clay, Cassius Marcellus Clay Jr. (wd:Q36107): American boxer (1942–2016), boxer
book, also known as books (wd:Q571): medium for recording information (words or images) typically on bound pages or more abstractly in electronic or audio form

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

Example 3:
Question:
Give me all federal chancellors of Germany.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P39 wd:Q4970706 .
}

Using entities:
Federal Chancellor of Germany, also known as German Federal Chancellor, prime minister of Germany, German Chancellor, Federal Chancellor of the Federal Republic of Germany, Federal Chancellor (wd:Q4970706): head of government of the Federal Republic of Germany (1949–present)

Using properties:
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

[Assistant]
From the examples, we see that to find books written by a specific author, we can query for items that are instances of "book" (wd:Q571) and have the author property (wdt:P50) set to the author entity.

Next, I will search for the Wikidata entity for Danielle Steel.

[Tool]
Top 10 entity alternatives:
1. Danielle Steel, also known as Danielle Fernandes Dominique Schülein-Steel, Danielle Fernandes Dominique Schuelein-Steel (wd:Q72653): children's writer, American writer, novelist, writer
2. Danielle Steel's Star, also known as Star (wd:Q4189382): 1993 film directed by Michael Miller
3. Changes, also known as Danielle Steel's Changes (wd:Q4994471): 1991 television film directed by Charles Jarrott
4. Secrets, also known as Danielle Steel's Secrets (wd:Q2264138): 1992 American television film by Peter H. Hunt
5. Daddy, also known as Danielle Steel's Daddy (wd:Q5207983): 1991 television film
6. Kaleidoscope, also known as Danielle Steel's Kaleidoscope (wd:Q6351961): 1990 film directed by Jud Taylor
7. Danielle Steel's 'Palomino' (wd:Q5219445): 1991 television film
8. Mixed Blessings, also known as Danielle Steel's Mixed Blessings (wd:Q6883881): 1995 American television film directed by Bethany Rooney
9. Danielle Steel's A Perfect Stranger (wd:Q5219446): 1994 TV-film by Michael Miller
10. Message from Nam, also known as Danielle Steel's 'Message from Nam' (wd:Q3492381): 1993 television film

[Assistant] The Wikidata entity for Danielle Steel is wd:Q72653. Now I will write a SPARQL query to find all books (instances of wd:Q571) where Danielle Steel is the author (wdt:P50).

[Tool] Got no rows and 2 columns

[Assistant]
The query returned no results, which is unexpected since Danielle Steel is a well-known author. It is possible that the author property (wdt:P50) is not used consistently for her books or the books are not explicitly marked as instances of "book" (wd:Q571).

I will try a more general query to find works authored by Danielle Steel without restricting to instance of book.

[Tool]
Got 50 rows and 2 columns, showing the first 5 and last 5 rows below:
| work                                   | workLabel                   |
| -------------------------------------- | --------------------------- |
| wd:Q100257629                          |                             |
| Jewels (wd:Q10306884)                  | Jewels (en)                 |
| The Promise (wd:Q10381720)             | The Promise (en)            |
| The Sins of the Mother (wd:Q107074924) | The Sins of the Mother (en) |
| First Sight (wd:Q107074970)            | First Sight (en)            |
| ...                                    | ...                         |
| wd:Q121952745                          |                             |
| wd:Q121953657                          |                             |
| wd:Q121958947                          |                             |
| wd:Q121958954                          |                             |
| wd:Q121963114                          |                             |

[Assistant] I found several works authored by Danielle Steel. Some have English labels like "Jewels," "The Promise," "The Sins of the Mother," and "First Sight." To ensure these are books, I will now check which of these works are instances of "book" (wd:Q571). I will do this by filtering the previous results to only those that are instances of books.

[Tool] Got no rows and 2 columns

[Assistant] It seems that the works authored by Danielle Steel are not explicitly marked as instances of "book" (wd:Q571). To provide a comprehensive answer, I will return all works authored by Danielle Steel regardless of their instance type, as these are likely her books. I will include their labels for better readability.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves all works authored by Danielle Steel, but it does not explicitly filter for items that are instances of 'book' (wd:Q571). This means the result may include works that are not books, such as articles or other types of creative works. To improve the query, add a triple pattern to ensure that the works are instances of 'book'. This will make the answer more precise and aligned with the user's request for books specifically.

[Assistant]
Thank you for the feedback. I understand that the query should explicitly filter for works that are instances of "book" (wd:Q571) to ensure the results are specifically books written by Danielle Steel.

Previously, I tried this filter but got no results, which might be due to incomplete data in Wikidata. However, I will try again to include the filter for instance of "book" and return the results. If no results are found, it indicates that the data is missing, but the query will be correct for the intended purpose.

