PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?date WHERE {
  wd:Q33132 wdt:P585 ?date .
}

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-sebastian

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

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

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

[User] When was the Battle of Gettysburg?

[Assistant] To answer the question about when the Battle of Gettysburg took place, I need to identify the entity for the Battle of Gettysburg and then find the property that indicates the date or time period of the event. Let's start by searching for the entity representing the Battle of Gettysburg.

[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

No other items found

[Assistant] The top result for the Battle of Gettysburg is `wd:Q33132`, which is described as the 1863 battle of the American Civil War. This is the entity we are looking for. Next, I will search for the property that indicates the date or time period of the event.

[Tool]
Top 10 property alternatives:
1. point in time, also known as at time, as of, year, when, time of event (wd:P585 as p/wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
2. start time, also known as start date, since, valid, join time, joined (wd:P580 as p/wdt): time an entity begins to exist or a statement starts being valid, point in time
3. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as p/wdt): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
4. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/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
5. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
6. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as p/wdtn/wdt): identifier from an international authority file of names, subjects, and organizations
7. participant, also known as suspect, player, party, participants, has participant (wd:P710 as p/wdt): person, group of people or organization (object) that actively t...ct has role" (P3831). Use P1923 for participants that are teams., significant person
8. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
9. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The top result for the property indicating the date or time period of the event is `wdt:P585` (point in time). This property is used to indicate the date when something took place. Now, I will construct a SPARQL query to retrieve the date of the Battle of Gettysburg using this property.

Let's execute the SPARQL query:

```sparql
SELECT ?date
WHERE {
  wd:Q33132 wdt:P585 ?date .
}
```

This query will return the date of the Battle of Gettysburg.

[Tool]
Got 1 row and 1 column:
| ?date                |
| -------------------- |
| 1863-07-01T00:00:00Z |

[Assistant]
The SPARQL query returned the date of the Battle of Gettysburg as `1863-07-01T00:00:00Z`. This indicates that the Battle of Gettysburg started on July 1, 1863.

Therefore, the answer to the question "When was the Battle of Gettysburg?" is July 1, 1863.

I will now provide the final SPARQL query and answer.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?book ?bookLabel WHERE {
  ?book wdt:P31 wd:Q571 ; p:P50 [ ps:P50 wd:Q72653 ] .
  OPTIONAL {
    ?book rdfs:label ?bookLabel .
    FILTER ( LANG( ?bookLabel ) = 'en' )
  }
}

Despite multiple attempts, no results were returned for books written by Danielle Steel. The data structure or availability might be different from what we expected.

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

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

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

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

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

[User] Give me all books written by Danielle Steel.

[Assistant] To answer this question, I need to identify the entity for Danielle Steel and the property that links her to the books she has written. Let's start by searching for Danielle Steel as a subject.

[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

No other items found

[Assistant] The top result for "Danielle Steel" is the correct entity (wd:Q72653). Now, I need to find the property that links Danielle Steel to the books she has written. This is likely to be something like "author of" or "work by". I'll search for properties where Danielle Steel is the subject and the object is a book.

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
3. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
4. Penguin Random House author ID, also known as Penguin Random House author identifier (wd:P9802 as p/wdt): identifier for an author on the Penguin Random House website
5. pseudonym, also known as nom de plume, nom-de-plume, nome de guerre, pen name, ring name (wd:P742 as p/wdt): alias used by someone (for nickname use P1449), name
6. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
7. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as p/wdt): language in which the writer has written their work, languages spoken, written or signed
8. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
9. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
10. LibraryThing author ID, also known as Library Thing author ID, LT author ID (wd:P7400 as p/wdt): identifier for an author on the LibraryThing website

No other items found

[Assistant]
None of the properties listed seem to directly link Danielle Steel to the books she has written. However, the property "described by source" (wd:P1343) might be relevant, as it could link her to works that describe her, which might include her books. Another possibility is that the property "author of" is not directly linked but is part of a more complex relationship.

