PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?person ?personLabel ?youtubeChannelID ?followers WHERE {
  ?person wdt:P106 wd:Q17125263 ; wdt:P106 wd:Q15143191 .
  FILTER NOT EXISTS {
    ?person wdt:P18 ?image
  }
  OPTIONAL {
    ?person wdt:P2397 ?youtubeChannelID
  }
  OPTIONAL {
    ?person wdt:P8284 ?followers
  }
  OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( LANG( ?personLabel ) = "en" )
  }
}
ORDER BY DESC ( ?followers )

Got 13 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                                   | personLabel                   | youtubeChannelID         | followers |
| ---------------------------------------- | ----------------------------- | ------------------------ | --------- |
| Vincent Heidelberg (wd:Q100710319)       | Vincent Heidelberg (en)       |                          |           |
| Henrique Abrahão Charles (wd:Q104882878) | Henrique Abrahão Charles (en) | UCxSbDOAmDA9xSDd3Numjsmg |           |
| Andrea Moccia (wd:Q106041589)            | Andrea Moccia (en)            |                          |           |
| Valentine Delattre (wd:Q118744878)       | Valentine Delattre (en)       | UCE_LWXcsdp7cWbo4DR4ZA-A |           |
| Willy Guasti (wd:Q119828705)             | Willy Guasti (en)             | UCyD1TlHPTq-H9dvQC3tr0zw |           |
| ...                                      | ...                           | ...                      | ...       |
| Begoña Gerpe (wd:Q131525183)             | Begoña Gerpe (en)             | UC1KFgMi-KVzNKnvYIkFxqCg |           |
| wd:Q133765022                            | Anton Petrov (en)             |                          |           |
| Tim Blais (wd:Q59240217)                 | Tim Blais (en)                |                          |           |
| Simon Whistler (wd:Q61053071)            | Simon Whistler (en)           | UCvqt8j7DfPmveJp3UOk9XTg |           |
| Mario Peláez-Fernández (wd:Q65073470)    | Mario Peláez-Fernández (en)   | UCipVtSaV6OOKk8VTMcHt71Q |           |

There are 13 YouTubers who are also science communicators and do not have an image. Some have a YouTube channel ID, but none have the number of social media followers listed. The results are ordered by the number of social media followers in descending order.

[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 are the YouTubers who are also science communicators and do not have an image? Include their YouTube channel ID and number of social media followers if available, and order by the number of social media followers in descending order.

[Assistant]
To answer this question, I need to identify entities that are YouTubers and also science communicators. Then, I need to filter those who do not have an image. For the resulting entities, I will retrieve their YouTube channel ID and the number of social media followers if available. Finally, I will order the results by the number of social media followers in descending order.

Step 1: Identify the Wikidata entities for "YouTuber" and "science communicator."
Step 2: Find entities that have both these occupations.
Step 3: Filter entities that do not have an image (property P18).
Step 4: Retrieve their YouTube channel ID (property P2397) and number of social media followers (property P8284).
Step 5: Order the results by the number of social media followers in descending order.

I will start by searching for the entities "YouTuber" and "science communicator."

[Tool]
Top 10 entity alternatives:
1. YouTuber, also known as YouTube user, YTer, YouTube Star, YouTube personality, Tuber (wd:Q17125263): person that produces videos on YouTube
2. Douha Laribi, also known as Tiktoker, Youtuber (wd:Q115557477): Tunisian influencer, TikToker
3. Youtuber (wd:Q125943224): written work by Gabriel Jaraba
4. Youtuber (wd:Q125943233): 2015 edition of written work by Gabriel Jaraba
5. YouTuber (wd:L34823-F1)
6. YouTuber (wd:L34823)
7. VTuber, also known as virtual YouTuber, V Tuber (wd:Q55155641): YouTuber or livestreamer that uses a digital avatar
8. Jumana Abdu Rahman, also known as Jumana Khan, Jumana Dubai, Jumana Youtuber, Actress Jumana, Jumana (wd:Q130728826): Indian actress and social media personality from Dubai, Internet celebrity, content creator, philanthropist, entrepreneur, influencer, orator, actor
9. beauty YouTuber, also known as Beautuber, beauty guru, beauty influencer, BeautyTuber, beauty vlogger (wd:Q23680154): content creator who specializes on beauty related products
10. Youtuber Dad, also known as Papá youtuber (wd:Q104388845): 2019 Peruvian-Argentine film

[Tool]
Top 10 entity alternatives:
1. science communicator, also known as scientific popularizer, science popularizer, SciComm'er, popularizer of science, populariser of science (wd:Q15143191): person who explains science to non-experts and the public
2. The science communicator (wd:Q73972391): journal article; published in Nature on 2008-12-17
3. Science Communicator Medal (wd:Q106706041): science award in New Zealand
4. Dante Alighieri Science Communicator (wd:Q115869045): scholarly article published on Substantia in 2021
5. Foundation for Research Science ...ology Science Communicator Award, also known as FRS&T Science Communicator Award, FRST Science Communicator Award (wd:Q106706036): science award in New Zealand
6. International Union for Science Communicators (wd:Q6054094): professional science organization
7. Lars Lindberg Christensen, also known as The Hands-On Guide for Science Communicators (wd:Q6491614): Danish astronomer (b.1970), science communicator, astronomer, writer
8. Television Weathercasters as Environmental Science Communicators (wd:Q58066203)
9. science, also known as general science, empirical sciences, scientific knowledge, sciences (wd:Q336): systematic endeavor that builds and organizes knowledge, and the set of knowledge produced by this system
10. Science, also known as sciencemag.org/, science.org, Sci. (N. Y., N. Y.), Science Magazine (wd:Q192864): academic journal of the American Association for the Advancement of Science

[Assistant]
The entity for "YouTuber" is wd:Q17125263 and for "science communicator" is wd:Q15143191.

Next, I will write a SPARQL query to find entities that have both occupations "YouTuber" and "science communicator," do not have an image (property P18), and retrieve their YouTube channel ID (property P2397) and number of social media followers (property P8284). I will order the results by the number of social media followers in descending order.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant] The query failed due to the use of the SERVICE wikibase:label, which is not supported by the used QLever SPARQL endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use OPTIONAL clauses to get the rdfs:label for the person.

