PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?song ) AS ?count ) WHERE {
  ?song wdt:P86 wd:Q238819 .
  FILTER NOT EXISTS {
    ?song wdt:P1433 ?album .
    ?album wdt:P175 wd:Q238819
  }
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 7 (xsd:int) |

[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 songs were composed by Jay Chou but not released in his own albums?

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

[Tool]
Example 1:
Question:
How high is the Yokohama Marine Tower?

SPARQL:
SELECT DISTINCT ?num WHERE {
  wd:Q1207989 wdt:P2048 ?num .
}

Using entities:
Yokohama Marine Tower (wd:Q1207989): lighthouse in Japan

Using properties:
height, also known as heighth, size, depth over terrain (wd:P2048 as wdt): vertical length of an entity, length

Example 2:
Question:
What was the last movie with Alec Guinness?

SPARQL:
SELECT DISTINCT ?s1 WHERE {
  ?s1 wdt:P31 wd:Q11424 .
  ?s1 wdt:P161 wd:Q103894 .
  ?s1 wdt:P577 ?o1 .
}
order by DESC ( ?o1 )
limit 1

Using entities:
Alec Guinness, also known as Alec Guinness de Cuffe, Sir Alec Guinness (wd:Q103894): British actor (1914–2000), television actor, character actor, autobiographer, screenwriter, stage actor, film actor, actor
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

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

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

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

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt): subject currently or formerly holds the object position or public office

[Assistant] From the examples, we can see how to structure a SPARQL query to find specific information about entities and their relationships. For our question, we need to identify the entity for Jay Chou and the properties for songs, composers, and albums. Let's start by searching for Jay Chou.

[Tool]
Top 10 entity alternatives:
1. Jay Chou, also known as President Chou, Zhou Jielun, Chou Chieh-lun (wd:Q238819): Taiwanese pop singer, songwriter, and actor, recording artist, record producer, film director, songwriter, composer, director, rapper, singer, actor
2. Jayanta Choudhury (wd:Q102339960): Ph.D. University of Louisiana at Lafayette 2008
3. Jaya Choudhary (wd:Q88317282): researcher
4. Jayadratha Choudhury (wd:Q107562664): Indian Odia-language writer, writer
5. Jay Chou's Bedtime Stories (wd:Q24595331): 2016 studio album by Jay Chou
6. Jayanta Narayan Choudhury, also known as Jayanto Narayan Choudhury (wd:Q110437452): Indian police officer
7. Choudhury Jayprakash Das, also known as Choudhury Jayaprakash Das, Caudhurī Jaẏaprakāśa Dāsa (wd:Q60511536): Indian actor and academic, film actor, teacher, actor
8. Jay Chou 2007 World Tour Concert Live (wd:Q1100149): live album
9. J, also known as ᴊ, Juliett, Juliet, j, jay (wd:Q9773): 10th-17th letter of Latin alphabets
10. Eurasian Jay, also known as Garrulus glandarius, Jay, European Jay (wd:Q25354): species of bird

[Assistant] The correct entity for Jay Chou is `wd:Q238819`. Next, we need to find the properties for songs, composers, and albums. We'll start by searching for the property related to composers.

[Tool]
Top 10 property alternatives:
1. composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): time when an entity begins to exist; for date of official opening use P1619, start time
3. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): author of song lyrics, author
4. composers.am person ID (wd:P9628 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a person in the  site of Composers Union of Armenia
5. music created for, also known as music for, music for work, music made for, music made for work, music written for (wd:P9899 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): a work, event, etc. for which a musical composition was created ... was written; a film for which motion picture music was created), created for
6. location of creation, also known as manufactured in, manufacturing location, mint, minted at, photographed at (wd:P1071 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): place where the item was conceived or made; where applicable, location of final assembly, significant place
7. Musicsperlacobla composer ID (wd:P11203 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): composer identifier used by musicsperlacobla archive
8. orchestrator, also known as arranged for orchestra by, orchestral arrangement by, orchestral arranger, orchestration by, orchestrations by (wd:P10806 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person or body responsible for arranging a musical composition for orchestra, adapted by
9. Musicalics composer ID (wd:P6925 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a composer in the Musicalics database
10. CompositionToday composer ID, also known as Composition Today composer ID (wd:P8688 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): composer ID on the website CompositionToday

[Assistant] The property for composer is `wd:P86`. Now, let's find the property for albums.

[Tool]
Top 10 property alternatives:
1. published in, also known as song on album, tome of the book, tome of, track of, track on (wd:P1433 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): larger work that a given work was published in, like a book, journal or music album, part of
2. form of creative work, also known as work type, work form, type of work, artform, type of reference work (wd:P7937 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): structure of a creative work
3. featured track(s), also known as songs, soundtrack, OST, music tracks, music track (wd:P10664 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): soundtrack of this audiovisual work
4. tracklist, also known as tracks, track listing, track list, songs, list of tracks (wd:P658 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): audio tracks contained in this release, has part(s)
5. record of, also known as is a record of, is record of, records (wd:P11851 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): state or event an object is a physical representation of
6. number of records, also known as entries, rows, records, quantitiy of records, number of rows (wd:P4876 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): number of values of an identifier or records in a catalog
7. soundtrack release, also known as soundtrack single, soundtrack extended play, soundtrack album, has soundtrack album, OST (wd:P406 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): music release that incorporates music directly recorded from the soundtrack of an audiovisual work
8. music created for, also known as music for, music for work, music made for, music made for work, music written for (wd:P9899 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): a work, event, etc. for which a musical composition was created ... was written; a film for which motion picture music was created), created for
9. personal best, also known as PR, record, personal record, PB (wd:P2415 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): an individual's best performance in a given discipline
10. MusicBrainz release group ID, also known as album MBID, single MBID, single ID (MusicBrainz), release group MBID, release group ID (MusicBrainz) (wd:P436 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a release group per the MusicBrainz open music encyclopedia (album, single, etc.)

[Assistant]
The property for published in (which indicates the album a song is part of) is `wd:P1433`. Now, we can start building our SPARQL query to find songs composed by Jay Chou but not released in his own albums.

First, let's find the songs composed by Jay Chou.