[Tool] Got no rows and 2 columns

[Assistant]
The query with the filter for instance of "book" (wd:Q571) still returns no results, indicating that the data for Danielle Steel's books may not be fully marked with this property in Wikidata.

Despite this, the correct approach to answer the user's question is to include this filter to ensure only books are returned.

I will provide the final SPARQL query with the filter for instance of "book" and explain the situation in the answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is logically correct for retrieving books written by Danielle Steel by checking for items that are instances of 'book' (wd:Q571) and authored by Danielle Steel (wd:Q72653). However, the query returns no results because Wikidata does not explicitly mark Danielle Steel's works as instances of 'book'. To improve the query, consider removing the instance of 'book' filter (wdt:P31 wd:Q571) to retrieve all works authored by Danielle Steel, which may include books not explicitly typed as such. Additionally, ensure that labels are retrieved optionally and filtered for English. This refinement will likely yield more results and better answer the user's question.

[Assistant] Thank you for the feedback. Based on it, I will refine the query by removing the instance of "book" filter and retrieving all works authored by Danielle Steel. I will keep the optional retrieval of English labels to provide readable titles. This approach will likely yield more results and better answer the user's question.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?daughter ?daughterLabel ?spouse ?spouseLabel WHERE {
  VALUES ?daughter {
    wd:Q273833 wd:Q467861 wd:Q467912
  }
  ?daughter wdt:P26 ?spouse .
  OPTIONAL {
    ?daughter rdfs:label ?daughterLabel FILTER ( LANG( ?daughterLabel ) = "en" )
  }
  OPTIONAL {
    ?spouse rdfs:label ?spouseLabel FILTER ( LANG( ?spouseLabel ) = "en" )
  }
}

Got 3 rows and 4 columns:
| daughter                               | daughterLabel                  | spouse                            | spouseLabel             |
| -------------------------------------- | ------------------------------ | --------------------------------- | ----------------------- |
| Kerry Kennedy (wd:Q467912)             | Kerry Kennedy (en)             | Andrew Cuomo (wd:Q11673)          | Andrew Cuomo (en)       |
| Rory Kennedy (wd:Q273833)              | Rory Kennedy (en)              | Mark Bailey (wd:Q29938796)        | Mark Bailey (en)        |
| Kathleen Kennedy Townsend (wd:Q467861) | Kathleen Kennedy Townsend (en) | David Lee Townsend (wd:Q75326812) | David Lee Townsend (en) |

The daughters of Robert Kennedy and their spouses are: Kerry Kennedy is married to Andrew Cuomo, Rory Kennedy is married to Mark Bailey, and Kathleen Kennedy Townsend is married to David Lee Townsend.

[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

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 is the daughter of Robert Kennedy married to?

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

[Tool]
Example 1:
Question:
Who became president after JFK died?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q9696 p:P39 ?position .
  ?position ps:P39 wd:Q11696 .
  ?position pq:P1366 ?uri .
}

Using entities:
President of the United States, also known as US President, U.S. President, United States President, the president of the United States, President of the U.S. (wd:Q11696): head of state and head of government of the United States of America
John F. Kennedy, also known as John Kennedy, John Fitzgerald Kennedy, John F Kennedy, Kennedy, President Kennedy (wd:Q9696): President of the United States from 1961 to 1963, anti-communist, naval officer, statesperson, journalist, politician, writer

Using properties:
replaced by, also known as heir, superseded by, successor, succeeded by, next job holder (wd:P1366 as pq): other person or item which continues the item by replacing it in... nor identical, but adds to the series (e.g. books in a series)., followed by
position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/p): subject currently or formerly holds the object position or public office

Example 2:
Question:
Was the wife of president Lincoln called Mary?

SPARQL:
ASK WHERE {
  wd:Q91 wdt:P26 ?spouse .
  ?spouse rdfs:label ?name .
  FILTER ( regex( ?name , 'Mary' ) )
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

Example 3:
Question:
Whom did Lance Bass marry?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q443120 wdt:P26 ?uri .
}

Using entities:
Lance Bass (wd:Q443120): American singer, dancer, actor, and film and television producer, television producer, television actor, autobiographer, film producer, stage actor, voice actor, film actor, dancer, singer, actor

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

[Assistant]
The examples show that to find who someone is married to, we can use the property "spouse" (wdt:P26). First, I need to identify the daughter or daughters of Robert Kennedy. Then I can find the spouse of that daughter or those daughters.

Step 1: Identify Robert Kennedy in Wikidata.
Step 2: Find the daughters of Robert Kennedy.
Step 3: Find the spouses of those daughters.