[Tool]
Got 13 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                                   | personLabel                   | youtubeChannelID         | followers |
| ---------------------------------------- | ----------------------------- | ------------------------ | --------- |
| Vincent Heidelberg (wd:Q100710319)       | Vincent Heidelberg (en)       |                          |           |
| Henrique Abrahão Charles (wd:Q104882878) | Henrique Abrahão Charles (en) | UCxSbDOAmDA9xSDd3Numjsmg |           |
| Andrea Moccia (wd:Q106041589)            | Andrea Moccia (en)            |                          |           |
| Valentine Delattre (wd:Q118744878)       | Valentine Delattre (en)       | UCE_LWXcsdp7cWbo4DR4ZA-A |           |
| Willy Guasti (wd:Q119828705)             | Willy Guasti (en)             | UCyD1TlHPTq-H9dvQC3tr0zw |           |
| ...                                      | ...                           | ...                      | ...       |
| Begoña Gerpe (wd:Q131525183)             | Begoña Gerpe (en)             | UC1KFgMi-KVzNKnvYIkFxqCg |           |
| wd:Q133765022                            | Anton Petrov (en)             |                          |           |
| Tim Blais (wd:Q59240217)                 | Tim Blais (en)                |                          |           |
| Simon Whistler (wd:Q61053071)            | Simon Whistler (en)           | UCvqt8j7DfPmveJp3UOk9XTg |           |
| Mario Peláez-Fernández (wd:Q65073470)    | Mario Peláez-Fernández (en)   | UCipVtSaV6OOKk8VTMcHt71Q |           |

[Assistant] I found 13 YouTubers who are also science communicators and do not have an image. Some of them have a YouTube channel ID, but none have the number of social media followers listed. I will now provide the SPARQL query and the results.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?game ?gameLabel WHERE {
  VALUES ?game {
    wd:Q111168061 wd:Q132646179
  }
  ?game rdfs:label ?gameLabel FILTER ( LANG( ?gameLabel ) = "en" )
}

The role-playing video games identified are Xeonjia and Pandoland. Unfortunately, there is no available information on their developers, publishers, or publication dates in the data.

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

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

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

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

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

[User] Which items are role-playing video games? Include their developers, publishers, and publication dates, if available.

[Assistant]
To answer this question, I need to identify the entity for "role-playing video games" and then find items that are instances of or subclasses of this entity. For each identified role-playing video game, I will retrieve its developers, publishers, and publication dates if available.

Step 1: Search for the entity "role-playing video game" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. role-playing video game, also known as role playing video games, RP video game, RPVG, RPG videogame, RPG video game (wd:Q744038): video game genre
2. action role-playing game, also known as ARPG, action/RPG, action RPG, action role-playing video game, action-RPG (wd:Q1422746): subgenre of role-playing and action video games
3. gamer, also known as player, video game player, video gamer, video role-playing game player, video RPG player (wd:Q5276395): person who plays video games and/or identifies with the gamer identity
4. tactical role-playing game, also known as RSLG, simulation RPGs, SRPG, strategic roleplaying game, strategy role-playing game (wd:Q1529437): video game genre
5. Japanese role-playing video game, also known as Japanese role-playing game, JRPG (wd:Q5923834): video game genre
6. turn-based role-playing game, also known as turn-based RPG, turn-based roleplaying game, turn-based role-playing video game (wd:Q105906396): genre of roleplaying games where players take turns when playing
7. side-scrolling role-playing video game, also known as side-scrolling RPG, side-scrolling role-playing game, side-scroller RPG (wd:Q107631040): video game genre
8. Western role-playing game, also known as Western role-playing video games, Western RPG, WRPG (wd:Q61654424): video game subgenre
9. history of Western role-playing video games, also known as history of Western RPGs, Western role-playing video games history (wd:Q5867207): aspect of history
10. chronology of tactical role-playing video games (wd:Q16968506)

[Assistant]
The entity "role-playing video game" is identified as wd:Q744038. Now, I will find items that are instances of this entity (role-playing video game) and retrieve their developers, publishers, and publication dates if available.

I will start with a query to get role-playing video games along with their developers, publishers, and publication dates.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant]
The query failed because the SERVICE wikibase:label is not supported by the endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use optional rdfs:label for the labels.

I will now execute the revised query to get role-playing video games with their developers, publishers, and publication dates.

[Tool]
SPARQL execution failed:
Tried to allocate 1.4 GB, but only 739.7 MB were available. Clear the cache or allow more memory for QLever during startup

[Assistant]
The query failed due to memory limitations. To reduce the memory usage, I will limit the number of results further and simplify the query by removing some optional labels for now. I will focus on retrieving the game, developer, publisher, and publication date IRIs first. Then I can add labels in a separate query if needed.

I will try a simpler query with a smaller limit.

[Tool]
Got 2 rows and 4 columns:
| game                      | developer | publisher | publicationDate |
| ------------------------- | --------- | --------- | --------------- |
| Xeonjia (wd:Q111168061)   |           |           |                 |
| Pandoland (wd:Q132646179) |           |           |                 |

[Assistant]
I found two role-playing video games: Xeonjia (wd:Q111168061) and Pandoland (wd:Q132646179). However, they do not have developer, publisher, or publication date information in the results.

I will now try to get the English labels for these games, their developers, and publishers to provide more readable information.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
The query to get labels timed out. Since the initial query returned very few results, I will try to expand the limit slightly and get the labels directly in one query but with a smaller timeout by limiting the number of results to 5.

I will try again to get role-playing video games with their developers, publishers, publication dates, and labels for all these entities with a limit of 5.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
The query keeps timing out, likely due to the complexity and size of the data. To reduce complexity, I will try a different approach: first get a few role-playing video games with their labels only, then for each game, I will query developers, publishers, and publication dates separately.

Step 1: Get 5 role-playing video games with their English labels.

[Tool]
Got 2 rows and 2 columns:
| game                      | gameLabel      |
| ------------------------- | -------------- |
| Xeonjia (wd:Q111168061)   | Xeonjia (en)   |
| Pandoland (wd:Q132646179) | Pandoland (en) |

[Assistant]
I retrieved two role-playing video games with their labels: Xeonjia and Pandoland.

Step 2: For each of these games, I will now query their developers, publishers, and publication dates separately.

I will start with Xeonjia (wd:Q111168061).

[Tool]
SPARQL execution failed:
Tried to allocate 3.3 GB, but only 2.8 GB were available. Clear the cache or allow more memory for QLever during startup

[Assistant] The query failed again due to memory limitations. To reduce memory usage, I will simplify the query by removing the optional labels for developer and publisher and only retrieve their IRIs along with the publication date for Xeonjia. Then I can query labels separately if needed.

[Tool]
Got 1 row and 3 columns:
| developer | publisher | publicationDate |
| --------- | --------- | --------------- |

[Assistant]
For the game Xeonjia, there is no available information on developer, publisher, or publication date in the data.

I will now try the same simplified query for the game Pandoland (wd:Q132646179).

[Tool]
Got 1 row and 3 columns:
| developer | publisher | publicationDate |
| --------- | --------- | --------------- |

[Assistant]
For the game Pandoland, there is also no available information on developer, publisher, or publication date in the data.

Since the initial results returned only two games with no additional information, I will try to get more role-playing video games (up to 10) with their labels only to see if there are games with more complete information. Then I can query their details one by one.

[Tool]
Got 2 rows and 2 columns:
| game                      | gameLabel      |
| ------------------------- | -------------- |
| Xeonjia (wd:Q111168061)   | Xeonjia (en)   |
| Pandoland (wd:Q132646179) | Pandoland (en) |

[Assistant]
The query to get 10 role-playing video games with labels still returns only the same two games: Xeonjia and Pandoland.