[Tool] Got no rows and 1 columns

[Assistant] It seems that the query did not return any results. This might be because the property `wd:P86` (composer) is used on the song entity to link to the composer, not the other way around. Let's try to find songs where Jay Chou is listed as the composer.

[Tool]
Got 7 rows and 1 column:
| song                                 |
| ------------------------------------ |
| Listen to Mom (wd:Q10918532)         |
| Chinese Herbal Manual (wd:Q11093458) |
| Say Love You (wd:Q114406775)         |
| wd:Q18658355                         |
| The Spirit of Knight (wd:Q45261044)  |
| Secret (wd:Q699749)                  |
| Kung Fu Dunk (wd:Q715295)            |

[Assistant] We have found the songs composed by Jay Chou. Now, we need to filter out the songs that are part of his own albums. To do this, we need to identify Jay Chou's albums. Let's find the albums associated with Jay Chou.

[Tool] Got no rows and 1 columns

[Assistant] It seems that the property `wd:P178` (producer) is not the right one to find Jay Chou's albums. Let's try another approach by searching for the property that links an artist to their albums.

[Tool]
Top 10 property alternatives:
1. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as p/wdt): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
2. 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
3. discography, also known as discography link, recording catalog (wd:P358 as p/wdt): item for list pages with discography of artist or band, list of works
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
6. record label, also known as label, labels (wd:P264 as p/wdt): brand and trademark associated with the marketing of subject music recordings and music videos
7. Apple Music artist ID (U.S. version), also known as iTunes author ID, music.apple.com/artist/, iTunes artist ID (American version), https://music.apple.com/artist/, Apple Music artist ID (American version) (wd:P2850 as p/wdt): identifier for a musical artist or author in the U.S. version of Apple Music
8. 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
9. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
10. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as p/wdt): musical instrument that a person plays or teaches or used in a music occupation, uses

No other items found

[Assistant]
None of these properties directly link Jay Chou to his albums. However, we can try using the property `wd:P178` (producer) again, but this time on the album entities to see if it returns any results. Alternatively, we can use the property `wd:P1433` (published in) to find the albums that the songs are part of and then filter out those that are produced by Jay Chou.

Let's try using `wd:P1433` to find the albums that the songs are part of.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the songs composed by Jay Chou are not directly linked to albums using the `wd:P1433` property. This suggests that we might need to take a different approach. One possible method is to find the albums that Jay Chou has produced and then exclude those albums from the list of songs he composed.

Let's first find the albums that Jay Chou has produced using the `wd:P178` property.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the property `wd:P178` (producer) is not being used to link Jay Chou to his albums. Let's try another approach by finding the albums that Jay Chou is associated with as a primary artist or contributor. We can use the property `wd:P175` (performer) to find albums where Jay Chou is the primary artist.

Let's try this approach.

[Tool]
Got 43 rows and 1 column, showing the first 5 and last 5 rows below:
| album                                               |
| --------------------------------------------------- |
| Dare for More (wd:Q106967725)                       |
| Far Away (wd:Q10904989)                             |
| Listen to Mom (wd:Q10918532)                        |
| Initial J (wd:Q1097148)                             |
| Jay Chou 2007 World Tour Concert Live (wd:Q1100149) |
| ...                                                 |
| Exclamation Mark (wd:Q873560)                       |
| Opus 12 (wd:Q893010)                                |
| wd:Q9507195                                         |
| Mojito (wd:Q97279208)                               |
| THE INVINCIBLE (wd:Q97350176)                       |

[Assistant]
We have found the albums where Jay Chou is the primary artist. Now, we need to filter out the songs composed by Jay Chou that are part of these albums. We will use the `wd:P1433` property to link songs to albums and then exclude the songs that are part of the albums listed above.

Let's build the final SPARQL query to find the songs composed by Jay Chou but not released in his own albums.

[Tool]
Got 7 rows and 1 column:
| song                                 |
| ------------------------------------ |
| Listen to Mom (wd:Q10918532)         |
| Chinese Herbal Manual (wd:Q11093458) |
| Say Love You (wd:Q114406775)         |
| wd:Q18658355                         |
| The Spirit of Knight (wd:Q45261044)  |
| Secret (wd:Q699749)                  |
| Kung Fu Dunk (wd:Q715295)            |

[Assistant]
The SPARQL query has returned the songs composed by Jay Chou but not released in his own albums. Let's count the number of such songs to answer the user's question.

Here is the final SPARQL query to count the number of songs:

```sparql
SELECT (COUNT(?song) AS ?count) WHERE {
  ?song wdt:P86 wd:Q238819 .
  FILTER NOT EXISTS {
    ?song wdt:P1433 ?album .
    ?album wdt:P175 wd:Q238819
  }
}
```

Let's execute this query to get the count.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 7 (xsd:int) |

[Assistant]
The SPARQL query has returned the count of songs composed by Jay Chou but not released in his own albums. The count is 7.

Therefore, the answer to the question "How many songs were composed by Jay Chou but not released in his own albums?" is 7.

Here is the final SPARQL query and the answer:

```sparql
SELECT (COUNT(?song) AS ?count) WHERE {
  ?song wdt:P86 wd:Q238819 .
  FILTER NOT EXISTS {
    ?song wdt:P1433 ?album .
    ?album wdt:P175 wd:Q238819
  }
}
```

Answer: 7

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?work ) AS ?count ) WHERE {
  wd:Q30875 wdt:P800 ?work .
  FILTER ( ?work != wd:Q82464 )
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 4 (xsd:int) |

[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 literary works besides The Picture of Dorian Gray did its author write?

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

[Tool]
Example 1:
Question:
In which military conflicts did Lawrence of Arabia participate?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q170596 wdt:P607 ?o1 .
}

Using entities:
T. E. Lawrence, also known as Thomas Edward Lawrence, T.E. Lawrence, Thomas Edward Shaw, John Hume Ross, Lawrence of Arabia (wd:Q170596): British archaeologist, army officer and diplomat (1888–1935), military personnel, military officer, castellologist, autobiographer, aircraft pilot, world traveler, anthropologist, archaeologist, screenwriter, translator, diplomat, writer, spy

Using properties:
conflict, also known as war, theatre (military), theater (military), participated in conflict, military conflict (wd:P607 as wdt): battles, wars or other military engagements in which the person or item participated, participant in

Example 2:
Question:
Where did Abraham Lincoln die?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q91 wdt:P20 ?uri .
}

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

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

Example 3:
Question:
What is the largest country in the world?

