PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?person ?youtubeChannel ?followers WHERE {
  ?person wdt:P106 wd:Q17125263 ; wdt:P106 wd:Q15143191 ; wdt:P2397 ?youtubeChannel .
  OPTIONAL {
    ?person wdt:P6168 ?followers
  }
  FILTER NOT EXISTS {
    ?person wdt:P18 []
  }
}
ORDER BY DESC ( ?followers )
LIMIT 10

Got 7 rows and 3 columns:
| ?person                                  | ?youtubeChannel          | ?followers |
| ---------------------------------------- | ------------------------ | ---------- |
| Henrique Abrahão Charles (wd:Q104882878) | UCxSbDOAmDA9xSDd3Numjsmg |            |
| Rocío Vidal (wd:Q105038628)              | UCoXtmmnLCbXDiSo8GxsmOzA |            |
| Valentine Delattre (wd:Q118744878)       | UCE_LWXcsdp7cWbo4DR4ZA-A |            |
| Willy Guasti (wd:Q119828705)             | UCyD1TlHPTq-H9dvQC3tr0zw |            |
| Stefano Vendrame (wd:Q123058549)         | UCuCdPgseAOAS_ZWgUeIlFNg |            |
| Samuel Buisseret (wd:Q124427586)         | UCh2YBKhYIy-_LtfCIn2Jycg |            |
| Mario Peláez-Fernández (wd:Q65073470)    | UCipVtSaV6OOKk8VTMcHt71Q |            |

- Henrique Abrahão Charles (wd:Q104882878) - YouTube Channel: UCxSbDOAmDA9xSDd3Numjsmg
- Rocío Vidal (wd:Q105038628) - YouTube Channel: UCoXtmmnLCbXDiSo8GxsmOzA
- Valentine Delattre (wd:Q118744878) - YouTube Channel: UCE_LWXcsdp7cWbo4DR4ZA-A
- Willy Guasti (wd:Q119828705) - YouTube Channel: UCyD1TlHPTq-H9dvQC3tr0zw
- Stefano Vendrame (wd:Q123058549) - YouTube Channel: UCuCdPgseAOAS_ZWgUeIlFNg
- Samuel Buisseret (wd:Q124427586) - YouTube Channel: UCh2YBKhYIy-_LtfCIn2Jycg
- Mario Peláez-Fernández (wd:Q65073470) - YouTube Channel: UCipVtSaV6OOKk8VTMcHt71Q

Note: The number of social media followers is not available for these individuals in the knowledge graph.

[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, we need to identify the relevant entities and properties in the knowledge graph. We are looking for individuals who are both YouTubers and science communicators and do not have an image. Additionally, we want to include their YouTube channel ID and the number of social media followers, if available, and order the results by the number of social media followers in descending order.

Let's start by identifying the properties and classes that might be relevant:
1. **YouTube channel ID**: This is likely represented by the property `P2397` (YouTube channel ID).
2. **Number of social media followers**: This is likely represented by the property `P6168` (number of social media followers).
3. **Image**: This is likely represented by the property `P18` (image).
4. **Occupation**: This is likely represented by the property `P106` (occupation), where we can look for the occupations "YouTuber" and "science communicator".

First, let's search for the entities "YouTuber" and "science communicator" to get their IRIs.

[Tool]
No entity items found

No other items found

[Assistant] It seems that the search for "YouTuber" did not yield any results. Let's try searching for "YouTuber" in a more general way, without constraining it to a specific type of entity.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

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

No other items found

[Assistant] The search for "YouTuber" returned several results, and the most relevant one is `wd:Q17125263`, which represents the occupation "YouTuber". Next, let's search for "science communicator" to get its IRI.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

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

No other items found

[Assistant]
The search for "science communicator" returned several results, and the most relevant one is `wd:Q15143191`, which represents the occupation "science communicator".

Now that we have the IRIs for "YouTuber" and "science communicator," we can construct a SPARQL query to find individuals who are both YouTubers and science communicators and do not have an image. We will also include their YouTube channel ID and the number of social media followers, if available, and order the results by the number of social media followers in descending order.

Let's start by constructing a basic query to find these individuals and their YouTube channel IDs.

[Tool]
Got 7 rows and 2 columns:
| ?person                                  | ?youtubeChannel          |
| ---------------------------------------- | ------------------------ |
| Henrique Abrahão Charles (wd:Q104882878) | UCxSbDOAmDA9xSDd3Numjsmg |
| Rocío Vidal (wd:Q105038628)              | UCoXtmmnLCbXDiSo8GxsmOzA |
| Valentine Delattre (wd:Q118744878)       | UCE_LWXcsdp7cWbo4DR4ZA-A |
| Willy Guasti (wd:Q119828705)             | UCyD1TlHPTq-H9dvQC3tr0zw |
| Stefano Vendrame (wd:Q123058549)         | UCuCdPgseAOAS_ZWgUeIlFNg |
| Samuel Buisseret (wd:Q124427586)         | UCh2YBKhYIy-_LtfCIn2Jycg |
| Mario Peláez-Fernández (wd:Q65073470)    | UCipVtSaV6OOKk8VTMcHt71Q |

[Assistant]
The initial query has successfully returned a list of individuals who are both YouTubers and science communicators and do not have an image, along with their YouTube channel IDs. Now, let's extend the query to include the number of social media followers, if available, and order the results by the number of social media followers in descending order.