Given the limited data available for these games, I will now try to find role-playing video games that have developers or publishers by adding a filter to the query to only get games with developers or publishers. This might give us games with more complete information. I will limit the results to 5.

[Tool] Got no rows and 7 columns

[Assistant]
There are no role-playing video games with developers or publishers available in the data from this query.

Given the limited data and repeated timeouts or memory issues, I will provide the two identified role-playing video games (Xeonjia and Pandoland) with the information available, which unfortunately does not include developers, publishers, or publication dates.

I will now finalize the answer with these two games and mention the lack of additional information.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?item ?itemLabel ?instanceOf ?instanceOfLabel WHERE {
  ?item wdt:P830 ?eolID .
  ?item wdt:P31 ?instanceOf .
  FILTER NOT EXISTS {
    ?item wdt:P31 / wdt:P279 * wd:Q16521 .
  }
  FILTER NOT EXISTS {
    ?item wdt:P31 wd:Q16521 .
  }
  OPTIONAL {
    ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" )
  }
  OPTIONAL {
    ?instanceOf rdfs:label ?instanceOfLabel FILTER ( LANG( ?instanceOfLabel ) = "en" )
  }
}
LIMIT 100

Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| item                                                    | itemLabel                                     | instanceOf                                              | instanceOfLabel                               |
| ------------------------------------------------------- | --------------------------------------------- | ------------------------------------------------------- | --------------------------------------------- |
| Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) (en) | later homonym (wd:Q17276484)                            | later homonym (en)                            |
| Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) (en) | Oecophoridae (wd:Q782541)                               | Oecophoridae (en)                             |
| Notaspis Warren (1892) (wd:Q10337670)                   | Notaspis Warren (1892) (en)                   | Crambidae (wd:Q132980)                                  | Crambidae (en)                                |
| Notaspis Warren (1892) (wd:Q10337670)                   | Notaspis Warren (1892) (en)                   | later homonym (wd:Q17276484)                            | later homonym (en)                            |
| Catenella Bat. & Peres (1963) (wd:Q10443855)            | Catenella Bat. & Peres (1963) (en)            | later homonym (wd:Q17276484)                            | later homonym (en)                            |
| ...                                                     | ...                                           | ...                                                     | ...                                           |
| Copriodes perinephela (wd:Q13496844)                    | Copriodes perinephela (en)                    | unavailable combination (wd:Q17487588)                  | unavailable combination (en)                  |
| Copriodes polynephela (wd:Q13496845)                    | Copriodes polynephela (en)                    | Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) (en) |
| Copriodes polynephela (wd:Q13496845)                    | Copriodes polynephela (en)                    | unavailable combination (wd:Q17487588)                  | unavailable combination (en)                  |
| Doclea syntomoides (wd:Q13592892)                       | Doclea syntomoides (en)                       | unavailable combination (wd:Q17487588)                  | unavailable combination (en)                  |
| Doclea syntomoides (wd:Q13592892)                       | Doclea syntomoides (en)                       | Doclea Walker (1865) non Leach (1815) (wd:Q18522853)    | Doclea Walker (1865) non Leach (1815) (en)    |

The distinct items that have an Encyclopedia of Life ID but are not taxons or subclasses of taxons are retrieved by the SPARQL query. The query returns the item identifiers, their labels, and the labels of what the items are instances of.

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

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

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

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

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

[User] What are the distinct items that have an Encyclopedia of Life ID, but are not taxons or subclasses of taxons? Include item labels and labels of what the items are instances of.

[Assistant]
To answer this question, I need to identify items that have an Encyclopedia of Life ID but are neither taxons nor subclasses of taxons. I will proceed with the following steps:

1. Identify the property for Encyclopedia of Life ID.
2. Identify the class for taxon.
3. Find items with Encyclopedia of Life ID.
4. Exclude items that are instances of taxon or subclasses of taxon.
5. Retrieve the labels of the items and the labels of what the items are instances of.

Step 1: Search for the property "Encyclopedia of Life ID".

[Tool]
Top 10 property alternatives:
1. Encyclopedia of Life ID, also known as eol, EoL ID (wd:P830 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): eol.org item reference number
2. Catalogue of Life ID, also known as CoL ID (wd:P10585 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): identifier of a taxon or synonym in the Catalogue of Life
3. Encyclopedia.com ID (wd:P11850 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): identifier of item within Encyclopedia.com
4. A Dictionary of Biology ID, also known as Dictionary of Biology ID (wd:P12774 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): identifier for an entry in online eighth edition of A Dictionary of Biology
5. A Dictionary of Zoology ID, also known as Dictionary of Zoology ID (wd:P12789 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): identifier for an entry in online fifth edition of A Dictionary of Zoology
6. South Carolina Encyclopedia ID, also known as SCencyclopedia ID, SC Encyclopedia ID (wd:P7690 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): identifier for an entry on the South Carolina Encyclopedia website
7. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): identifier for an article in the online version of Encyclopædia Britannica
8. World History Encyclopedia ID, also known as Ancient History Encyclopedia ID (wd:P9000 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): alphabetical identifier for an article in the World History Encyclopedia (former Ancient History Encyclopedia)
9. Encyclopedia of Ideas ID, also known as EI id (wd:P10717 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): Hebrew-language encyclopedia describing philosophical ideas in daily life
10. Literary Encyclopedia ID (wd:P9001 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): identifier in Soviet Literary Encyclopedia (1929-1939)

[Assistant]
The property for Encyclopedia of Life ID is wd:P830.

Step 2: I will now search for the class "taxon" to identify the taxon entity.

[Tool]
Top 10 entity alternatives:
1. taxon, also known as taxa, taxonomic unit (wd:Q16521): group of one or more organism(s), which a taxonomist adjudges to be a unit
2. Taxon, also known as Taxon. The Journal of the Intern...l Association for Plant Taxonomy (wd:Q2003024): academic journal
3. TaxOn, also known as ISSN 2079-1380 (wd:Q21386141): scientific journal
4. ¡Taxon! (wd:Q96184500): scientific article published in 1993
5. taxon (wd:L20987)
6. taxon (wd:L20987-F1)
7. taxon (wd:L34573-S1)
8. taxon (wd:L745006-S3)
9. biological classification, also known as biological and zoological classification, classification of organisms, scientific classification, taxonomic classification, taxonomy (wd:Q11398): method of scientific taxonomy
10. extinction, also known as dying out, taxon extinction, species extinctions, species extinction, going extinct (wd:Q123509): termination of a taxon by the death of its last member

[Assistant]
The class for taxon is wd:Q16521.

Step 3: I will now write a SPARQL query to find distinct items that have an Encyclopedia of Life ID (wdt:P830) but are not instances of taxon (wd:Q16521) or subclasses of taxon. I will also include the labels of the items and the labels of what the items are instances of.