Let's try a different approach by listing the triples where Danielle Steel is the subject to see if we can find any properties that link her to her books.

[Tool]
Got 502 rows and 3 columns, showing the first 10 rows below:
| subject                    | property                         | object                                                    |
| -------------------------- | -------------------------------- | --------------------------------------------------------- |
| Danielle Steel (wd:Q72653) | instance of (wdt:P31)            | human (wd:Q5)                                             |
| Danielle Steel (wd:Q72653) | occupation (wdt:P106)            | writer (wd:Q36180)                                        |
| Danielle Steel (wd:Q72653) | sex or gender (wdt:P21)          | female (wd:Q6581072)                                      |
| Danielle Steel (wd:Q72653) | given name (wdt:P735)            | Danielle (wd:Q18040452)                                   |
| Danielle Steel (wd:Q72653) | date of birth (wdt:P569)         | 1947-08-14T00:00:00Z                                      |
| Danielle Steel (wd:Q72653) | Commons category (wdt:P373)      | Danielle Steel                                            |
| Danielle Steel (wd:Q72653) | country of citizenship (wdt:P27) | United States (wd:Q30)                                    |
| Danielle Steel (wd:Q72653) | family name (wdt:P734)           | Steel (wd:Q16883818)                                      |
| Danielle Steel (wd:Q72653) | place of birth (wdt:P19)         | New York City (wd:Q60)                                    |
| Danielle Steel (wd:Q72653) | educated at (wdt:P69)            | New York University Tisch School of the Arts (wd:Q797078) |
| ...                        | ...                              | ...                                                       |

[Assistant]
From the list of triples, it appears that there is no direct property linking Danielle Steel to the books she has written. However, we can try to find the books by looking for statements where Danielle Steel is the author. The property "author" (wdt:P50) is commonly used to link authors to their works. Let's check if this property is used for Danielle Steel.

I will execute a SPARQL query to find all books where Danielle Steel is listed as the author.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the property `wdt:P50` (author) is not directly linking Danielle Steel to her books. This suggests that the relationship might be more complex, or the data might be structured differently.

Let's try another approach. We can search for properties that might link Danielle Steel to her works, such as "work by" or "created by". We can also look for properties that might link books to their authors.

I will search for properties where the object is a book and the subject is Danielle Steel.

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as p/wdt): location where persons or organisations were actively participating in employment, business or other work, significant place, location
3. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as p/wdt): specialization of a person or organization; see P106 for the occupation, interested in
4. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as p/wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
5. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as p/wdt): language in which the writer has written their work, languages spoken, written or signed
6. Open Library ID, also known as Open Library book ID, OpenLibrary work ID, Open Library work ID, OpenLibrary identifier, Open Library identifier (wd:P648 as p/wdtn/wdt): identifier for a work ("W"), edition ("M") or author ("A") for book data of the Internet Archive
7. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
8. pseudonym, also known as nom de plume, nom-de-plume, nome de guerre, pen name, ring name (wd:P742 as p/wdt): alias used by someone (for nickname use P1449), name
9. signature, also known as signature image, image of signature, facsimiles, autograph (wd:P109 as p/wdt): image of a person's signature, image
10. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant]
None of the properties listed seem to directly link Danielle Steel to the books she has written. However, the property "work by" (wdt:P178) is often used to link a creator to their works. Let's try using this property to find the books written by Danielle Steel.

I will execute a SPARQL query to find all books where Danielle Steel is listed as the creator using the property `wdt:P178`.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the property `wdt:P178` (work by) is also not being used to link Danielle Steel to her books. Given this, let's try a more general approach by searching for books that are instances of the class "book" (wd:Q571) and then checking if Danielle Steel is listed as the author using the property `wdt:P50`.

I will execute a SPARQL query to find all books where Danielle Steel is listed as the author using the property `wdt:P50` and ensuring that the object is an instance of a book.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that even the more general approach did not yield any results. This suggests that the data structure for linking Danielle Steel to her books might be more complex or different from what we expected.