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

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

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

[Assistant] Based on the examples, we need to identify the author of "The Picture of Dorian Gray" and then find out how many other literary works they wrote. Let's start by searching for the entity "The Picture of Dorian Gray".

[Tool]
Top 10 entity alternatives:
1. The Picture of Dorian Gray, also known as El retrato de Dorian Gray, Picture of Dorian Gray (wd:Q82464): 1890–1891 novel by Oscar Wilde
2. The Picture of Dorian Gray, also known as Picture of Dorian Gray (wd:Q1167299): 1945 film by Albert Lewin
3. The Picture of Dorian Gray, also known as Picture of Dorian Gray (wd:Q7757057): 1916 film directed by Fred W. Durrant
4. The Picture of Dorian Gray, also known as Picture of Dorian Gray (wd:Q16979666): 1913 film by Phillips Smalley
5. The Picture of Dorian Gray (wd:Q1397330): telenovela
6. The Picture of Dorian Gray, also known as Picture of Dorian Gray (wd:Q7757058): 1917 film by Richard Oswald
7. The Picture of Dorian Gray, also known as Dorian Grays Portræt, Picture of Dorian Gray (wd:Q15177406): 1910 film by Axel Strøm
8. The Picture of Dorian Gray, also known as Picture of Dorian Gray (wd:Q1167302): 1976 television film
9. The Picture of Dorian Gray, also known as Picture of Dorian Gray (wd:Q17044933): 1915 film directed by Eugene Moore
10. The Picture of Dorian Gray, also known as Picture of Dorian Gray (wd:Q7757059): 1918 Hungarian silent film by Alfréd Deésy

[Assistant] The first result is the correct one, which is the novel "The Picture of Dorian Gray" by Oscar Wilde. Now, let's find the author of this work.

[Tool]
Got 1 row and 3 columns:
| subject                                | property         | object                  |
| -------------------------------------- | ---------------- | ----------------------- |
| The Picture of Dorian Gray (wd:Q82464) | author (wdt:P50) | Oscar Wilde (wd:Q30875) |

[Assistant]
The author of "The Picture of Dorian Gray" is Oscar Wilde. Next, we need to find out how many other literary works Oscar Wilde wrote. We will look for all the works where Oscar Wilde is listed as the author and exclude "The Picture of Dorian Gray" from the count.

Let's construct a SPARQL query to achieve this.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Assistant]
It seems that the query returned a count of 0, which suggests that no other works were found where Oscar Wilde is listed as the author, excluding "The Picture of Dorian Gray." However, this is unlikely given Oscar Wilde's prolific writing career. Let's verify this by listing all the works where Oscar Wilde is listed as the author to ensure we are not missing anything.

Let's run a query to list all the works where Oscar Wilde is the author.

[Tool] Got no rows and 1 columns

[Assistant]
The query returned no results, which is unexpected given Oscar Wilde's known works. It's possible that the property `wdt:P50` (author) might not be the only way to link Oscar Wilde to his works. Let's try another approach by searching for properties related to "author" for Oscar Wilde's entity to see if there are any other relevant properties.

Let's search for properties related to "author" for Oscar Wilde.

[Tool]
Top 10 property alternatives:
1. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as p/wdt): notable scientific, artistic or literary work, or other work of significance among subject's works
2. Commons Creator page, also known as creator page, creator template (wd:P1472 as p/wdt): name of Commons Infobox template residing in "Creator" namespace on Wikimedia Commons
3. The Literary Encyclopedia person ID, also known as LE author ID, LE person ID, Literary Encyclopedia author ID, Literary Encyclopedia person ID, Literary Encyclopedia person identifier (wd:P11870 as p/wdt): identifier for an author in The Literary Encyclopedia
4. 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
5. 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
6. Project Gutenberg author ID, also known as Gutenberg ID, gutenberg.org/ebooks/author/, Project Gutenberg ID (author) (wd:P1938 as p/wdt/wdtn): author identifier at Project Gutenberg
7. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
8. BookBrainz author ID, also known as BB author ID, BookBrainz creator ID, BookBrainz ID (wd:P2607 as p/wdt): identifier for a creator per the BookBrainz open book encyclopedia
9. 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
10. PhilPapers author ID (wd:P3232 as p/wdt): identifier for authors of papers on PhilPapers

No other items found

[Assistant]
The search for properties related to "author" for Oscar Wilde did not yield any additional useful properties. However, the property `wdt:P800` (notable work) stands out as it links notable works to the author. Let's use this property to find all the notable works of Oscar Wilde and exclude "The Picture of Dorian Gray" from the count.

Let's construct a new SPARQL query using `wdt:P800`.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 4 (xsd:int) |

[Assistant]
The query returned a count of 4, indicating that Oscar Wilde wrote 4 other notable works besides "The Picture of Dorian Gray."

Therefore, the answer to the question "How many literary works besides The Picture of Dorian Gray did its author write?" is 4.

Here is the final SPARQL query:

```sparql
SELECT (COUNT(?work) AS ?count) WHERE {
  wd:Q30875 wdt:P800 ?work .
  FILTER(?work != wd:Q82464)
}
```

And the answer is 4.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q42053 wdt:P31 wd:Q1549591 .
  wd:Q42053 wdt:P1082 ?population .
  FILTER ( ?population > 1000000 )
}

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 Isfahan a big city?

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

[Tool]
Example 1:
Question:
Give me the grandchildren of Elvis Presley.

SPARQL:
SELECT DISTINCT ?o2 WHERE {
  wd:Q303 wdt:P40 ?o1 .
  ?o1 wdt:P40 ?o2
}

Using entities:
Elvis Presley, also known as The King of Rock'n'Roll, Elvis A. Presley, King of Rock'n'Roll, Elvis, Elvis Aaron Presley (wd:Q303): American singer and actor (1935–1977), military personnel, military officer, philanthropist, film actor, composer, activist, singer, actor

Using properties:
child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

Example 2:
Question:
What is the smallest city by area in Germany?