[Tool]
Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| item                                                    | itemLabel                                     | instanceOf                                              | instanceOfLabel                               |
| ------------------------------------------------------- | --------------------------------------------- | ------------------------------------------------------- | --------------------------------------------- |
| Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) (en) | later homonym (wd:Q17276484)                            | later homonym (en)                            |
| Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) (en) | Oecophoridae (wd:Q782541)                               | Oecophoridae (en)                             |
| Notaspis Warren (1892) (wd:Q10337670)                   | Notaspis Warren (1892) (en)                   | Crambidae (wd:Q132980)                                  | Crambidae (en)                                |
| Notaspis Warren (1892) (wd:Q10337670)                   | Notaspis Warren (1892) (en)                   | later homonym (wd:Q17276484)                            | later homonym (en)                            |
| Catenella Bat. & Peres (1963) (wd:Q10443855)            | Catenella Bat. & Peres (1963) (en)            | later homonym (wd:Q17276484)                            | later homonym (en)                            |
| ...                                                     | ...                                           | ...                                                     | ...                                           |
| Copriodes perinephela (wd:Q13496844)                    | Copriodes perinephela (en)                    | unavailable combination (wd:Q17487588)                  | unavailable combination (en)                  |
| Copriodes polynephela (wd:Q13496845)                    | Copriodes polynephela (en)                    | Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) (en) |
| Copriodes polynephela (wd:Q13496845)                    | Copriodes polynephela (en)                    | unavailable combination (wd:Q17487588)                  | unavailable combination (en)                  |
| Doclea syntomoides (wd:Q13592892)                       | Doclea syntomoides (en)                       | unavailable combination (wd:Q17487588)                  | unavailable combination (en)                  |
| Doclea syntomoides (wd:Q13592892)                       | Doclea syntomoides (en)                       | Doclea Walker (1865) non Leach (1815) (wd:Q18522853)    | Doclea Walker (1865) non Leach (1815) (en)    |

[Assistant]
The query results show distinct items that have an Encyclopedia of Life ID but are not instances of taxons or subclasses of taxons. The results include the item labels and the labels of what the items are instances of.

I will now provide the final SPARQL query and the explanation to the user.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?award ?awardLabel ( COUNT( ?award ) AS ?count ) WHERE {
  ?person wdt:P9044 ?geprisID .
  ?person wdt:P166 ?award .
  ?award rdfs:label ?awardLabel .
  FILTER ( LANG( ?awardLabel ) = "en" ) ?award ( wdt:P31 / wdt:P279 * ) ?awardType .
  VALUES ?awardType {
    wd:Q11448906 wd:Q618779 wd:Q15383322 wd:Q107471279 wd:Q378427 wd:Q107494520 wd:Q1709894
  }
}
GROUP BY ?award ?awardLabel
ORDER BY DESC ( ?count )

Got 809 rows and 3 columns, showing the first 5 and last 5 rows below:
| award                                                                              | awardLabel                                                               | count         |
| ---------------------------------------------------------------------------------- | ------------------------------------------------------------------------ | ------------- |
| Goethe Medal for Art and Science (wd:Q1396769)                                     | Goethe Medal for Art and Science (en)                                    | 486 (xsd:int) |
| Pour le Mérite for Sciences and Arts order (wd:Q15056034)                          | Pour le Mérite for Sciences and Arts order (en)                          | 474 (xsd:int) |
| Commander's Cross of the Order o... the Federal Republic of Germany (wd:Q10905276) | Commander's Cross of the Order o... the Federal Republic of Germany (en) | 341 (xsd:int) |
| National Prize of East Germany (wd:Q449353)                                        | National Prize of East Germany (en)                                      | 224 (xsd:int) |
| Bavarian Maximilian Order for Science and Art (wd:Q565030)                         | Bavarian Maximilian Order for Science and Art (en)                       | 205 (xsd:int) |
| ...                                                                                | ...                                                                      | ...           |
| doctor honoris causa from the Pierre and Marie Curie University (wd:Q26270762)     | doctor honoris causa from the Pierre and Marie Curie University (en)     | 1 (xsd:int)   |
| Grand Cross of the National Order of the Lion (wd:Q26242431)                       | Grand Cross of the National Order of the Lion (en)                       | 1 (xsd:int)   |
| Fellow of the Royal College of Physicians of London (wd:Q26204035)                 | Fellow of the Royal College of Physicians of London (en)                 | 1 (xsd:int)   |
| Fellow of the Royal Astronomical Society (wd:Q26111565)                            | Fellow of the Royal Astronomical Society (en)                            | 1 (xsd:int)   |
| Wolfgang Amadeus Mozart Prize (wd:Q2589008)                                        | Wolfgang Amadeus Mozart Prize (en)                                       | 1 (xsd:int)   |

The query retrieves the different types of awards received by individuals listed in the GEPRIS Historisch database, filtered to include only specific types such as general awards, science awards, cultural prizes, chemistry awards, literary awards, physics awards, and journalism prizes. It also provides the labels and the count of each award type.

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

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

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

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

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

[User] What are the different types of awards received by individuals listed in the GEPRIS Historisch database, along with their labels and the count of each award? The awards should be filtered to include only specific types such as general awards, science awards, cultural prizes, chemistry awards, literary awards, physics awards, national academies, and journalism prizes.

[Assistant]
To answer this question, I need to identify the individuals listed in the GEPRIS Historisch database and then find the awards they have received. I also need to filter the awards to include only specific types such as general awards, science awards, cultural prizes, chemistry awards, literary awards, physics awards, national academies, and journalism prizes. Finally, I need to count the occurrences of each award type.

Step 1: Identify the entity for the GEPRIS Historisch database.
Step 2: Find individuals listed in this database.
Step 3: Find awards received by these individuals.
Step 4: Filter awards by the specified types.
Step 5: Count the occurrences of each award type and get their labels.

I will start by searching for the GEPRIS Historisch database entity in Wikidata.

[Tool]
Top 10 entity alternatives:
1. GEPRIS Historisch (wd:Q104599609): database of projects funded by German Research Foundation between 1920 and 1945
2. GEPRIS Historisch person ID (wd:P9044): identifier of a person in GEPRIS Historisch database of funded r...eutsche Forschungsgemeinschaft (DFG, German Research Foundation)
3. GEPRIS, also known as German Project Information System (wd:Q48879895): database of projects funded by German Research Foundation (DFG)
4. WordGraph - Development of a uni...uiring lexico-semantic phenomena, also known as GEPRIS, Word Graph (wd:Q116122602): 2007-2018 German Research Foundation linguistics research project
5. Historisches Lexikon des Fürstentums Liechtenstein, also known as Historical Lexicon of the Principality of Liechtenstein, historisches-lexikon.li, HLFL (wd:Q59035927): encyclopedia on the history of Liechtenstein
6. Former city hall of Halle, also known as Historisch Stadhuis, Oud Stadhuis, Renaissancestadhuis, Stadhuis (wd:Q2284117): former city hall of Halle, Belgium
7. Historisch Nieuwsblad (wd:Q21008985)
8. Historisch Centrum, also known as historic center of Antwerp, Antwerp historic center (wd:Q64685207): historic center of Antwerp, Belgium
9. Wegweiser historisch (wd:Q41174096)
10. Historisch Goor (wd:Q110891771)

[Assistant] The GEPRIS Historisch database is identified as wd:Q104599609 in Wikidata. Next, I need to find individuals listed in this database. The property "GEPRIS Historisch person ID" (wd:P9044) seems relevant for identifying individuals in this database. I will now search for individuals with this property.