Given the lack of direct links, let's try a different strategy. We can search for books that are instances of the class "book" (wd:Q571) and then check if Danielle Steel is listed as the author using the property `wdt:P50` in a broader context. We can also include additional properties to ensure we are capturing all relevant information.

I will execute a more comprehensive SPARQL query to find all books where Danielle Steel is listed as the author, including any additional properties that might help us identify the books correctly.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that even the more comprehensive query did not yield any results. This suggests that the data structure for linking Danielle Steel to her books might be different from what we expected, or the data might not be available in the way we are querying it.

Given the lack of success, let's try a different approach. We can search for books that are instances of the class "book" (wd:Q571) and then check if Danielle Steel is listed as the author using the property `wdt:P50` in a broader context, including any qualifiers or references that might be used.

I will execute a more detailed SPARQL query to find all books where Danielle Steel is listed as the author, including any qualifiers or references that might help us identify the books correctly.

[Tool] Got no rows and 2 columns

[Assistant]
Despite multiple attempts, it seems that the data for linking Danielle Steel to her books is either not present in the expected format or not available in the Wikidata knowledge graph. This could be due to the data being structured differently or not being fully populated.

Given the lack of success, I will provide my best attempt at a SPARQL query and explain why I could not find a satisfactory answer.

### Best Attempt at SPARQL Query
```sparql
SELECT ?book ?bookLabel WHERE {
  ?book wdt:P31 wd:Q571 ;
        p:P50 [ ps:P50 wd:Q72653 ] .
  OPTIONAL { ?book rdfs:label ?bookLabel . FILTER(LANG(?bookLabel) = 'en') }
}
```

### Explanation
1. **Entity Identification**: I correctly identified Danielle Steel as `wd:Q72653`.
2. **Property Identification**: I tried various properties such as `wdt:P50` (author), `wdt:P178` (work by), and `wdt:P1343` (described by source) to link Danielle Steel to her books.
3. **Query Attempts**: I attempted multiple SPARQL queries to find books where Danielle Steel is listed as the author, including more comprehensive and detailed queries.
4. **No Results**: Despite these efforts, no results were returned, suggesting that the data might not be structured as expected or might not be available in the Wikidata knowledge graph.

### Conclusion
I am unable to find a satisfactory SPARQL query that returns the books written by Danielle Steel. The data structure or availability might be different from what we expected.

If you have any additional information or constraints, please let me know, and I can try again.

### Best Attempt
```json
{
  "explanation": "Despite multiple attempts, no results were returned for books written by Danielle Steel. The data structure or availability might be different from what we expected.",
  "best_attempt": {
    "sparql": "SELECT ?book ?bookLabel WHERE { ?book wdt:P31 wd:Q571 ; p:P50 [ ps:P50 wd:Q72653 ] . OPTIONAL { ?book rdfs:label ?bookLabel . FILTER(LANG(?bookLabel) = 'en') } }",
    "kg": "wikidata"
  }
}
```

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?daughter ?spouse WHERE {
  wd:Q25310 wdt:P40 ?daughter .
  ?daughter wdt:P21 wd:Q6581072 .
  ?daughter wdt:P26 ?spouse
}

Got 5 rows and 2 columns:
| ?daughter                              | ?spouse                            |
| -------------------------------------- | ---------------------------------- |
| Rory Kennedy (wd:Q273833)              | Mark Bailey (wd:Q29938796)         |
| Kathleen Kennedy Townsend (wd:Q467861) | David Lee Townsend (wd:Q75326812)  |
| Kerry Kennedy (wd:Q467912)             | Andrew Cuomo (wd:Q11673)           |
| Courtney Kennedy Hill (wd:Q5178632)    | Paul Hill (wd:Q15133215)           |
| Courtney Kennedy Hill (wd:Q5178632)    | Jeffrey Robert Ruhe (wd:Q75326831) |

Rory Kennedy is married to Mark Bailey, Kathleen Kennedy Townsend is married to David Lee Townsend, Kerry Kennedy is married to Andrew Cuomo, and Courtney Kennedy Hill is married to Paul Hill and Jeffrey Robert Ruhe.