SPARQL:
SELECT ?res WHERE {
  ?res wdt:P17 wd:Q183 .
  ?res wdt:P31 / wdt:P279 * wd:Q515 .
  ?res wdt:P1082 ?inhabitants .
}
ORDER BY ?inhabitants
LIMIt 1

Using entities:
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
city, also known as cities (wd:Q515): large human settlement

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
What are the names of the Teenage Mutant Ninja Turtles?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P361 wd:Q1381762 .
}

Using entities:
Teenage Mutant Ninja Turtles, also known as Ninja Turtles, Teenage Mutant Hero Turtles, TMNT (wd:Q1381762): fictional team of four teenage anthropomorphic turtles

Using properties:
part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))

[Assistant] Based on the examples, we need to first identify the entity for Isfahan and then check if it is classified as a city. We can also look at its population to determine if it is considered a big city. Let's start by searching for the entity Isfahan.

[Tool]
Top 10 entity alternatives:
1. Isfahan, also known as Spahān, Spahan, Sepahan, Ispahān, Ispahân (wd:Q42053): city in Isfahan Province, Iran
2. Isfahan (wd:Q21998562): 1967 jazz song by Duke Ellington
3. Isfahan (wd:Q103936201): encyclopedia article
4. Isfahan Province, also known as Esfahan Province (wd:Q1367759): province of Iran
5. Isfahan County (wd:Q1282082): county in Isfahan Province, Iran
6. Isfahan International Airport, also known as IFN, IFN Airport, Isfahan Airport, OIFM, Shahid Beheshti Airport (wd:Q1151889): International Airport in Isfahan, Iran
7. Baharestan, also known as Baharestan, Isfahan (wd:Q430773): city in Isfahan Province, Iran
8. Isfahan Metro (wd:Q5963929): rapid transit system in Isfahan, Iran
9. Dowlatabad, also known as Shapurabad, Dowlatabad, Isfahan, Dowlatabad, Borkhar, Dowlatābād, Daulatābād (wd:Q2616779): city in Isfahan Province, Iran
10. Isfahan Grand Bazaar, also known as Isfahan Bazaar, Grand Bazaar of Isfahan, Grand Bazaar, Isfahan, Bazaar of Isfahan (wd:Q2754230): bazaar in Isfahan, Iran

[Assistant] The top result for Isfahan is the city in Isfahan Province, Iran. Now let's confirm that it is indeed classified as a city and check its population to determine if it is considered a big city. We will use the properties `instance of` (P31) and `population` (P1082).

[Tool]
Got 5 rows and 2 columns:
| instanceOf                  | population            |
| --------------------------- | --------------------- |
| big city (wd:Q1549591)      | 1961260 (xsd:decimal) |
| metropolis (wd:Q200250)     | 1961260 (xsd:decimal) |
| global city (wd:Q208511)    | 1961260 (xsd:decimal) |
| largest city (wd:Q51929311) | 1961260 (xsd:decimal) |
| city of Iran (wd:Q56557504) | 1961260 (xsd:decimal) |

[Assistant]
The results show that Isfahan is classified as a big city, metropolis, global city, largest city, and city of Iran. Additionally, its population is approximately 1,961,260, which is a significant number. Therefore, we can conclude that Isfahan is indeed a big city.

Here is the final SPARQL query and answer:

```sparql
ASK WHERE {
  wd:Q42053 wdt:P31 wd:Q1549591 .
  wd:Q42053 wdt:P1082 ?population .
  FILTER(?population > 1000000)
}
```

The answer to the question "Is Isfahan a big city?" is **True**.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?work WHERE {
  wd:Q312101 wdt:P800 ?work .
  FILTER ( ?work != wd:Q11835640 )
}

Got 5 rows and 1 column:
| work                                   |
| -------------------------------------- |
| Time of Contempt (wd:Q2045474)         |
| The Last Wish (wd:Q2414756)            |
| The Tower of the Swallow (wd:Q4080260) |
| Lady of the Lake (wd:Q4113386)         |
| Baptism of Fire (wd:Q4240572)          |

The notable works of Andrzej Sapkowski, apart from the book series 'The Witcher', include: Time of Contempt, The Last Wish, The Tower of the Swallow, Lady of the Lake, and Baptism of Fire.

[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] Apart from the book series the witcher, name all of the author’s notable work.

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

[Tool]
Example 1:
Question:
Give me all libraries established before 1400.

SPARQL:
SELECT * WHERE {
  ?uri wdt:P31 / wdt:P279 * wd:Q7075 .
  ?uri wdt:P571 ?date .
  FILTER ( YEAR( ?date ) < 1400 )
}

Using entities:
library, also known as libraries, library organization (wd:Q7075): institution charged with the care of a collection of literary, m...ence materials, such as books, manuscripts, recordings, or films

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt): time when an entity begins to exist; for date of official opening use P1619, start time

Example 2:
Question:
What is the timezone in San Pedro de Atacama?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q187893 wdt:P421 ?o1 .
}

Using entities:
San Pedro de Atacama (wd:Q187893): town in Chile

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

Example 3:
Question:
How large is the area of UK?

SPARQL:
SELECT ?area WHERE {
  wd:Q145 wdt:P2046 ?area .
}

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

Using properties:
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an object

[Assistant] From the examples, we can see how to structure a basic SPARQL query. We need to identify the author of "The Witcher" series and then find their other notable works. Let's start by searching for the author.

[Tool]
Top 10 entity alternatives:
1. Andrzej Sapkowski (wd:Q312101): Polish novelist, translator, writer
2. Andrzej, also known as Andřej, Andrzej (first name), Andrzej (given name) (wd:Q14941830): male given name
3. Andrzej, also known as Andrzej (Borkowski), Andrzej Borkowski (wd:Q24717986): Eastern Orthodox theologian and bishop, theologian, bishop
4. Andrzej Andrzejewski, also known as Andrzej Piotr Andrzejewski (wd:Q361187): Brigadier General/Polish Air Force (1961–2008), military officer
5. Andrzej Andrzejewski (wd:Q11685807): Polish actor, film actor, actor
6. Andrzej Andrzejczak (wd:Q9151455): Polish politician and deputy, politician
7. Adam Andrzejowski, also known as Andrzej Andrzejowski (wd:Q87355265): born 1880; died 1920, violinist, pedagogue, composer
8. Andrzej (wd:Q11685803)
9. Andrzej (wd:Q21445873): genus of insects
10. Andrzej (wd:Q22695582): iconographer

[Assistant] The correct entity for Andrzej Sapkowski is `wd:Q312101`. Now, let's find out what properties are associated with this entity to understand how to find his notable works.