We will use the property `P6168` (number of social media followers) to get this information.

[Tool]
Got 7 rows and 3 columns:
| ?person                                  | ?youtubeChannel          | ?followers |
| ---------------------------------------- | ------------------------ | ---------- |
| Henrique Abrahão Charles (wd:Q104882878) | UCxSbDOAmDA9xSDd3Numjsmg |            |
| Rocío Vidal (wd:Q105038628)              | UCoXtmmnLCbXDiSo8GxsmOzA |            |
| Valentine Delattre (wd:Q118744878)       | UCE_LWXcsdp7cWbo4DR4ZA-A |            |
| Willy Guasti (wd:Q119828705)             | UCyD1TlHPTq-H9dvQC3tr0zw |            |
| Stefano Vendrame (wd:Q123058549)         | UCuCdPgseAOAS_ZWgUeIlFNg |            |
| Samuel Buisseret (wd:Q124427586)         | UCh2YBKhYIy-_LtfCIn2Jycg |            |
| Mario Peláez-Fernández (wd:Q65073470)    | UCipVtSaV6OOKk8VTMcHt71Q |            |

[Assistant]
The extended query has returned the same list of individuals, but now it includes the number of social media followers, which are all null in this case. This suggests that the number of social media followers is not available for these individuals in the knowledge graph.

Since the number of social media followers is not available, we can still provide the list of individuals who are both YouTubers and science communicators and do not have an image, ordered by the number of social media followers (which will be in the default order since all values are null).

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

```sparql
SELECT ?person ?youtubeChannel ?followers WHERE {
  ?person wdt:P106 wd:Q17125263 ;
          wdt:P106 wd:Q15143191 ;
          wdt:P2397 ?youtubeChannel .
  OPTIONAL { ?person wdt:P6168 ?followers }
  FILTER NOT EXISTS { ?person wdt:P18 [] }
} ORDER BY DESC(?followers) LIMIT 10
```

Answer:
- Henrique Abrahão Charles (wd:Q104882878) - YouTube Channel: UCxSbDOAmDA9xSDd3Numjsmg
- Rocío Vidal (wd:Q105038628) - YouTube Channel: UCoXtmmnLCbXDiSo8GxsmOzA
- Valentine Delattre (wd:Q118744878) - YouTube Channel: UCE_LWXcsdp7cWbo4DR4ZA-A
- Willy Guasti (wd:Q119828705) - YouTube Channel: UCyD1TlHPTq-H9dvQC3tr0zw
- Stefano Vendrame (wd:Q123058549) - YouTube Channel: UCuCdPgseAOAS_ZWgUeIlFNg
- Samuel Buisseret (wd:Q124427586) - YouTube Channel: UCh2YBKhYIy-_LtfCIn2Jycg
- Mario Peláez-Fernández (wd:Q65073470) - YouTube Channel: UCipVtSaV6OOKk8VTMcHt71Q

Note: The number of social media followers is not available for these individuals in the knowledge graph.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?game ?gameLabel ?developer ?publisher ?publicationDate WHERE {
  ?game wdt:P31 wd:Q744038 .
  OPTIONAL {
    ?game wdt:P178 ?developer .
  }
  OPTIONAL {
    ?game wdt:P123 ?publisher .
  }
  OPTIONAL {
    ?game wdt:P577 ?publicationDate .
  }
  OPTIONAL {
    ?game rdfs:label ?gameLabel .
    FILTER ( LANG( ?gameLabel ) = "en" )
  }
}
ORDER BY DESC ( ?publicationDate )
LIMIT 200

The query returned only one role-playing video game with no developer, publisher, or publication date information. The game is Xeonjia (wd:Q111168061).

[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, we need to identify the items that are role-playing video games and then retrieve their developers, publishers, and publication dates. Let's start by finding the property that indicates a game is a role-playing video game.

I will search for the property that indicates a game is a role-playing video game.

[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. video game, also known as computer game, computer games, vg, videogame, videogames (wd:Q7889): electronic game with user interface and visual feedback
3. role-playing game, also known as role playing game, roleplaying game, role-playing games, RPG (wd:Q160738): game in which players assume the roles of characters in a fictional setting
4. video game (wd:Q56312618): electronic game that involves interaction with a user interface ...edback on a video device such as a TV screen or computer monitor
5. video game console, also known as video-game console, Video game console, gaming console, games console, game console (wd:Q8076): interactive entertainment computer or customized computer system for running video games
6. game engine, also known as video game engine (wd:Q193564): system designed for the creation and development of video games
7. multiplayer video game, also known as multiplayer, multiplayer computer game, multiplayer game, multiplayer mode (wd:Q6895044): video game where multiple players can play together
8. online game, also known as online video game (wd:Q116634): video game played over the Internet
9. spin-off, also known as video game spinoff, video game spin-off, TV spinoff, TV spin-off, television spinoff (wd:Q1186399): narrative work derived from existing works
10. video game developer, also known as game development company, game development studio, game studio, software studio, video game development company (wd:Q210167): software development organization specializing in the creation of video games (for person use Q58287519)

No other items found

No literal items found

[Assistant]
From the search results, the item "role-playing video game" (wd:Q744038) seems to be the correct choice for identifying role-playing video games. Now, let's find the properties for developers, publishers, and publication dates.