I will start by searching for Robert Kennedy in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Robert F. Kennedy, also known as Robert Kennedy, Robert Francis Kennedy, RFK, Bobby Kennedy (wd:Q25310): United States politician, military officer, politician, lawyer, writer
2. Robert Kennedy, also known as Robert L. Kennnedy (wd:Q59010): Irish field hockey player (1880–1963), field hockey player
3. Bobby Kennedy, also known as Robert Kennedy (wd:Q4935237): Scottish footballer and manager, association football manager, association football player
4. Robert Kennedy, also known as Robert John Kennedy (wd:Q7346314): New Zealand cricketer, cricketer
5. Robert P. Kennedy, also known as Robert Kennedy, Robert Patterson Kennedy (wd:Q7348217): Union Army officer (1840–1918), military officer, politician, lawyer
6. Robert Kennedy (wd:Q7346315): Canadian publisher (1938–2012), publisher
7. Robert B. Kennedy, also known as R. B. Kennedy, Robert Kennedy (wd:Q16105383): American politician, politician
8. Bob Kennedy, also known as Robert Kennedy, Robert Michael Kennedy (wd:Q4933007): American football player (1928–1991), American football player
9. Robert Kennedy, also known as Robert Edward Kennedy (wd:Q7346313): American Jesuit priest, psychoanalyst and Zen rōshi, writer
10. Robert Kennedy (wd:Q125958286): rhodesian rugby player (1925–1979), rugby union player

[Assistant] Robert F. Kennedy (wd:Q25310) is the relevant Robert Kennedy who was a United States politician. Next, I will find the daughters of Robert F. Kennedy. To find daughters, I will look for the property "child" (wdt:P40) and filter for female children. I will first list the children of Robert F. Kennedy.

[Tool]
Got 11 rows and 3 columns, showing the first 10 rows below:
| subject                       | property        | object                                 |
| ----------------------------- | --------------- | -------------------------------------- |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | Robert F. Kennedy Jr. (wd:Q1352872)    |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | Rory Kennedy (wd:Q273833)              |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | Kerry Kennedy (wd:Q467912)             |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | Joseph P. Kennedy II (wd:Q1386420)     |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | Kathleen Kennedy Townsend (wd:Q467861) |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | Michael LeMoyne Kennedy (wd:Q1804720)  |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | David A. Kennedy (wd:Q1975383)         |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | Douglas Harriman Kennedy (wd:Q5301573) |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | Christopher G. Kennedy (wd:Q5112377)   |
| Robert F. Kennedy (wd:Q25310) | child (wdt:P40) | Max Kennedy (wd:Q6794923)              |
| ...                           | ...             | ...                                    |

[Assistant] Robert F. Kennedy has several children. Now I need to find which of these children are daughters. I will check the gender (wdt:P21) of these children to identify the daughters. I will query the gender of the children.

[Tool]
Got 3 rows and 3 columns:
| child                                  | childLabel                     | genderLabel |
| -------------------------------------- | ------------------------------ | ----------- |
| Rory Kennedy (wd:Q273833)              | Rory Kennedy (en)              | female (en) |
| Kathleen Kennedy Townsend (wd:Q467861) | Kathleen Kennedy Townsend (en) | female (en) |
| Kerry Kennedy (wd:Q467912)             | Kerry Kennedy (en)             | female (en) |

[Assistant] The daughters of Robert F. Kennedy are Rory Kennedy, Kathleen Kennedy Townsend, and Kerry Kennedy. Now, I will find the spouses of these daughters using the property "spouse" (wdt:P26). I will query the spouses of these three daughters.

[Tool]
Got 3 rows and 4 columns:
| daughter                               | daughterLabel                  | spouse                            | spouseLabel             |
| -------------------------------------- | ------------------------------ | --------------------------------- | ----------------------- |
| Kerry Kennedy (wd:Q467912)             | Kerry Kennedy (en)             | Andrew Cuomo (wd:Q11673)          | Andrew Cuomo (en)       |
| Rory Kennedy (wd:Q273833)              | Rory Kennedy (en)              | Mark Bailey (wd:Q29938796)        | Mark Bailey (en)        |
| Kathleen Kennedy Townsend (wd:Q467861) | Kathleen Kennedy Townsend (en) | David Lee Townsend (wd:Q75326812) | David Lee Townsend (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the daughters of Robert Kennedy and their spouses, returning both the identifiers and English labels as requested. The answer provided is accurate and complete, listing all three daughters and their respective spouses. The query uses appropriate properties and entities and follows the rules for SPARQL queries. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?lyricist ?lyricistLabel WHERE {
  wd:Q482988 wdt:P676 ?lyricist .
  OPTIONAL {
    ?lyricist rdfs:label ?lyricistLabel FILTER ( LANG( ?lyricistLabel ) = "en" )
  }
}

The lyrics for the Polish national anthem were written by Józef Wybicki.