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

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

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

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

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

[User] Who is the daughter of Robert Kennedy married to?

[Assistant] To answer this question, we need to identify the daughter of Robert Kennedy and then find out who she is married to. Let's start by searching for Robert Kennedy in the knowledge graph.

[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

No other items found

[Assistant] The top result is Robert F. Kennedy, who is the prominent United States politician. We will use this entity to find his daughter. Let's search for the property that indicates a parent-child relationship.

[Tool]
Top 10 property alternatives:
1. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
2. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as p/wdt): female parent of the subject. For stepmother, use "stepparent" (P3448), parent
3. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as p/wdt): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
4. sibling, also known as is sister of, is the brother of, is the sibling of, is the sister of, sib (wd:P3373 as p/wdt): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), relative
5. family, also known as royal house, noble family, member of family, house, dynasty (wd:P53 as p/wdt): family, including dynasty and nobility houses. Not family name (use P734 for family name)., member of
6. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

No other items found

[Assistant] The property `child` (P40) seems to be the most appropriate for finding Robert F. Kennedy's children. Let's use this property to find his daughters.

[Tool]
Got 4 rows and 1 column:
| ?daughter                              |
| -------------------------------------- |
| Rory Kennedy (wd:Q273833)              |
| Kathleen Kennedy Townsend (wd:Q467861) |
| Kerry Kennedy (wd:Q467912)             |
| Courtney Kennedy Hill (wd:Q5178632)    |

[Assistant] We have identified Robert F. Kennedy's daughters. Now, let's find out who each of these daughters is married to. We will use the property `spouse` (P26) to find this information.

[Tool]
Got 5 rows and 2 columns:
| ?daughter                              | ?spouse                            |
| -------------------------------------- | ---------------------------------- |
| Rory Kennedy (wd:Q273833)              | Mark Bailey (wd:Q29938796)         |
| Kathleen Kennedy Townsend (wd:Q467861) | David Lee Townsend (wd:Q75326812)  |
| Kerry Kennedy (wd:Q467912)             | Andrew Cuomo (wd:Q11673)           |
| Courtney Kennedy Hill (wd:Q5178632)    | Paul Hill (wd:Q15133215)           |
| Courtney Kennedy Hill (wd:Q5178632)    | Jeffrey Robert Ruhe (wd:Q75326831) |

[Assistant]
We have found the spouses of Robert F. Kennedy's daughters. Here are the results:

- Rory Kennedy is married to Mark Bailey.
- Kathleen Kennedy Townsend is married to David Lee Townsend.
- Kerry Kennedy is married to Andrew Cuomo.
- Courtney Kennedy Hill is married to Paul Hill and Jeffrey Robert Ruhe.

Since the question asks specifically about the daughter of Robert Kennedy, we need to provide the answer for one of them. Let's choose the first daughter listed, Rory Kennedy, as the primary answer.

Here is the final SPARQL query and answer:

```sparql
SELECT ?daughter ?spouse WHERE {
  wd:Q25310 wdt:P40 ?daughter .
  ?daughter wdt:P21 wd:Q6581072 .
  ?daughter wdt:P26 ?spouse
}
```

Answer: Rory Kennedy is married to Mark Bailey.

However, since the question does not specify which daughter, we can provide a more comprehensive answer:

Rory Kennedy is married to Mark Bailey, Kathleen Kennedy Townsend is married to David Lee Townsend, Kerry Kennedy is married to Andrew Cuomo, and Courtney Kennedy Hill is married to Paul Hill and Jeffrey Robert Ruhe.

Let's finalize this with the answer function.

[Tool] Stopped generation process


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

Got 1 row and 2 columns:
| ?lyricist                  | ?lyricistLabel |
| -------------------------- | -------------- |
| Józef Wybicki (wd:Q370069) | Józef Wybicki  |

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-sebastian

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

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

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

[User] Who wrote the lyrics for the Polish national anthem?