[Tool]
Got 567 rows and 3 columns, showing the first 10 rows below:
| subject                        | property                         | object                                                                                |
| ------------------------------ | -------------------------------- | ---------------------------------------------------------------------------------------------------------------------- |
| Andrzej Sapkowski (wd:Q312101) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Andrzej Sapkowski (wd:Q312101) | occupation (wdt:P106)            | writer (wd:Q36180)                                                                                |
| Andrzej Sapkowski (wd:Q312101) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                                |
| Andrzej Sapkowski (wd:Q312101) | given name (wdt:P735)            | Andrzej (wd:Q14941830)                                                                                |
| Andrzej Sapkowski (wd:Q312101) | date of birth (wdt:P569)         | 1948-06-21T00:00:00Z (xsd:dateTime)                                                                                |
| Andrzej Sapkowski (wd:Q312101) | Commons category (wdt:P373)      | Andrzej Sapkowski                                                                                |
| Andrzej Sapkowski (wd:Q312101) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Andrzej%20Sapkowski%20-%20Lucca%20Comics%20%26%20Games%202015.JPG> |
| Andrzej Sapkowski (wd:Q312101) | country of citizenship (wdt:P27) | Poland (wd:Q36)                                                                                |
| Andrzej Sapkowski (wd:Q312101) | family name (wdt:P734)           | Sapkowski (wd:Q118493740)                                                                                |
| Andrzej Sapkowski (wd:Q312101) | place of birth (wdt:P19)         | Łódź (wd:Q580)                                                                                |
| ...                            | ...                              | ...                                                                                |

[Assistant] From the list of properties, we can see that `occupation` (wdt:P106) is linked to `writer` (wd:Q36180). However, we need to find the notable works of Andrzej Sapkowski. The property `notable work` (wdt:P800) seems relevant. Let's check if this property is used for Andrzej Sapkowski.

[Tool]
Got 6 rows and 3 columns:
| subject                        | property                | object                                 |
| ------------------------------ | ----------------------- | -------------------------------------- |
| Andrzej Sapkowski (wd:Q312101) | notable work (wdt:P800) | The Witcher (wd:Q11835640)             |
| Andrzej Sapkowski (wd:Q312101) | notable work (wdt:P800) | The Last Wish (wd:Q2414756)            |
| Andrzej Sapkowski (wd:Q312101) | notable work (wdt:P800) | Time of Contempt (wd:Q2045474)         |
| Andrzej Sapkowski (wd:Q312101) | notable work (wdt:P800) | Baptism of Fire (wd:Q4240572)          |
| Andrzej Sapkowski (wd:Q312101) | notable work (wdt:P800) | The Tower of the Swallow (wd:Q4080260) |
| Andrzej Sapkowski (wd:Q312101) | notable work (wdt:P800) | Lady of the Lake (wd:Q4113386)         |

[Assistant]
We have found the notable works of Andrzej Sapkowski, including "The Witcher" series. To exclude "The Witcher" series and list the other notable works, we can filter out the specific book series.

Let's construct the SPARQL query to achieve this:

1. Select the notable works of Andrzej Sapkowski.
2. Exclude "The Witcher" series.

Here is the SPARQL query:

```sparql
SELECT ?work WHERE {
  wd:Q312101 wdt:P800 ?work .
  FILTER(?work != wd:Q11835640) # Exclude The Witcher series
}
```

Let's execute this query to get the results.

[Tool]
Got 5 rows and 1 column:
| work                                   |
| -------------------------------------- |
| Time of Contempt (wd:Q2045474)         |
| The Last Wish (wd:Q2414756)            |
| The Tower of the Swallow (wd:Q4080260) |
| Lady of the Lake (wd:Q4113386)         |
| Baptism of Fire (wd:Q4240572)          |

[Assistant]
The SPARQL query has successfully returned the notable works of Andrzej Sapkowski, excluding "The Witcher" series. Here are the notable works:

- Time of Contempt (wd:Q2045474)
- The Last Wish (wd:Q2414756)
- The Tower of the Swallow (wd:Q4080260)
- Lady of the Lake (wd:Q4113386)
- Baptism of Fire (wd:Q4240572)

I will now provide the final answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?person ) AS ?count ) WHERE {
  ?person wdt:P166 wd:Q17985761 ; wdt:P172 wd:Q49085 .
}

[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 african-american people got a star on the Hollywood Walk of Fame?

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

[Tool]
Example 1:
Question:
What was the name of the famous battle in 1836 in San Antonio?

SPARQL:
SELECT ?uri WHERE {
  ?uri wdt:P276 wd:Q975 .
  ?uri wdt:P31 wd:Q178561 .
  ?uri wdt:P585 ?time .
  FILTER ( YEAR( ?time ) = 1836 )
}

Using entities:
battle, also known as ⚔, combat (wd:Q178561): part of a war which is well defined in duration, area and force commitment
San Antonio, also known as City of San Antonio, Alamo City, San Antonio, USA, San Antonio, TX, River City (wd:Q975): city in Bexar, Comal, and Medina counties in Texas, United States, that is the county seat of Bexar County

Using properties:
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)

Example 2:
Question:
In which U.S. state is Area 51 located?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q177397 wdt:P131 ?obj .
  ?obj wdt:P131 ?uri .
}

Using entities:
Area 51, also known as Paradise Ranch, Groom Lake, Area 51 (hawkin I., Nevada Area 51, KXTA (wd:Q177397): classified U.S. Military Base situated in Groom Lake, Nevada

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of

Example 3:
Question:
Give me all professional skateboarders from Sweden.