[Tool]
Got 10,902 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                                | object  |
| ----------------------------- | --------------------------------------- | ------- |
| Albert Einstein (wd:Q937)     | GEPRIS Historisch person ID (wdt:P9044) | 5140127 |
| Max Planck (wd:Q9021)         | GEPRIS Historisch person ID (wdt:P9044) | 5140060 |
| David Hilbert (wd:Q41585)     | GEPRIS Historisch person ID (wdt:P9044) | 5105019 |
| Konrad Adenauer (wd:Q2492)    | GEPRIS Historisch person ID (wdt:P9044) | 5140086 |
| Martin Heidegger (wd:Q48301)  | GEPRIS Historisch person ID (wdt:P9044) | 5140159 |
| Werner Heisenberg (wd:Q40904) | GEPRIS Historisch person ID (wdt:P9044) | 5104724 |
| Karl Popper (wd:Q81244)       | GEPRIS Historisch person ID (wdt:P9044) | 5109323 |
| Max Born (wd:Q58978)          | GEPRIS Historisch person ID (wdt:P9044) | 5101250 |
| Heinrich Himmler (wd:Q43067)  | GEPRIS Historisch person ID (wdt:P9044) | 5140029 |
| Philipp Lenard (wd:Q57063)    | GEPRIS Historisch person ID (wdt:P9044) | 5107236 |
| ...                           | ...                                     | ...     |

[Assistant]
I have found individuals listed in the GEPRIS Historisch database using the property GEPRIS Historisch person ID (wdt:P9044). Now, I will find the awards received by these individuals. Awards are typically represented by the property "award received" (wdt:P166) in Wikidata. I will query the awards received by individuals with the GEPRIS Historisch person ID property.

After that, I will filter the awards to include only the specified types: general awards, science awards, cultural prizes, chemistry awards, literary awards, physics awards, national academies, and journalism prizes. I will identify these award types by their subclasses or instance of relationships.

I will start by querying the awards received by individuals with the GEPRIS Historisch person ID property.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant]
The query failed because the SERVICE wikibase:label is not supported by the used QLever SPARQL endpoint. I will rewrite the query to get the labels using rdfs:label instead and filter for English labels.

I will now execute the revised query to get the awards received by individuals with the GEPRIS Historisch person ID property along with their labels and counts.

[Tool]
Got 822 rows and 3 columns, showing the first 5 and last 5 rows below:
| award                                                                              | awardLabel                                                               | count         |
| ---------------------------------------------------------------------------------- | ------------------------------------------------------------------------ | ------------- |
| Commander's Cross of the Order o... the Federal Republic of Germany (wd:Q10905276) | Commander's Cross of the Order o... the Federal Republic of Germany (en) | 341 (xsd:int) |
| Goethe Medal for Art and Science (wd:Q1396769)                                     | Goethe Medal for Art and Science (en)                                    | 162 (xsd:int) |
| Officer's Cross of the Order of ... the Federal Republic of Germany (wd:Q10905334) | Officer's Cross of the Order of ... the Federal Republic of Germany (en) | 129 (xsd:int) |
| National Prize of East Germany (wd:Q449353)                                        | National Prize of East Germany (en)                                      | 112 (xsd:int) |
| Bavarian Order of Merit (wd:Q672787)                                               | Bavarian Order of Merit (en)                                             | 101 (xsd:int) |
| ...                                                                                | ...                                                                      | ...           |
| Orden de la Independencia Cultural Rubén Darío (wd:Q3885401)                       | Orden de la Independencia Cultural Rubén Darío (en)                      | 1 (xsd:int)   |
| Order of Valour (wd:Q3885253)                                                      | Order of Valour (en)                                                     | 1 (xsd:int)   |
| National Order of Madagascar (wd:Q3885159)                                         | National Order of Madagascar (en)                                        | 1 (xsd:int)   |
| Order of José Matías Delgado (wd:Q3885158)                                         | Order of José Matías Delgado (en)                                        | 1 (xsd:int)   |
| honorary doctorate of the University of Valladolid (wd:Q38810578)                  | honorary doctorate of the University of Valladolid (en)                  | 1 (xsd:int)   |

[Assistant]
I have retrieved a list of awards received by individuals listed in the GEPRIS Historisch database along with their labels and counts. Now, I need to filter these awards to include only specific types such as general awards, science awards, cultural prizes, chemistry awards, literary awards, physics awards, national academies, and journalism prizes.

To do this, I will identify the subclasses or instance of relationships for these awards and filter accordingly. I will start by searching for the subclasses or instance of relationships for the first few awards to understand their types.

[Tool]
Got 1 row and 3 columns:
| subject                                                                            | property              | object                           |
| ---------------------------------------------------------------------------------- | --------------------- | -------------------------------- |
| Commander's Cross of the Order o... the Federal Republic of Germany (wd:Q10905276) | instance of (wdt:P31) | grade of an order (wd:Q60754876) |

[Tool]
Got 2 rows and 3 columns:
| subject                                        | property              | object                  |
| ---------------------------------------------- | --------------------- | ----------------------- |
| Goethe Medal for Art and Science (wd:Q1396769) | instance of (wdt:P31) | medallion (wd:Q131647)  |
| Goethe Medal for Art and Science (wd:Q1396769) | instance of (wdt:P31) | art prize (wd:Q1792571) |

[Tool]
Got 2 rows and 3 columns:
| subject                                     | property              | object                         |
| ------------------------------------------- | --------------------- | ------------------------------ |
| National Prize of East Germany (wd:Q449353) | instance of (wdt:P31) | award (wd:Q618779)             |
| National Prize of East Germany (wd:Q449353) | instance of (wdt:P31) | state decoration (wd:Q3302125) |

[Assistant]
The awards have various instance of types such as "grade of an order," "medallion," "art prize," "award," and "state decoration." To filter the awards by the specified types (general awards, science awards, cultural prizes, chemistry awards, literary awards, physics awards, national academies, and journalism prizes), I need to identify the corresponding Wikidata classes or categories for these types.

I will search for these categories in Wikidata to use them as filters in the query. I will start by searching for "science award" and then proceed with the other types.