[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

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 wrote the lyrics for the Polish national anthem?

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

[Tool]
Example 1:
Question:
How many people live in Poland?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q36 wdt:P1082 ?uri
}

Using entities:
Poland, also known as Republic of Poland (wd:Q36): country in Central Europe

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject

Example 2:
Question:
Who wrote the Game of Thrones theme?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q23572 wdt:P86 ?uri .
}

Using entities:
Game of Thrones, also known as GoT, GOT (wd:Q23572): American fantasy drama television series

Using properties:
composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as wdt): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator

[Assistant]
From the examples, we see that to find the author of a work, the property "composer" (wdt:P86) is used for music, and "lyrics by" (P676) is used for lyricists. We want to find the lyricist of the Polish national anthem.

Next, I will search for the entity "Polish national anthem" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Poland Is Not Yet Lost, also known as Dąbrowski's Mazurka, Polish national anthem, Song of the Polish Legions in Italy (wd:Q482988): national anthem of Poland
2. national anthem, also known as national hymn, state anthem (wd:Q23691): song that represents a country or sovereign state
3. National Anthem of Chile, also known as Canción Nacional, National Anthem (wd:Q484161): National Anthem of Chile
4. National Anthem (wd:Q2697331): Lana Del Rey song
5. National Anthem (wd:Q116945688): 2023 film directed by Luke Gilford
6. The National Anthem, also known as National Anthem (wd:Q19573235): 1999 film by Wu Ziniu
7. National Anthem (wd:Q16955069): album by The Away Team
8. National Anthem (wd:Q39078564): 2003 film
9. America, also known as National Anthem, National Hymn (wd:Q109781686): melody often used for national anthems; first published in 1744
10. National Anthem (wd:Q110059383): sketch from Saturday Night Live

[Assistant] The entity "Poland Is Not Yet Lost" (wd:Q482988) is the Polish national anthem. Now, I will search for the property related to lyrics or lyricist for this entity.

[Tool]
Top 10 property alternatives:
1. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as wdt/p): author of song lyrics, author
2. first line, also known as incipit, opening line, fl, first verse, first sentence (wd:P1922 as wdt/p): first line (incipit) of a poem, first sentence of a novel, speech, etc.
3. audio, also known as audio file, audio recording, audio sample, recording, song (wd:P51 as wdt/p): relevant sound. If available, use a more specific property. Samples: "spoken text audio" (P989), "pronunciation audio" (P443)
4. composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as wdt/p): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator
5. MusicBrainz work ID, also known as composition ID (MusicBrainz), MBID work, MBW, MB work ID, MusicBrainz composition ID (wd:P435 as wdt/wdtn/p): identifier for a work per the MusicBrainz open music encyclopedia
6. last line, also known as closing line, ending, excipit, final line, final sentence (wd:P3132 as wdt/p): last line (excipit) of a poem, last sentence of a novel, etc.
7. tonality, also known as in key, key, key of musical composition, key used, musical key (wd:P826 as wdt/p): key of a musical composition
8. author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt/p): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
9. 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
10. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic

No other items found

[Assistant] The property "lyricist" (wdt:P676) corresponds to the author of song lyrics. I will now write a SPARQL query to find the lyricist of the Polish national anthem (wd:Q482988) using this property.

[Tool]
Got 1 row and 2 columns:
| lyricist                   | lyricistLabel      |
| -------------------------- | ------------------ |
| Józef Wybicki (wd:Q370069) | Józef Wybicki (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the lyricist of the Polish national anthem (Poland Is Not Yet Lost) using the property P676 (lyricist). The query returns the identifier and the English label of Józef Wybicki, who is indeed the author of the lyrics. The answer is accurate and complete, and the query follows the rules by returning the actual identifier and an optional label. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX schema: <http://schema.org/>
SELECT ?item ?itemLabel ?itemDescription WHERE {
  VALUES ?item {
    wd:Q810986
  }
  OPTIONAL {
    ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" )
  }
  OPTIONAL {
    ?item schema:description ?itemDescription FILTER ( LANG( ?itemDescription ) = "en" )
  }
}

Yes, there is a video game called Battle Chess. It is a 1988 chess-playing video game (Wikidata entity: wd:Q810986).

[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

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] Is there a video game called Battle Chess?

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

[Tool] No examples found

[Assistant] There are no similar example questions available. Next, I will search for the entity "Battle Chess" in the knowledge graph to see if it exists as a video game.