SPARQL:
SELECT ?s1 WHERE {
  ?s1 wdt:P641 wd:Q842284 .
  ?s1 wdt:P19 ?o1 .
  ?o1 wdt:P131 * wd:Q34 .
}

Using entities:
Sweden, also known as Swedish Kingdom, Konungariket Sverige, SWE, se, Kingdom of Sweden (wd:Q34): country in Northern Europe
skateboarding, also known as skateboard sport (wd:Q842284): action sport on skateboards

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location
sport, also known as play, plays, sport played, sports (wd:P641 as wdt): sport that the subject participates or participated in or is associated with

[Assistant] Based on the examples, we need to identify the relevant entities and properties for our question. We need to find African-American people who have a star on the Hollywood Walk of Fame. Let's start by searching for the entity representing the Hollywood Walk of Fame.

[Tool]
Top 10 entity alternatives:
1. Hollywood Walk of Fame, also known as Walk of Fame (wd:Q71719): more than 2,700 five-pointed terrazzo and brass stars embedded i...ulevard and three blocks of Vine Street in Hollywood, California
2. star on Hollywood Walk of Fame, also known as Hollywood Walk of Fame star (wd:Q17985761): award in the Hollywood Walk of Fame, Hollywood, California, United States
3. Hollywood's Rock Walk of Fame (wd:Q3139400)
4. Walk of Fame (wd:Q48673901): 2017 film by Jesse Thomas
5. Walk of Fame (wd:Q51084447): street in Saint Petersburg, Russia
6. Starr gets star; Ringo added to Hollywood Walk of Fame (wd:Q18021457): Wikinews article
7. Walk of Fame (wd:Q7962075): memorial for famous dogs in Battersea Park, London, England, UK
8. walk of fame (wd:Q47502370): sidewalk or similar construction that commemorates outstanding individuals in a particular group
9. Walk of Fame (wd:Q114476628): episode of Cupcake Wars (S2 E11)
10. Walk of Fame, also known as Wigan's Walk of Fame, Believe Square (wd:Q121879112): public walkway in Wigan, England

[Assistant] The first result, "Hollywood Walk of Fame" (wd:Q71719), seems to be the correct entity for our query. Next, we need to find the property that indicates a person has a star on the Hollywood Walk of Fame. Let's search for this property.

[Tool]
Top 10 property alternatives:
1. spectral class, also known as is an object of class, is a star of class (wd:P215 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): spectral class of an astronomical object
2. parent astronomical body, also known as star, primary, parent body, orbits, planetary system (wd:P397 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): major astronomical body the item belongs to
3. cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
4. significant person, also known as significant people, sigper, sign. person, relevant person, relevant people (wd:P3342 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person linked to the item in any possible way
5. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
6. hotel rating, also known as hotel stars, star rating of a hotel (wd:P10290 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): star rating of the hotel
7. Movie Walker Press person ID, also known as Movie Walker person ID (wd:P7745 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier of person on the Movie Walker Press database
8. Douban movie celebrity ID, also known as https://movie.douban.com/celebrity, https://movie.douban.com, https://m.douban.com, Douban person ID, douban.com person ID (wd:P5284 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a celebrity at the Douban movie website
9. influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”
10. agent of action, also known as being done by, initiator, initiated by, done by, doer (wd:P12995 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): particular item that initiates this action or class of actions

[Assistant]
None of the top 10 properties seem to directly indicate having a star on the Hollywood Walk of Fame. However, the second result, "star on Hollywood Walk of Fame" (wd:Q17985761), is an entity that represents the award itself. We can use this entity to find people who have received it. Let's try to find the property that links people to this award.

We can use the `search_property_of_entity` function to find properties related to the "star on Hollywood Walk of Fame" entity.

[Tool]
Top 10 property alternatives:
1. category for recipients of this award, also known as recipient category, recipcat (wd:P2517 as p/wdt): link to Wikimedia category for recipients of this award, topic's main category
2. 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)
3. 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)
4. 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)
5. 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
6. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
7. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
8. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
9. has list, also known as list, topic's list, topic list, related list, list for this topic (wd:P2354 as p/wdt): Wikimedia list related to this subject

No other items found

[Assistant]
The property "category for recipients of this award" (wd:P2517) seems to be the closest match. However, it links to a category rather than directly to the recipients. Instead, let's try to find the property that directly links people to the "star on Hollywood Walk of Fame" entity.

We can use the `list` function to find examples of how the "star on Hollywood Walk of Fame" entity is used in the knowledge graph.

[Tool]
Got 4,884 rows and 3 columns, showing the first 10 rows below:
| subject                                                                                | property                             | object                                        |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------ | --------------------------------------------- |
| Donald Trump (wd:Q22686)                                                                                | award received (wdt:P166)            | star on Hollywood Walk of Fame (wd:Q17985761) |
| s:Q214959-64bfaace-4911-bb73-8618-9fa7d4a2c53b                                                                                | depicts (pq:P180)                    | star on Hollywood Walk of Fame (wd:Q17985761) |
| wd:Q42343458                                                                                | category's main topic (wdt:P301)     | star on Hollywood Walk of Fame (wd:Q17985761) |
| wd:Q152471                                                                                | is a list of (wdt:P360)              | star on Hollywood Walk of Fame (wd:Q17985761) |
| wd:Q25476868                                                                                | based on (wdt:P144)                  | star on Hollywood Walk of Fame (wd:Q17985761) |
| Hollywood Walk of Fame (wd:Q71719)                                                                                | has part(s) of the class (wdt:P2670) | star on Hollywood Walk of Fame (wd:Q17985761) |
| <https://ar.wikipedia.org/wiki/%D9%86%D8%AC%D9%85%D8%A9_%D8%B9%D9%84%D9%89_%D9%85%D9%85%D8%B1_%D8%A7%D9%84%D8%B4%D9%87%D8%B1%D8%A9_%D9%81%D9%8A_%D9%87%D9%88%D9%84%D9%8A%D9%88%D9%88%D8%AF> | schema:about                         | star on Hollywood Walk of Fame (wd:Q17985761) |
| Michael Jackson (wd:Q2831)                                                                                | award received (wdt:P166)            | star on Hollywood Walk of Fame (wd:Q17985761) |
| Ronald Reagan (wd:Q9960)                                                                                | award received (wdt:P166)            | star on Hollywood Walk of Fame (wd:Q17985761) |
| Charlie Chaplin (wd:Q882)                                                                                | award received (wdt:P166)            | star on Hollywood Walk of Fame (wd:Q17985761) |
| ...                                                                                | ...                                  | ...                                           |

[Assistant] From the results, we can see that the property "award received" (wdt:P166) is used to link people to the "star on Hollywood Walk of Fame" entity. Now, we need to find the property that indicates a person's race or ethnicity, specifically African-American. Let's search for this property.