[Tool]
Top 10 entity alternatives:
1. science award, also known as award in science, award (science), science prize, scientific award, scientific prize (wd:Q11448906): award for science
2. Mahathir Science Award (wd:Q106960581): Award named after Mahathir Mohamad
3. GCSE Science, also known as Single Award Science (wd:Q7523823): British educational qualification
4. Suffrage Science award (wd:Q56765711): Prize for women in science, engineering and computing
5. Berlin Science Award (wd:Q821879)
6. Finnish Science Award (wd:Q11895129): Finnish award, granted biannually by the Ministry of Education and Culture
7. India Science Award (wd:Q6019402)
8. Korea Science Award (wd:Q19483802): South Korean award
9. Science Writing Award (wd:Q6084965): Award for excellence in writing about science
10. Ammodo Science Award for Fundamental Research, also known as Ammodo KNAW award, Ammodo Science Award (wd:Q28725741): Dutch award

[Tool]
Top 10 entity alternatives:
1. General Heusinger Award (wd:Q1501515): award
2. GENERAL practitioner's award (wd:Q75502979): scientific article published on 01 December 1950
3. GENERAL practitioner's award (wd:Q75852621): scientific article published on 01 December 1951
4. Governor General's Awards, also known as Governor General's Award (wd:Q283256): Canadian academic, artistic, and social awards
5. ANNUAL General Practitioner's Award (wd:Q74007715): scientific article published on 01 December 1952
6. ANNUAL general Practitioner's Award (wd:Q73333286): scientific article published on 01 December 1953
7. General medical nursing award (wd:Q120749915): scientific article published in 1996
8. Governor General's Literary Awards, also known as Dominion Literary Awards, GGBooks, Governor General's Literary Award (wd:Q3405963): Canadian literary award
9. General Maxwell R. Thurman Award (wd:Q5532018)
10. MFO Director General's Award (wd:Q17131651)

[Tool]
Top 10 entity alternatives:
1. cultural prize, also known as cultural award, culture prize (wd:Q15383322): type of award in the field of culture
2. Faroese Cultural Prize, also known as Heiðurgáva landsins, Mentanarvirðisløn Landsins, Faroese Prize for Young Artist, Faroese Life Achievement Award, Faroese Cultural Award (wd:Q800098): Faroese annual cultural award given by the Faroese government to Faroese writers, musicians, artists, film directors etc.
3. Hessian Cultural Prize (wd:Q1615933): The cultural prize instituted in 1981 by the state government of Hesse, Germany
4. Manor Cultural Prize, also known as le Prix Culturel Manor, Prix Manor (wd:Q1891015): Swiss award for visual artists
5. Würzburg Cultural Prize (wd:Q1320081): cultural award in Germany
6. Vantaa cultural prize, also known as Vantaa cultural award, Vantaa culture prize, Vantaa culture award (wd:Q25454289): Finnish culture award
7. Tezuka Osamu Cultural Prize (wd:Q1336528): award
8. Mainichi Publication Culture Award, also known as Mainchi Cultural prizes, Mainichi Publishing Culture Award, Mainichi Shuppan Bunkasho (wd:Q1554156): Japanese award
9. Georg Dehio Cultural Prize (wd:Q17511309)
10. The Greenlandic Cultural Prize (wd:Q66108319)

[Tool]
Top 10 entity alternatives:
1. chemistry award (wd:Q107471279): academic award to recognize achievements in chemistry
2. Bioinorganic Chemistry Award (wd:Q18560138): award granted by the Royal Society of Chemistry
3. Green Chemistry Award (wd:Q18560158): award granted by the Royal Society of Chemistry
4. Dream Chemistry Award (wd:Q78938012): award
5. Supramolecular Chemistry Award (wd:Q18560203): award granted by the Royal Society of Chemistry
6. Bioorganic Chemistry Award, also known as RSC Bioorganic Chemistry Award (wd:Q18560139): award granted by the Royal Society of Chemistry
7. Organometallic Chemistry Award (wd:Q18560189): award granted by the Royal Society of Chemistry
8. Medicinal Chemistry Award (wd:Q56669328): award of the Royal Society of Chemistry (1971-2005)
9. Welch Award in Chemistry, also known as Robert A. Welch Award, Robert A. Welch Award in Chemistry, Welch Award (wd:Q1632244): American chemistry prize (1972-)
10. Applied Inorganic Chemistry Award (wd:Q18560129): award granted by the Royal Society of Chemistry

[Tool]
Top 10 entity alternatives:
1. literary award, also known as book award, book prize, literary prize, literature award, literature prize (wd:Q378427): award for writers, literary associations and literary works
2. literary award (wd:L494575-S4)
3. Lambda Literary Award, also known as Lambdas, Lammies (wd:Q594550): award for published works which celebrate or explore LGBT themes
4. SAARC Literary Award (wd:Q17126068): literary award given by SAARC's literary wing to the writers from SAARC countries
5. Daesan Literary Award (wd:Q11232367)
6. Aftonbladet Literary Award (wd:Q2684629): Swedish literary award
7. Dong-in Literary Award (wd:Q623969): award
8. Rancage Literary Award (wd:Q7475785): Indonesian literary award
9. Yookwoodang Literary Award (wd:Q23718746): literary award
10. Adamjee Literary Award, also known as Adamjee Award, Adam Jee Award, Adam Jee Literary Award (wd:Q19582542): Pakistan's literary prize

[Tool]
Top 10 entity alternatives:
1. physics award (wd:Q107494520): type of award
2. Wang Ganchang Physics Award (wd:Q48911119)
3. Institute of Physics Awards (wd:Q85769551): list of IOP medals and prizes
4. Excellence in Physics Education Award (wd:Q110867751): annual award of the American Physical Society
5. Dissertation Award in Nuclear Physics, also known as DNP Dissertation Award (wd:Q125210599): award of the American Physical Society
6. Physics award acclaims superfluid helium (wd:Q60088654): scientific article published in Nature
7. Physics Award for Tunnelling Research (wd:Q59052992): scientific article published in Nature
8. Physics award yields high return (wd:Q80900982): scientific article published on 01 April 1990
9. Irving Langmuir Award in Chemical Physics, also known as Irving Langmuir Award (wd:Q901579): award for interdisciplinary research in chemistry and physics
10. Bertram Eugene Warren Diffraction Physics Award, also known as Eugene Warren Award, Warren Award (wd:Q123436651): American award in physics

[Tool]
Top 10 entity alternatives:
1. national academy, also known as National Academy of Video Game Trade Reviewers Awards (wd:Q1966910): organizational body, usually operating with state financial supp...iplines, most frequently in the sciences but also the humanities
2. National Defence Academy, also known as Indian National Defence Academy, NDA (wd:Q3630909): Defence training institute of Indian armed forces
3. TCIFA National Academy (wd:Q1354743): sports venue
4. National Sports Academy, also known as National Sports Academy Vasil Levski, National Sports Academy Vassil Levski, NSA Vasil Levski, National Institute of Physical Education Vassil Levski (wd:Q6978640): college in Sofia, Bulgaria
5. Central Guoshu Institute, also known as National Martial Arts Academy, National Wushu Academy (wd:Q2274126): a martial arts academy
6. National Virgilian Academy, also known as Accademia Nazionale Virgiliana (wd:Q139860): academy of sciences
7. National Academies Press, also known as The National Academies Press, National Academy Press (wd:Q6970107): organization in Washington D.C., United States
8. Singapore NFA U-18, also known as National Football Academy (wd:Q7523054)
9. Talysh National Academy (wd:Q105080371)
10. National Judicial Academy (wd:Q6973888): judicial training wing of India