[Assistant] To find out who wrote the lyrics for the Polish national anthem, I need to identify the entity for the Polish national anthem and then find the property that links it to the lyricist. Let's start by searching for the Polish national anthem.

[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

No other items found

[Assistant] The top result is "Poland Is Not Yet Lost, also known as Dąbrowski's Mazurka, Polish national anthem, Song of the Polish Legions in Italy" (wd:Q482988), which seems to be the correct entity for the Polish national anthem. Now, I will look for the property that links this entity to the lyricist.

[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 p/wdt): author of song lyrics, author
2. first line, also known as incipit, opening line, fl, first verse, first sentence (wd:P1922 as p/wdt): 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 p/wdt): 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 p/wdt): 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 wdtn/p/wdt): 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 p/wdt): 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 p/wdt): key of a musical composition
8. author, also known as writer, written by, poet, playwright, maker (wd:P50 as p/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
9. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): 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 p/wdt): 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 top result for the property is "lyricist" (wd:P676), which is the property that links the Polish national anthem to its lyricist. Now, I will construct a SPARQL query to find the lyricist of the Polish national anthem.

Let's execute the query:

```sparql
SELECT ?lyricist ?lyricistLabel
WHERE {
  wd:Q482988 wdt:P676 ?lyricist.
  OPTIONAL { ?lyricist rdfs:label ?lyricistLabel . FILTER(LANG(?lyricistLabel) = "en") }
}
```

This query will return the IRI of the lyricist and, if available, the English label of the lyricist.

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

[Assistant]
The lyricist of the Polish national anthem, "Poland Is Not Yet Lost," is Józef Wybicki (wd:Q370069).

Here is the final SPARQL query and answer:

```sparql
SELECT ?lyricist ?lyricistLabel
WHERE {
  wd:Q482988 wdt:P676 ?lyricist.
  OPTIONAL { ?lyricist rdfs:label ?lyricistLabel . FILTER(LANG(?lyricistLabel) = "en") }
}
```

Answer: Józef Wybicki

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
ASK WHERE {
  wd:Q810986 wdt:P31 wd:Q7889
}

True

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

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

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

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

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

[User] Is there a video game called Battle Chess?

[Assistant]
To determine if there is a video game called Battle Chess, I will first search for the subject "Battle Chess" in the Wikidata knowledge graph. If it exists, I will then check if it has the property "instance of" (P31) with the object "video game" (Q7889).

Let's start by searching for the subject "Battle Chess".

[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

No other items found

[Assistant]
I found several entries related to "Battle Chess". The first result, `wd:Q810986`, seems to be the most relevant as it is described as a 1988 chess-playing video game. To confirm that this is indeed a video game, I will check if it has the property "instance of" (P31) with the object "video game" (Q7889).

Let's execute a SPARQL query to verify this.

[Tool] True

[Assistant]
The SPARQL query confirms that `wd:Q810986` is indeed an instance of a video game. Therefore, there is a video game called Battle Chess.

Here is the final SPARQL query and answer:

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
ASK WHERE {
  wd:Q5513 wdt:P2046 ?baikalArea .
  wd:Q5525 wdt:P2046 ?greatBearArea .
  FILTER ( ?baikalArea > ?greatBearArea )
}

True

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

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

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

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

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

[User] Is Lake Baikal bigger than the Great Bear Lake?

[Assistant] To determine if Lake Baikal is bigger than the Great Bear Lake, we need to compare their sizes. We will first identify the entities for Lake Baikal and the Great Bear Lake, and then find the relevant property for their size (likely surface area or volume). Finally, we will construct a SPARQL query to compare these values.

[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

No other items found

[Assistant]
The top result for "Lake Baikal" is `wd:Q5513`, which is the freshwater rift lake in southern Siberia, Russia. This is the entity we are looking for.

Next, let's find the entity for the Great Bear Lake.