[Tool]
Top 10 entity alternatives:
1. Battle Chess (wd:Q810986): 1988 chess-playing video game
2. Battle Chess (wd:Q108370586): video game series
3. Check vs. Mate, also known as Battle vs. Chess (wd:Q3636865): 2011 video game
4. Battle Chess 4000, also known as BC 4000, BC4000 (wd:Q111966835): 1992 video game developed by Interplay
5. Eonica Chess Battle (wd:Q122824456): 2020 early access video game
6. Battle Chess II: Chinese Chess (wd:Q3636840): 1990 video game
7. Battle Chess: Game of Kings (wd:Q4869999): 2014 video game remake
8. Battle Chess Enhanced CD Rom (wd:Q124877749): 1992 video game
9. chess, also known as chess game, Western chess, modern European chess, international chess (wd:Q718): strategy board game
10. battle, also known as ⚔, combat (wd:Q178561): part of a war which is well defined in duration, area and force commitment

[Assistant] There is an entity called "Battle Chess" (wd:Q810986) which is described as a 1988 chess-playing video game. This indicates that there is indeed a video game called Battle Chess. To confirm, I will retrieve the label and description of this entity.

[Tool]
Got 1 row and 3 columns:
| item                      | itemLabel         | itemDescription                    |
| ------------------------- | ----------------- | ---------------------------------- |
| Battle Chess (wd:Q810986) | Battle Chess (en) | 1988 chess-playing video game (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified that there is a video game called Battle Chess and provided the Wikidata entity along with its label and description. The SPARQL query is appropriate and returns the relevant information confirming the existence of the video game. The answer is clear, accurate, and complete.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?lake ?lakeLabel ?area WHERE {
  VALUES ?lake {
    wd:Q5513 wd:Q5525
  }
  ?lake wdt:P2046 ?area .
  OPTIONAL {
    ?lake rdfs:label ?lakeLabel FILTER ( LANG( ?lakeLabel ) = "en" )
  }
}

Lake Baikal has an area of 31,722 square kilometers, while Great Bear Lake has an area of 31,153 square kilometers. Therefore, Lake Baikal is bigger than Great Bear Lake.

[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

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] Is Lake Baikal bigger than the Great Bear Lake?

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

[Tool] No examples found

[Assistant] There are no direct similar examples found. Next, I will identify the entities "Lake Baikal" and "Great Bear Lake" in Wikidata to get their identifiers. Then I will find the property that represents the size or area of a lake to compare these two lakes.

[Tool]
Top 10 entity alternatives:
1. Lake Baikal, also known as Baikal, Baikal Sea, Baykal (wd:Q5513): freshwater rift lake in southern Siberia, Russia
2. Lake Baikal (wd:Q123738053): Canadian animated short film, directed by Alisi Telengut and released in 2023
3. Lake Baikal (wd:L300494-S1)
4. Baikal Seal, also known as Pusa sibirica, Phoca sibirica, Nerpa, Lake baikal seal (wd:Q4535): species of seal
5. Lake Baikal mountain vole, also known as Alticola olchonensis (wd:Q1768026): species of mammal
6. Battle of Lake Baikal (wd:Q11153274): 1918 battle of the Russian Civil War
7. 1862 lake Baikal earthquake (wd:Q4191068)
8. Ambitions for Lake Baikal (wd:Q58990558): scientific article published in Nature
9. Ice cave on Olkhon island, also known as Lake Baikal Ice Cave (wd:Q123524221): ice cave on Lake Baikal, Siberia, Russia
10. Lake Baikal in Crisis (wd:Q116758151): scientific article published in 2022

[Tool]
Top 10 entity alternatives:
1. Great Bear Lake, also known as Sahtú (wd:Q5525): large glacial lake in the Northwest Territories, Canada
2. Great Bear Lake (wd:Q33257595): lake in Van Buren County, Michigan, USA
3. Great Bear Lake (wd:Q39073453): 2009 novel by Erin Hunter
4. Great Bear Lake Airport, also known as DAS (wd:Q3913216): airport in Northwest Territories, Canada
5. Great Bear Lake Drain (wd:Q33194757): canal in Van Buren County, Michigan, United States of America
6. Great Bear Lake Dam (wd:Q34818758): dam in Webster County, Missouri, United States of America
7. Great Bear Lake 16 (wd:Q22424486): First Nation reserve in British Columbia, Canada
8. Great Bear Lake Water Aerodrome (wd:Q3913618): airport in Northwest Territories, Canada
9. Radium Mine, Great Bear Lake (wd:Q59504373): painting by A.Y. Jackson
10. Radium Mine, Great Bear Lake (wd:Q59552554): painting by A.Y. Jackson (NGA Canada 4542r)

[Assistant] I have identified the entities for Lake Baikal (wd:Q5513) and Great Bear Lake (wd:Q5525). Next, I will search for properties related to the size or area of a lake to compare these two lakes.