[Tool]
Top 10 entity alternatives:
1. journalism prize, also known as journalism award, journalist prize (wd:Q1709894): type of award for journalism
2. Sami Journalism Prize (wd:Q10660928): Swedish journalism prize (2009-)
3. «Colombine» Journalism Prize (wd:Q87477513)
4. European Parliament Journalism Prize (wd:Q1993482)
5. Lorenzo Natali Journalism Prize (wd:Q6680780): Annual journalism award
6. Stora Journalistpriset, also known as Grand Prize for Journalism (wd:Q3436850): Swedish journalism prize (1966-)
7. National Prize for Journalism (wd:Q11942619): award granted by the Government of Catalonia
8. American Mosaic Journalism Prize (wd:Q112570785): Journalism award
9. Grand Prize for Journalism, also known as Journalist Award, Journalist award of Finland (wd:Q11854492): annual Finnish journalist award given by the Association of Finnish Chief Journalists (2001-)
10. Miguel Delibes Journalism Prize (wd:Q9062329)

[Assistant]
I have identified the following Wikidata entities for the specified award types:
- Science award: wd:Q11448906
- General award: No single entity, but can consider "award" (wd:Q618779) as general
- Cultural prize: wd:Q15383322
- Chemistry award: wd:Q107471279
- Literary award: wd:Q378427
- Physics award: wd:Q107494520
- National academy: wd:Q1966910 (though this is an organizational body, not an award)
- Journalism prize: wd:Q1709894

I will now construct a SPARQL query to get the awards received by individuals listed in the GEPRIS Historisch database, filter the awards to include only those that are instances or subclasses of the above categories, and count the occurrences of each award along with their labels.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?item WHERE {
  ?item rdfs:label "Коломия" @uk .
}

The items that have the label "Коломия" in Ukrainian are: wd:Q16702144, wd:Q1841153, wd:Q20077869, wd:Q52193, and wd:Q9270646. However, none of these items have the official name property with the value "Коломия" in Ukrainian explicitly set.

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

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

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

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

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

[User] Which items have the official name "Коломия" in Ukrainian?

[Assistant]
The user is asking for items that have the official name "Коломия" in Ukrainian.

Step 1: Determine entities and properties.
- The property "official name" is likely represented in Wikidata by property P1448 (official name).
- The language "Ukrainian" can be represented by the language code "uk" or the entity wd:Q879 (Ukrainian language).
- The value "Коломия" is a string literal in Ukrainian.

Step 2: Construct a SPARQL query that finds items with the official name "Коломия" in Ukrainian.

The official name property (P1448) can have a value with a language tag. We want to find items where the official name is "Коломия"@uk.

Step 3: Write the SPARQL query.

We want to select items ?item where ?item wdt:P1448 ?name and ?name = "Коломия"@uk.

Step 4: Execute the query to check if it returns results.

I will now write the query and execute it.

[Tool] Got no rows and 1 columns

[Assistant]
No results were returned for the official name "Коломия" in Ukrainian using the direct property wdt:P1448. It is possible that the official name is stored as a statement with qualifiers or in a different way.

Step 5: Try to find the property "official name" in Wikidata to confirm its identifier.

I will search for the property "official name" in Wikidata.

[Tool]
Top 10 property alternatives:
1. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): label for the items in their official language  or their original language, name
2. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): official name of the subject in its official language(s), name
3. officialized by, also known as made official by, officialised by (wd:P5194 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): the item which officialized this lexeme
4. short name, also known as short title, shortname, abbreviation, shortened name, initialism (wd:P1813 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): short name of a place, organisation, person, journal, wikidata property, etc. Used by some Wikipedia templates., name
5. official symbol, also known as symbol, state tartan, official tartan, floral emblem, official emblem (wd:P2238 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): official symbol of an organisation
6. nickname, also known as informal name, moniker, other name, othername, other_names (wd:P1449 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): informal name (for a pseudonym use P742), name
7. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): 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
8. anthem, also known as national anthem, team anthem, official song, official hymn, club anthem (wd:P85 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): subject's official anthem
9. courtesy name, also known as courtesy name, style name, zi (wd:P1782 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): name bestowed upon a person at adulthood in addition to one's given name, mostly in East Asia, name
10. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as prv/wdtn/pqn/prn/pr/psn/pq/wdt/pqv/p/ps/psv): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name

[Assistant]
The property official name is indeed wd:P1448, which matches our initial assumption.

Step 6: Since the direct query with wdt:P1448 did not return results, try to query the statement form (ps:P1448) with the value and language tag.

I will write a query to find items where the statement value of P1448 is "Коломия"@uk.

[Tool] Got no rows and 1 columns

[Assistant]
No results were found even when querying the statement form of the official name property with the value "Коломия" in Ukrainian.

Step 7: Consider that the official name might be stored as a label or alias in Ukrainian rather than as an official name property.

I will try to find items with the label "Коломия" in Ukrainian.

[Tool]
Got 5 rows and 1 column:
| item                                          |
| --------------------------------------------- |
| wd:Q16702144                                  |
| Kołomyja, Podlaskie Voivodeship (wd:Q1841153) |
| Kolomyia (wd:Q20077869)                       |
| Kolomyia (wd:Q52193)                          |
| wd:Q9270646                                   |

[Assistant]
There are 5 items with the label "Коломия" in Ukrainian. Some of them have labels in English or other languages that suggest they are related to Kolomyia.

Step 8: Check if any of these items have the official name "Коломия" in Ukrainian as a property.

I will now check for each of these items if they have the official name property (P1448) with the value "Коломия" in Ukrainian.

[Tool] Got no rows and 1 columns

[Assistant]
None of the items with the Ukrainian label "Коломия" have the official name property "Коломия" in Ukrainian.

Step 9: Since the user specifically asked for items with the official name "Коломия" in Ukrainian, and no direct official name property matches were found, I will return the items that have the label "Коломия" in Ukrainian as the closest relevant answer.

I will prepare the final answer with these items.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?secondLevelParentOrg ?secondLevelParentOrgLabel WHERE {
  wd:Q1318441 wdt:P749 ?parentOrg .
  ?parentOrg wdt:P749 ?secondLevelParentOrg .
  OPTIONAL {
    ?secondLevelParentOrg rdfs:label ?secondLevelParentOrgLabel FILTER ( LANG( ?secondLevelParentOrgLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| secondLevelParentOrg         | secondLevelParentOrgLabel |
| ---------------------------- | ------------------------- |
| Alphabet Inc. (wd:Q20800404) | Alphabet Inc. (en)        |

The second-level parent organization of AdMob is Alphabet Inc.

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

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

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

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

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

[User] What is the second-level parent organization of AdMob, the mobile advertising company?

[Assistant] To answer the question about the second-level parent organization of AdMob, I will first identify the entity for "AdMob" in Wikidata. Then, I will look for its parent organization and subsequently the parent organization of that parent organization to find the second-level parent organization. Let's start by searching for the entity "AdMob."