[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)

No other items found

[Assistant]
The top result for "Great Bear Lake" is `wd:Q5525`, which is the large glacial lake in the Northwest Territories, Canada. This is the entity we are looking for.

Now, we need to find the property that represents the size of these lakes. Common properties for size include surface area and volume. Let's search for these properties.

[Tool]
Top 10 property alternatives:
1. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as p/wdt): area occupied by an object
2. perimeter, also known as boundary length, circumference, coastline (wd:P2547 as p/wdt): linear distance around the outside of an object
3. volume as quantity, also known as tonnage, volume (geometry), vaq, spatial volume, quantity as volume (wd:P2234 as p/wdt): quantity of three-dimensional space
4. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. width, also known as breadth, bus width, size (wd:P2049 as p/wdt): width of an object, length
6. length, also known as size, long, LOA, distance, dimension (wd:P2043 as p/wdt): measured dimension of an object
7. watershed area, also known as basin area, catchment basin size, drainage basin size, size of watershed (wd:P2053 as p/wdt): size of a stream's watershed (drainage basin), area
8. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
9. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
10. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as p/wdt): height of the item (geographical object) as measured relative to sea level

No other items found

[Assistant]
The property `wd:P2046` (area) is the most relevant for the surface area of a lake. Let's confirm this property for both Lake Baikal and the Great Bear Lake.

We will now construct a SPARQL query to retrieve the surface areas of both lakes and compare them.

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

[Assistant]
The surface area of Lake Baikal is 31,722 square kilometers, and the surface area of the Great Bear Lake is 31,153 square kilometers. Therefore, Lake Baikal is indeed larger than the Great Bear Lake.

Here is the final SPARQL query and answer:

```sparql
ASK WHERE {
  wd:Q5513 wdt:P2046 ?baikalArea .
  wd:Q5525 wdt:P2046 ?greatBearArea .
  FILTER(?baikalArea > ?greatBearArea)
}
```

The answer to the question is "True".

[Tool] Stopped generation process


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

Got 1 row and 1 column:
| ?count |
| ------ |
| 43     |

There are 43 countries in Europe.

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

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

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

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

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

[User] How many countries are there in Europe?

[Assistant]
To answer the question "How many countries are there in Europe?", we need to identify the entity representing Europe and the property that links countries to their continent. We can then count the number of distinct countries linked to Europe through this property.

First, let's search for the entity representing Europe.

[Tool]
Top 10 entity alternatives:
1. Europe, also known as European continent, The Old Continent, Old Continent, European Continent, European Peninsula (wd:Q46): continent in the Northern Hemisphere
2. European Union, also known as E.U., Europe, eu (wd:Q458): political and economic union of 27 European states
3. Europa, also known as Europe, Evropa (wd:Q165170): Phoenician character in Greek mythology, daughter of Agenor
4. Europe (wd:Q185144): Swedish rock band
5. Europe (wd:Q579160): National anthem of Kosovo
6. Europe (wd:Q766618): Paris Métro station
7. Europe (wd:Q1163173): international racing sailing class
8. Europe (wd:Q198697): 1983 debut studio album by Europe
9. James Reese Europe, also known as Jim Europe, James R. Europe, James R. Europe, Sr., Lieut. Jim Europe, James Europe (wd:Q1280917): American jazz musician and United States Army officer (1880-1919), jazz musician, mandolinist, bandleader, conductor, composer, pianist
10. Europe (wd:Q612228): French magazine

No other items found

[Assistant] The top result for "Europe" is the continent Europe (wd:Q46). Next, we need to find the property that links countries to their continent. Let's search for this property.

[Tool]
Top 10 property alternatives:
1. continent (wd:P30 as ps/pq/wdt): 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 ps/pq/wdt): 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 ps/pq/wdt): 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 ps/pq/wdt): 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 pr/ps/pq/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
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 ps/pq/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
7. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as ps/pq/wdt): place where a statement is valid, applies to part
8. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as ps/pq/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
9. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as ps): the object is a country that recognizes the subject as its citizen, country
10. country, also known as sovereign state, state, land, host country (wd:P17 as ps/pq/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

No other items found

[Assistant]
The property that links countries to their continent is `continent` (wd:P30). Now, we can construct a SPARQL query to count the number of distinct countries that have Europe (wd:Q46) as their continent.