[Tool]
Top 10 property alternatives:
1. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/p): area occupied by an object
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. drainage basin, also known as watershed, water basin, river basin district, river basin, catchment area (wd:P4614 as wdt/p): area where precipitation collects and drains off into a common outlet, such as into a river, bay, or other body of water, located in/on physical feature
4. watershed area, also known as basin area, catchment basin size, drainage basin size, size of watershed (wd:P2053 as wdt/p): size of a stream's watershed (drainage basin), area
5. 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
6. shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt/p): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.
7. perimeter, also known as boundary length, circumference, coastline (wd:P2547 as wdt/p): linear distance around the outside of an object
8. continent (wd:P30 as wdt/p): continent of which the subject is a part, located in/on physical feature
9. locator map image, also known as locator map, map image, map (wd:P242 as wdt/p): geographic map image which highlights the location of the subject within some larger entity, image
10. 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

No other items found

[Assistant] The property "area" (wdt:P2046) represents the area occupied by an object and is suitable for comparing the sizes of lakes. I will now write a SPARQL query to get the area of Lake Baikal and Great Bear Lake and compare them.

[Tool]
Got 2 rows and 3 columns:
| lake                       | lakeLabel            | area                |
| -------------------------- | -------------------- | ------------------- |
| Lake Baikal (wd:Q5513)     | Lake Baikal (en)     | 31722 (xsd:decimal) |
| Great Bear Lake (wd:Q5525) | Great Bear Lake (en) | 31153 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the area of both Lake Baikal and Great Bear Lake using their Wikidata identifiers and the property for area (wdt:P2046). The answer accurately compares the two areas and concludes that Lake Baikal is bigger. The query also includes English labels for readability, which is helpful. The output is complete, correct, and follows the rules for SPARQL queries. No further refinement is needed.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?country ) AS ?count ) WHERE {
  ?country wdt:P31 wd:Q6256 .
  ?country wdt:P30 wd:Q46 .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 43 (xsd:int) |

There are 43 countries in Europe according to Wikidata.

[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

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] How many countries are there in Europe?

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

[Tool]
Example 1:
Question:
What is the largest country in the world?

SPARQL:
SELECT DISTINCT * WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P2046 ?area .
  ?uri rdfs:label ?label
}
ORDER BY DESC ( ?area )
LIMIT 1

Using entities:
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
Which countries have more than ten volcanoes?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  {
    ?volcano wdt:P31 wd:Q8072 .
  } UNION {
    ?volcano wdt:P31 ?type .
    ?type wdt:P279 * wd:Q8072 .
  }
  ?volcano wdt:P17 ?uri .
}
GROUP BY ?uri
HAVING ( COUNT( ?volcano ) > 10 )

Using entities:
volcano (wd:Q8072): natural, surface vent or fissure usually in a mountainous form

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

Example 3:
Question:
How many people live in Poland?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q36 wdt:P1082 ?uri
}

Using entities:
Poland, also known as Republic of Poland (wd:Q36): country in Central Europe

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject

[Assistant]
From the examples, I see that countries are instances of the class "country" (wd:Q6256) and Europe is a continent (wd:Q46). To find the number of countries in Europe, I need to find entities that are instances of "country" and are located in Europe.

I will now search for the property that indicates the continent or location of a country. This is likely to be "located in the administrative territorial entity" (wdt:P17) or "continent" (wdt:P30). I will check which property is used to indicate that a country is in Europe.

[Tool]
Top 10 property alternatives:
1. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as wdt/p): (list of) direct subdivisions of an administrative territorial entity, has part(s)
2. geoshape, also known as Commons map data, geographic data, geographic shape, .map, map data (wd:P3896 as wdt/p): geographic data from Wikimedia Commons
3. 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).
4. 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)
5. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
6. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
7. OpenStreetMap tag or key, also known as tag, OSM wiki tag or key, OpenStreetMap relation role, OSM tag or key, OSM tag (wd:P1282 as wdt/p): OpenStreetMap tagging schema (a Key:key, Tag:key=value, Relation:type, or Role:role) for classes, properties, and values
8. named after, also known as toponym, namesake, named in honor of, named for, etymology (wd:P138 as wdt/p): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
9. 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)
10. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as wdt/p): main Wikidata property for this item