[Tool]
Top 10 entity alternatives:
1. AdMob (wd:Q1318441): mobile advertising company

[Assistant] I found the entity for AdMob as wd:Q1318441. Next, I will look for the parent organization of AdMob. The property for parent organization in Wikidata is usually "P749" (parent organization). I will list the parent organizations of AdMob.

[Tool]
Got 1 row and 3 columns:
| subject             | property                       | object          |
| ------------------- | ------------------------------ | --------------- |
| AdMob (wd:Q1318441) | parent organization (wdt:P749) | Google (wd:Q95) |

[Assistant] The parent organization of AdMob (wd:Q1318441) is Google (wd:Q95). Now, I will find the parent organization of Google to determine the second-level parent organization of AdMob.

[Tool]
Got 1 row and 3 columns:
| subject         | property                       | object                       |
| --------------- | ------------------------------ | ---------------------------- |
| Google (wd:Q95) | parent organization (wdt:P749) | Alphabet Inc. (wd:Q20800404) |

[Assistant] The parent organization of Google (wd:Q95) is Alphabet Inc. (wd:Q20800404). Therefore, the second-level parent organization of AdMob is Alphabet Inc. I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?occupation ?occupationLabel ?subclass ?subclassLabel WHERE {
  {
    ?occupation wdt:P279 wd:Q639669 .
    OPTIONAL {
      ?subclass wdt:P279 ?occupation .
      OPTIONAL {
        ?subclass rdfs:label ?subclassLabel FILTER ( LANG( ?subclassLabel ) = "en" )
      }
    }
    OPTIONAL {
      ?occupation rdfs:label ?occupationLabel FILTER ( LANG( ?occupationLabel ) = "en" )
    }
  }
}
ORDER BY ?occupationLabel ?subclassLabel

The SPARQL query retrieves distinct occupations related to the musical profession (musician) along with their subclasses if available. It returns the occupation and subclass IRIs and their English labels. This provides a hierarchy of musical occupations and their more specific subclasses.

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

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

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

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

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

[User] What are the distinct occupations related to the musical profession, along with their subclasses (if available)?

[Assistant]
To answer this question, I need to identify occupations related to the musical profession and then find their subclasses if available.

Step 1: Identify the entity for "musical profession" or "musician" or related concept.
Step 2: Find occupations related to this entity.
Step 3: Find subclasses of these occupations.

I will start by searching for the entity "musical profession" or "musician" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. musician, also known as musical artist (wd:Q639669): person who composes, conducts or performs music
2. Musician (wd:Q6942594): monthly magazine that covered news and information about American popular music
3. Musician (wd:Q108502747): 2021 single by Porter Robinson
4. Dj Faith India, also known as Musician (wd:Q122975649): Musical Artist, musician
5. musician (wd:Q133269746)
6. Musician (wd:Q6942591): video game for the Philips Videopac
7. Musician (wd:Q6942592): occupational rating in the United States Navy
8. Musician, also known as Mus (wd:Q6942593): rank equivalent to Private held by members of the Corps of Army Music of the British Army and the Royal Marines Band Service
9. Kevlar Siickk, also known as Musician (wd:Q116672182): musician, Musician
10. Keletso Merafe, also known as Musician (wd:Q125536491): musician, Tyte

[Assistant]
The entity "musician" (wd:Q639669) is defined as a person who composes, conducts, or performs music. This seems to be the most relevant entity for the musical profession.

Next, I will look for occupations related to the musical profession. Since "musician" is itself an occupation, I will search for subclasses of "musician" to find more specific musical occupations.

I will now search for subclasses of the occupation "musician" (wd:Q639669).

[Tool]
Got 159 rows and 2 columns, showing the first 5 and last 5 rows below:
| subclass                            | subclassLabel             |
| ----------------------------------- | ------------------------- |
| principal trumpet (wd:Q100431014)   | principal trumpet (en)    |
| hip-hop musician (wd:Q100493654)    | hip-hop musician (en)     |
| jōrurikatari (wd:Q100951393)        | jōrurikatari (en)         |
| folk musician (wd:Q101084010)       | folk musician (en)        |
| pop musician (wd:Q102277154)        | pop musician (en)         |
| ...                                 | ...                       |
| fado musician (wd:Q88821468)        | fado musician (en)        |
| film accompanist (wd:Q9355558)      | film accompanist (en)     |
| chipmusician (wd:Q96573927)         | chipmusician (en)         |
| reggae musician (wd:Q98523719)      | reggae musician (en)      |
| son jarocho musician (wd:Q98567931) | son jarocho musician (en) |

[Assistant]
I found 159 subclasses of the occupation "musician" which represent distinct musical professions. Examples include hip-hop musician, folk musician, pop musician, fado musician, film accompanist, chipmusician, reggae musician, and son jarocho musician.

Next, I will check if these subclasses themselves have further subclasses to provide a more complete hierarchy of musical occupations.

I will query for subclasses of these subclasses.

[Tool]
Got 410 rows and 3 columns, showing the first 5 and last 5 rows below:
| subsubclass                                | subsubclassLabel                | parent                            |
| ------------------------------------------ | ------------------------------- | --------------------------------- |
| tango singer (wd:Q100269042)               | tango singer (en)               | singer (wd:Q177220)               |
| principal trumpet (wd:Q100431014)          | principal trumpet (en)          | classical musician (wd:Q81729632) |
| flûte à trois trous player (wd:Q100539888) | flûte à trois trous player (en) | instrumentalist (wd:Q1278335)     |
| jōrurikatari (wd:Q100951393)               | jōrurikatari (en)               | vocalist (wd:Q2643890)            |
| operatic vocalist (wd:Q101436559)          | operatic vocalist (en)          | vocalist (wd:Q2643890)            |
| ...                                        | ...                             | ...                               |
| sufi singer (wd:Q99510107)                 | sufi singer (en)                | singer (wd:Q177220)               |
| livđejeijee (wd:Q99535287)                 | livđejeijee (en)                | singer (wd:Q177220)               |
| wd:Q99535397                               |                                 | singer (wd:Q177220)               |
| santurist (wd:Q99576286)                   | santurist (en)                  | instrumentalist (wd:Q1278335)     |
| organist in residence (wd:Q99982121)       | organist in residence (en)      | organist (wd:Q765778)             |

[Assistant]
I found 410 subclasses of the subclasses of "musician," representing a more detailed hierarchy of musical occupations. These include specific roles like tango singer, principal trumpet, flûte à trois trous player, jōrurikatari, operatic vocalist, sufi singer, santurist, and organist in residence.

Now I will construct a SPARQL query that returns the distinct occupations related to the musical profession (musician) along with their subclasses if available. The query will return the occupation, its label, the subclass, and the subclass label. If there are no subclasses, the occupation itself will be returned.

I will write the query to get all subclasses of musician and their subclasses (if any).

[Tool] Stopped generation process