Let's write and execute this query.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 30821  |

[Assistant]
The result of the query indicates that there are 30,821 items that are linked to Europe (wd:Q46) through the `continent` (wd:P30) property. However, this number seems unusually high for the number of countries in Europe. It's possible that the property `continent` (wd:P30) is used for more than just countries.

To refine our query, we should filter the results to include only those items that are classified as countries. We can use the property `instance of` (wd:P31) to check if the items are instances of a country (wd:Q6256).

Let's update the query to include this filter.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 43     |

[Assistant]
The refined query returns 43 distinct countries that are linked to Europe (wd:Q46) through the `continent` (wd:P30) property and are instances of a country (wd:Q6256).

Therefore, the number of countries in Europe is 43.

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(DISTINCT ?country) AS ?count)
WHERE {
  ?country wdt:P30 wd:Q46 ;
  wdt:P31 wd:Q6256 .
}
```

Answer: There are 43 countries in Europe.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process


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

The museum that exhibits 'The Scream' by Edvard Munch is 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-sebastian

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

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

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

[User] Which museum exhibits The Scream by Munch?

[Assistant]
To answer the question about which museum exhibits "The Scream" by Munch, we need to identify the following entities and properties:
1. The painting "The Scream" by Edvard Munch.
2. The property that links a painting to the museum where it is exhibited.
3. The museum that exhibits "The Scream."

Let's start by searching for the entity representing "The Scream" by Edvard Munch.

[Tool]
Top 10 entity alternatives:
1. Edvard Munch: The Scream (wd:Q110953479): October 24 2012-April 29 2013 exhibition at Museum of Modern Art
2. Munch and The Scream (wd:Q87282890): episode of In Our Time
3. [Atmosphere, The scream and Edvard Munch] (wd:Q57128356): scientific article published on 01 January 2014
4. Munch's "The Scream" might have been burned (wd:Q18621392): Wikinews article
5. Edvard Munch's The Scream and Madonna found (wd:Q18016696): Wikinews article
6. The Scream, also known as Scream (wd:Q471379): group of paintings by Edvard Munch
7. Darryl Jones, also known as The Munch (wd:Q463695): American bassist, jazz musician, bassist
8. The Scream (wd:Q1188720): album by Siouxsie and the Banshees
9. De Schreeuw, also known as The Scream (wd:Q920580): sculpture by Jeroen Henneman
10. The Scream (wd:Q1101680): American hard rock band

No other items found

[Assistant]
From the search results, the most relevant entity for "The Scream" by Edvard Munch is `wd:Q471379`, which represents the group of paintings by Edvard Munch.

Next, we need to find the property that links a painting to the museum where it is exhibited. We can search for properties related to "museum" or "exhibition" and constrain the search to the subject `wd:Q471379`.

[Tool]
Top 10 property alternatives:
1. collection, also known as editorial collection, series, repository, museum collection, held by (wd:P195 as p/wdt): art, museum, archival, or bibliographic collection of which the subject is part, part of
2. National Museum Norway artwork ID, also known as National Museum Norway ID, National Museum Norway work ID (wd:P9121 as p): identifier for an artwork in the Norwegian National Museum collections
3. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/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
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. depicts, also known as portrays, presents, preserves, quotes, represents (wd:P180 as p/wdt): entity visually depicted in an image, literarily described in a ...o an audiovisual or other medium; see also P921,  'main subject', has part(s)
6. movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as p/wdt): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.
7. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as p/wdt): maker of this creative work or other object (where no more specific property exists)
8. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
9. on focus list of Wikimedia project, also known as WikiProject, Wikimedia project focus list, part of Wikimedia project, item created or edited for Wikimedia project, item created or edited as part of Wikimedia project (wd:P5008 as p/wdt): property to indicate that an item is of particular interest for ... they are not notable for Wikidata. See also P6104, P972, P2354.
10. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant]
From the search results, the most relevant property for linking a painting to the museum where it is exhibited is `wdt:P195`, which stands for "collection" or "held by." This property indicates the art, museum, archival, or bibliographic collection of which the subject is a part.

Now, let's construct a SPARQL query to find the museum that exhibits "The Scream" by Edvard Munch using the identified property.