[Tool]
Top 10 property alternatives:
1. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
2. classification of race, also known as classification of cycling race (wd:P2502 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): race for which this classification applies
3. demographics of topic, also known as demography of topic (wd:P9241 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): item that deals with demographics of the subject
4. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the object is a country that recognizes the subject as its citizen, country
5. Statistics Indonesia ethnicity code, also known as BPS ethnicity code (wd:P2589 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): ethnicity code in Indonesia by Statistics Indonesia (Badan Pusat Statistik)
6. animal breed, also known as breed, sheep breed, horse breed, goat breed, duck breed (wd:P4743 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): subject item belongs to a specific group of domestic animals, generally given by association
7. general classification of race participants, also known as GC (wd:P2321 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): classification of race participants, participant
8. Library of Congress Demographic Group Terms ID, also known as Demographic Group ID (Library of Congress), Demographic Group Terms ID (Library of Congress), LC Demographic Group Terms ID, LCDGT ID, LoC Demographic Group Terms ID (wd:P4946 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a term in the Library of Congress Demographic Group Terms controlled vocabulary
9. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): country a person or a team represents when playing a sport, country
10. pronunciation variety, also known as language variant, with pronunciation, with dialect, pronunciation, dialect (wd:P5237 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): qualifier for IPA transcription (P898), pronunciation audio (P44... audio (P989) to indicate the associated spoken language variant

[Assistant] The property "ethnic group" (wdt:P172) seems to be the correct property to indicate a person's race or ethnicity. Now, we need to find the entity representing African-Americans. Let's search for this entity.

[Tool]
Top 10 entity alternatives:
1. African Americans, also known as Black or African American, African-American, Black Americans and Afro-Americans, Black Americans, African American people (wd:Q49085): Americans with sub-Saharan African ancestry
2. Textbooks > Fiction & Literature > African American, also known as African American, Textbooks - Fiction & Literature - African American (wd:Q110593688): iTunes Textbooks genre
3. African American (wd:L983173-S1)
4. African American (wd:L983172-S1)
5. slavery in the United States, also known as African American slavery, American slavery, slavery in the United States of America, slavery (United States), slavery (United States of America) (wd:Q118382): form of slave labor which existed as a legal institution from the early years of the United States
6. African-American music, also known as African American music, Afro-American music, Black American music, Black music (wd:Q388207): musical traditions of African American people
7. African American literature, also known as African-American literature, Afro-American literature, Black literature, Negro literature (wd:Q388170): body of literature by Americans of African descent
8. Hoodoo, also known as African American Hoodoo (wd:Q1546302): spiritual practices, traditions and beliefs
9. African American history, also known as African-American history, Afro-American history, Black American history, history of African Americans, history of African-Americans (wd:Q162881): black American history
10. African American studies, also known as African American and Diaspora Studies, African-American/Black studies, African-Americanology, African-American studies, Black studies (wd:Q383968): academic field focusing on peoples of the African diaspora and Africa

[Assistant]
The first result, "African Americans" (wd:Q49085), seems to be the correct entity for our query. Now we have all the necessary components to construct the SPARQL query. We need to find people who have a star on the Hollywood Walk of Fame and are African-American.

Let's write the SPARQL query to find these people.

[Tool]
Got 105 rows and 1 column, showing the first 5 and last 5 rows below:
| person                                  |
| --------------------------------------- |
| Halle Berry (wd:Q1033016)               |
| Sidney Poitier (wd:Q104049)             |
| Billie Holiday (wd:Q104358)             |
| Herbie Hancock (wd:Q105875)             |
| Jimmy Jam and Terry Lewis (wd:Q1063111) |
| ...                                     |
| Little Richard (wd:Q82222)              |
| Donna Summer (wd:Q908933)               |
| Eddie Heywood (wd:Q924783)              |
| Teddy Riley (wd:Q927450)                |
| Miles Davis (wd:Q93341)                 |

[Assistant]
The SPARQL query successfully returned a list of African-American people who have a star on the Hollywood Walk of Fame. To get the count of these people, we can modify the query to use the `COUNT` function.

Let's update the query to count the number of African-American people with a star on the Hollywood Walk of Fame.

[Tool]
Got 1 row and 1 column:
| count         |
| ------------- |
| 105 (xsd:int) |

[Assistant]
The SPARQL query returned the count of African-American people who have a star on the Hollywood Walk of Fame. There are 105 such individuals.

Here is the final SPARQL query and the answer:

```sparql
SELECT (COUNT(?person) AS ?count) WHERE {
  ?person wdt:P166 wd:Q17985761 ;
          wdt:P172 wd:Q49085 .
}
```

The answer to the question is: **105** African-American people have a star on the Hollywood Walk of Fame.

[Tool] Stopped generation process


Failed to generate SPARQL query

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

You have access to the following knowledge graphs:
wikidata at 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 created the Turing machine?

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

[Tool]
Example 1:
Question:
Who wrote Harry Potter?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q8337 wdt:P50 ?uri
}

Using entities:
Harry Potter, also known as Harry Potter series (wd:Q8337): 1997–2007 fantasy book series by J. K. Rowling

Using properties:
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

Example 2:
Question:
What movies does Jesse Eisenberg play in?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P161 wd:Q219512 .
}

Using entities:
Jesse Eisenberg, also known as Jesse Adam Eisenberg (wd:Q219512): television actor, American actor, film director, screenwriter, voice actor, stage actor, film actor, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer

Example 3:
Question:
Who has Tom Cruise been married to?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q37079 wdt:P26 ?o1 .
}

Using entities:
Tom Cruise, also known as Thomas Cruise Mapother IV (wd:Q37079): American actor and producer (born 1962), stunt performer, aircraft pilot, film producer, film director, screenwriter, film actor, producer, director, writer, actor

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

[Assistant] Based on the examples, we can see that the pattern for finding the creator of something is to use the property `wdt:P178` (designer) or `wdt:P50` (author). However, since the Turing machine is more of an invention, we might want to look for the property `wdt:P178` first. Let's search for the entity "Turing machine" and then check which property is more appropriate.