No other items found

[Tool]
Top 10 property alternatives:
1. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as wdt/p): (list of) direct subdivisions of an administrative territorial entity, has part(s)
2. geoshape, also known as Commons map data, geographic data, geographic shape, .map, map data (wd:P3896 as wdt/p): geographic data from Wikimedia Commons
3. 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)
4. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as wdt/p): main Wikidata property for this item
5. 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)
6. model item, also known as specimen, sample, featured item, example item, best example (wd:P5869 as wdt/p): defines which item is a best practice example of modelling a sub...lue of this property, usage instructions at Wikidata:Model items
7. properties for this type, also known as uses properties, Wikidata properties for this type, Wikidata properties for this class, uses property, things one could say about (wd:P1963 as wdt/p): when this subject is used as object of “instance of”, the following properties normally apply
8. described at URL, also known as mentioned at URL, descURL, described on webpage, discussed at URL, d@url (wd:P973 as wdt/p): item is described at the following URL, URL
9. named after, also known as toponym, namesake, named in honor of, named for, etymology (wd:P138 as wdt/p): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
10. 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).

No other items found

[Tool]
Top 10 property alternatives:
1. continent (wd:P30 as pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/p): continent of which the subject is a part, located in/on physical feature
2. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/p): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
3. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/p): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
4. applies to part, also known as when viewed as, valid for part, section, region, per (wd:P518 as pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/p): part, aspect, or form of the item to which the claim applies
5. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/p): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
6. 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 pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/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
7. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
8. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/p): place where a statement is valid, applies to part
9. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/p): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
10. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pq/pqn/psv/pr/wdt/wdtn/prn/psn/ps/pqv/prv/p): the object is a country that recognizes the subject as its citizen, country

[Assistant]
The property "continent" (wdt:P30) is the appropriate property to indicate the continent to which a country belongs.

I will now write a SPARQL query to count the number of countries (instances of wd:Q6256) that have the continent property set to Europe (wd:Q46).

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 43 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of distinct countries (?country wdt:P31 wd:Q6256) that are located in Europe (?country wdt:P30 wd:Q46). The result of 43 countries matches the answer provided. The query follows the rules by returning the count as a numeric value and uses appropriate entities and properties. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?museum ?museumLabel WHERE {
  wd:Q471379 wdt:P195 ?museum .
  OPTIONAL {
    ?museum rdfs:label ?museumLabel FILTER ( LANG( ?museumLabel ) = "en" )
  }
}

The Scream by Edvard Munch is exhibited at the National Museum of Art, Architecture and Design.

[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

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] Which museum exhibits The Scream by Munch?

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

[Tool]
Example 1:
Question:
Show me all museums in London.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q33506 .
  ?uri wdt:P276 wd:Q84 .
}

Using entities:
museum, also known as museal institution, museum-style institution (wd:Q33506): institution that holds artifacts and other objects of scientific, artistic, cultural, historical, or other importance
London, also known as Loniniensi, Trinovantum, the Big Smoke, Lundenwic, Lundenburh (wd:Q84): capital and largest city of England and the United Kingdom

Using properties:
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
The example shows how to find museums in a specific location using the property "instance of" (P31) for museum (Q33506) and the property "location" (P276) for the location.

Now, I will search for the entity "The Scream" to find its Wikidata identifier.

[Tool]
Top 10 entity alternatives:
1. The Scream, also known as Scream (wd:Q471379): group of paintings by Edvard Munch
2. The Scream (wd:Q1188720): album by Siouxsie and the Banshees
3. De Schreeuw, also known as The Scream (wd:Q920580): sculpture by Jeroen Henneman
4. The Scream (wd:Q1101680): American hard rock band
5. The Scream, also known as Scream (wd:Q4241005): 1993 Azerbaijani war film by Jeyhun Mirzayev
6. The Scream (wd:Q18891158): painting by Edvard Munch (1910)
7. The Scream (wd:Q18891156): painting by Edvard Munch (1893)
8. The Scream (wd:Q18891155): pastel drawing by Edvard Munch (1893)
9. The Scream (wd:Q18891157): pastel by Edvard Munch (1895)
10. The Scream (wd:Q67151412): 2019 short film directed by Francesco Barilli

[Assistant] The Scream by Edvard Munch is represented by several entities, including the group of paintings (wd:Q471379) and specific paintings from different years (e.g., wd:Q18891156 for 1893 painting). I will use the group of paintings entity (wd:Q471379) to find which museum exhibits it. I will search for properties related to exhibition or location for this entity.