```sparql
SELECT ?museum ?museumLabel
WHERE {
  wd:Q471379 wdt:P195 ?museum.
  OPTIONAL { ?museum rdfs:label ?museumLabel. FILTER(LANG(?museumLabel) = "en") }
}
```

This query will return the museum that holds "The Scream" and optionally its English label.

Let's execute this query to get the result.

[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 |

[Assistant]
The SPARQL query has returned the museum that exhibits "The Scream" by Edvard Munch. The museum is the National Museum of Art, Architecture and Design.

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

```sparql
SELECT ?museum ?museumLabel
WHERE {
  wd:Q471379 wdt:P195 ?museum.
  OPTIONAL { ?museum rdfs:label ?museumLabel. FILTER(LANG(?museumLabel) = "en") }
}
```

Answer: The museum that exhibits "The Scream" by Edvard Munch is the National Museum of Art, Architecture and Design.

Let's finalize this with the answer function.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?mayor WHERE {
  wd:Q33935 wdt:P6 ?mayor .
}

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-sebastian

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

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

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

[User] Who is the mayor of Tel Aviv?

[Assistant] To find out who the current mayor of Tel Aviv is, we need to identify the entity for Tel Aviv and then find the property that indicates the mayor. Let's start by searching for the entity representing Tel Aviv.

[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

No other items found

[Assistant] The top result for "Tel Aviv" is the city in Israel, which is represented by the entity `wd:Q33935`. Now, let's find the property that indicates the mayor of a city. We can search for properties related to "mayor" and see if any of them are used with Tel Aviv.

[Tool]
Top 10 property alternatives:
1. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as p/wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
2. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
3. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as p/wdt): political office that is fulfilled by the head of the government of this item
4. capital of, also known as national capital of, parish seat of, provincial capital of, seat of, state capital (wd:P1376 as p/wdt): country, state, department, canton or other administrative division of which the municipality is the governmental seat, located in the administrative territorial entity
5. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
6. twinned administrative body, also known as twin cities, twin town, twin city, sister town, sister city (wd:P190 as p/wdt): twin towns, sister cities, twinned municipalities and other loca..., either legally or informally acknowledged by their governments
7. population, also known as inhabitants, human population (wd:P1082 as p/wdt): number of people inhabiting the place; number of people of subject
8. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
9. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as p/wdt): official name of the subject in its official language(s), name
10. category for honorary citizens of entity, also known as honorary citizens category (wd:P10280 as p/wdt): category containing the honorary citizens of a settlement (admin...ry). Honorary citizens may or may not be citizens of the country, related category

No other items found

[Assistant]
The property `wd:P6` (head of government) seems to be the most relevant for indicating the mayor of a city. Let's use this property to find the current mayor of Tel Aviv.

I will now construct a SPARQL query to retrieve the mayor of Tel Aviv.

```sparql
SELECT ?mayor WHERE {
  wd:Q33935 wdt:P6 ?mayor .
}
```

Let's execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| ?mayor                  |
| ----------------------- |
| Ron Huldai (wd:Q114760) |

[Assistant]
The current mayor of Tel Aviv is Ron Huldai, represented by the entity `wd:Q114760`.

Here is the final SPARQL query and answer:

```sparql
SELECT ?mayor WHERE {
  wd:Q33935 wdt:P6 ?mayor .
}
```

The mayor of Tel Aviv is Ron Huldai.

[Tool] Stopped generation process