[Tool]
Top 10 entity alternatives:
1. Turing machine, also known as deterministic Turing machine (wd:Q163310): abstract computation model; mathematical model of computation th...pulates symbols on a strip of tape according to a table of rules
2. Turing Machine (wd:Q7854958): band
3. Turing Machine (wd:Q118469770): Greek theatrical performance at the New Theatre of Katerina Vassilakou, Athens, 2022/3
4. Turing Machine (wd:Q116450980): 2022 board game
5. non-deterministic Turing machine, also known as nondeterministic Turing machine, NTM (wd:Q1190223): may have a set of rules that prescribes more than one action for...t actions may apply for the same combination of state and symbol
6. universal Turing machine, also known as UCM, Universal Computing Machine, UTM (wd:Q2703890): turing machine that can simulate an arbitrary Turing machine on ...e to be simulated as well as the input thereof from its own tape
7. probabilistic Turing machine (wd:Q1191836): non-deterministic Turing machine which chooses between the avail...sitions at each point according to some probability distribution
8. quantum Turing machine (wd:Q765620): model of quantum computation
9. Alternating Turing machine, also known as Alternating Turing Machine, ATM (wd:Q438833): abstract computation model
10. neural Turing machine (wd:Q25325414): neural network with external memory

[Assistant]
The correct entity for "Turing machine" is `wd:Q163310`. Now let's check which property is more appropriate for finding the creator of the Turing machine. We will try both `wdt:P178` (designer) and `wdt:P50` (author).

First, let's try `wdt:P178`:

[Tool] Got no rows and 1 columns

[Assistant] It seems that the property `wdt:P178` (designer) did not yield any results. Let's now try `wdt:P50` (author):


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?builtDate WHERE {
  wd:Q523286 wdt:P571 ?builtDate .
}

The Hambach Castle was built around the year 1100.

[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 Hambach Castle built?

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

[Tool]
Example 1:
Question:
Who wrote The Hunger Games?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q11679 wdt:P50 ?uri .
}

Using entities:
The Hunger Games, also known as Hunger Games Saga, The Hunger Games Saga (wd:Q11679): three books by Suzanne Collins (2008–2010)

Using properties:
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

Example 2:
Question:
Who was Vincent van Gogh inspired by?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q5582 wdt:P737 ?uri .
}

Using entities:
Vincent van Gogh (wd:Q5582): Dutch painter (1853–1890), draftsperson, printmaker, painter

Using properties:
influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as wdt): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”

Example 3:
Question:
Who is the daughter of Bill Clinton married to?

SPARQL:
SELECT * {
  wd:Q1124 wdt:P40 ?child .
  ?child wdt:P26 ?uri
}

Using entities:
Bill Clinton, also known as William Jefferson Blythe, William Jefferson Blythe III, William Jefferson "Bill" Clinton, William Jefferson Clinton, WJC (wd:Q1124): President of the United States from 1993 to 2001, autobiographer, statesperson, saxophonist, politician, governor, diplomat, teacher, jurist, lawyer, writer

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

[Assistant] Based on the examples, we need to identify the entity for Hambach Castle and then find the property that indicates when it was built. Let's start by searching for the entity "Hambach Castle".

[Tool]
Top 10 entity alternatives:
1. Hambach Castle (wd:Q523286): castle near the urban district Hambach of Neustadt an der Weinstraße in Rhineland-Palatinate, Germany
2. castle (wd:Q23413): type of fortified structure built in Europe, Asia and the Middle East during the Middle Ages by nobility
3. rook, also known as marquess, tower, Rook (chess), rector, R (wd:Q137): piece from the board game chess
4. castling, also known as castle (wd:Q102877): chess move in which the king moves 2 squares toward a rook, while the rook moves to the square passed over by the king
5. Castle (wd:Q386880): American police procedural comedy-drama television series (2009-2016)
6. Hambach (wd:Q22391): commune in Moselle, France
7. château, also known as castle, chateau, landschloss (wd:Q751876): type of manor house mostly built by noble families for representative purposes
8. Hambach, also known as Hambach (Diez) (wd:Q566907): municipality of Germany
9. Castle, also known as Castle, OK (wd:Q3287085): town in Okfuskee County, Oklahoma, United States
10. Peveril Castle, also known as Peak Castle, Peveril Castle eleventh to fourteenth century tower keep castle, Castleton Castle (wd:Q255574): castle in Castleton, Derbyshire, England, UK

[Assistant] The correct entity for Hambach Castle is `wd:Q523286`. Now, let's find the property that indicates when it was built. We can search for properties related to "built" or "construction" for this entity.

[Tool]
Top 10 property alternatives:
1. 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
2. architectural style, also known as architecture, style of architecture (wd:P149 as p/wdt): architectural style of a structure, movement
3. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
4. 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
5. 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
6. Structurae structure ID, also known as Structurae ID for building, Structurae ID (structure), Structurae ID for structure (wd:P454 as p/wdt): identifier for a building in the Structurae database
7. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. 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)
9. 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
10. 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 p/wdt): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of

No other items found

[Assistant]
The property `inception` (wd:P571) seems to be the most relevant for indicating when Hambach Castle was built. Let's construct a SPARQL query to retrieve this information.

```sparql
SELECT ?builtDate WHERE {
  wd:Q523286 wdt:P571 ?builtDate .
}
```

I will now execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| builtDate                           |
| ----------------------------------- |
| 1100-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The Hambach Castle was built around the year 1100.

Here is the final SPARQL query and answer:

```sparql
SELECT ?builtDate WHERE {
  wd:Q523286 wdt:P571 ?builtDate .
}
```

Answer: The Hambach Castle was built around the year 1100.

[Tool] Stopped generation process