[Tool]
Top 10 property alternatives:
1. depicts, also known as portrays, presents, preserves, quotes, represents (wd:P180 as wdt/p): entity visually depicted in an image, literarily described in a ...o an audiovisual or other medium; see also P921,  'main subject', has part(s)
2. 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)
3. 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)
4. collection, also known as editorial collection, series, repository, museum collection, held by (wd:P195 as wdt/p): art, museum, archival, or bibliographic collection of which the subject is part, part of
5. title, also known as name, titled, page name, original title, known as (wd:P1476 as wdt/p): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
6. 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
7. 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).
8. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt/p): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
9. quantity, also known as amount, total number, total, qty, occurrences (wd:P1114 as wdt/p): number of instances of this subject in the universe of the subje...e actual number of instances in Wikidata may be lower or higher)
10. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt/p): maker of this creative work or other object (where no more specific property exists)

No other items found

[Assistant] The property "collection" (wdt:P195) seems to be the most relevant for finding the museum or collection that holds the artwork. I will now query which museums or collections hold "The Scream" (wd:Q471379).

[Tool]
Got 1 row and 2 columns:
| museum                                                        | museumLabel                                          |
| ------------------------------------------------------------- | ---------------------------------------------------- |
| National Museum of Art, Architecture and Design (wd:Q1132918) | National Museum of Art, Architecture and Design (en) |

[Assistant] The Scream by Edvard Munch is exhibited at the National Museum of Art, Architecture and Design. I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the museum that exhibits 'The Scream' by Edvard Munch using the property 'held by' (wdt:P195). It returns the museum's identifier and its English label, which matches the answer provided. The query follows best practices by including the label as an optional clause with a language filter. The answer is accurate and complete based on the query result. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?mayor ?mayorLabel WHERE {
  wd:Q33935 wdt:P6 ?mayor .
  OPTIONAL {
    ?mayor rdfs:label ?mayorLabel FILTER ( LANG( ?mayorLabel ) = "en" )
  }
}

The mayor of Tel Aviv is Ron Huldai.

[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

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 is the mayor of Tel Aviv?

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

[Tool]
Example 1:
Question:
Who is the mayor of Paris?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q90 wdt:P6 ?uri .
}

Using entities:
Paris, also known as City of Love, Lutetia, City of Light (wd:Q90): capital city and largest city of France

Using properties:
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

Example 2:
Question:
To which party does the mayor of Paris belong?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q90 wdt:P6 / wdt:P102 ?uri
}

Using entities:
Paris, also known as City of Love, Lutetia, City of Light (wd:Q90): capital city and largest city of France

Using properties:
member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as wdt): the political party of which a person is or has been a member or otherwise affiliated, member of
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

Example 3:
Question:
Who is the president of Eritrea?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q986 wdt:P35 ?uri
}

Using entities:
Eritrea, also known as er, ERI, Ertrā, IRI, Iritriyā (wd:Q986): country in the Horn of Africa

Using properties:
head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as wdt): official with the highest formal authority in a country/state, director / manager, chairperson

[Assistant]
From the examples, the property "head of government" (wdt:P6) is used to find the mayor or equivalent head of government of a city. Tel Aviv is a city, so we can use the entity for Tel Aviv and query for the head of government using this property.

Next, I will search for the entity for Tel Aviv in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Tel Aviv, also known as Tel Aviv City, TLV, Tel Aviv-Jafo, Tel-Aviv Jaffa, Tel Aviv-Jaffa (wd:Q33935): city in Israel
2. Telefon Tel Aviv (wd:Q768658): American band
3. Tel Aviv (wd:Q15755268): journal
4. Tel Aviv (wd:Q6583053): Israeli painter, painter
5. Tel Aviv (wd:Q16131234): song by Omer Adam
6. Tel Aviv (wd:Q91946708): photograph by Liselotte Grschebina 343498
7. Tel Aviv (wd:Q91939097): visual artwork by Liselotte Grschebina 343450
8. Tel Aviv (wd:Q91932450): photograph by Liselotte Grschebina 343501
9. Tel Aviv (wd:Q76626599): photograph by Liselotte Grschebina
10. Tel Aviv (wd:Q103969725): encyclopedia article

[Assistant]
The entity for Tel Aviv as a city in Israel is wd:Q33935. Based on the example for Paris, we can query for the head of government (property wdt:P6) of Tel Aviv (wd:Q33935) to find the mayor.

I will now construct and execute the SPARQL query to find the mayor of Tel Aviv.

[Tool]
Got 1 row and 2 columns:
| mayor                   | mayorLabel      |
| ----------------------- | --------------- |
| Ron Huldai (wd:Q114760) | Ron Huldai (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the mayor of Tel Aviv using the property 'head of government' (wdt:P6) for the entity Tel Aviv (wd:Q33935). The query also optionally fetches the English label of the mayor. The execution result shows the correct mayor, Ron Huldai, which matches the answer provided. The query follows the rules by returning the identifier and label, and the answer is accurate and complete.