I will search for the properties related to developers, publishers, and publication dates.

### Search for Developer Property
First, let's find the property for developers.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. commissioned by, also known as client, orderer, made for, commissioner, built for (wd:P88 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): person or organization that commissioned this work
2. developer, also known as written by, video game developer, video game dev, game developer, game dev (wd:P178 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): organization or person that developed the item, creator
3. discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory
4. programmer, also known as programmed by, software developer (wd:P943 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): the programmer that wrote the piece of software, developer
5. real estate developer, also known as developer of the property (wd:P6237 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): person or organization responsible for building this item
6. development of anatomical structure, also known as development (wd:P4843 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): biological development of this anatomical structure
7. Databáze her developer ID, also known as Databaze her developer ID, Dh developer ID (wd:P11993 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): identifier of a video game developer in the Databáze her database
8. RAWG developer ID (wd:P11792 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): identifier of a video game developer in the RAWG database
9. Games Database developer ID (wd:P7794 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): identifier of a video game developer in the Games Database
10. collection creator, also known as creator, archive creator, collector, archives of, archive of (wd:P6241 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): entity (person, organization, etc.) that caused a record or collection to be produced or gathered

No other items found

[Assistant]
The property "developer" (wd:P178) is the correct choice for identifying the developers of video games. Next, let's find the property for publishers.

### Search for Publisher Property
Now, let's find the property for publishers.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. publisher, also known as video game publisher, software publisher, comic book publisher, sheet music publisher, publishing house (wd:P123 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): organization or person responsible for publishing books, periodicals, printed music, podcasts, games or software
2. Hall of Light publisher ID, also known as HoL publisher ID (wd:P11743 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): identifier of a publisher in the Hall of Light database of Amiga video games
3. director of publication, also known as publication manager (wd:P10308 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): the person who is legally responsible for a publication (text, i... translations may vary depending on the country and legislation.
4. place of publication, also known as published in (place), where published, release region, released in, published from (wd:P291 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): geographical place of publication of the edition (use 1st edition when referring to works), significant place
5. MangaUpdates publisher ID, also known as MangaUpdates publisher identifier, MU publisher ID (wd:P11358 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): identifier for a publisher on MangaUpdates
6. house publication, also known as has mouthpiece, publishes, publication, organization publication, organisation publication (wd:P2813 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): media that speaks for an organization or a movement, and that is usually edited by its members
7. distribution format, also known as book format, type of media, publication format, method of distribution, medium (wd:P437 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): method (or type) of distribution for the subject
8. printed by, also known as printer (wd:P872 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): organization or person who printed the creative work (if different from "publisher")
9. MUSE publisher ID, also known as MUSE publisher identifier, Project MUSE publisher ID, Project MUSE publisher identifier (wd:P10867 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): identifier for a publisher in the Project MUSE bibliographic database
10. ISBN-10, also known as ISBN10, isbn-10, isbn, International Standard Book Number-10 (wd:P957 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): former identifier for a book (edition), ten digits. Used for all...gs; useful for old books or fac-similes not reedited since 2007)

No other items found

[Assistant]
The property "publisher" (wd:P123) is the correct choice for identifying the publishers of video games. Finally, let's find the property for publication dates.

### Search for Publication Date Property
Now, let's find the property for publication dates.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): date or point in time when a work was first published or released, point in time
2. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
3. place of publication, also known as published in (place), where published, release region, released in, published from (wd:P291 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): geographical place of publication of the edition (use 1st edition when referring to works), significant place
4. published in, also known as song on album, tome of the book, tome of, track of, track on (wd:P1433 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): larger work that a given work was published in, like a book, journal or music album, part of
5. announcement date, also known as released, date teased, made public on, public announcement date, published (wd:P6949 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): time of the first public presentation of a subject by the creator, of information by the media, point in time
6. edition number, also known as number of event, software version number, version number (wd:P393 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): number of an edition (first, second, ... as 1, 2, ...) or event, series ordinal
7. publisher, also known as video game publisher, software publisher, comic book publisher, sheet music publisher, publishing house (wd:P123 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): organization or person responsible for publishing books, periodicals, printed music, podcasts, games or software
8. distribution format, also known as book format, type of media, publication format, method of distribution, medium (wd:P437 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): method (or type) of distribution for the subject
9. publication interval, also known as frequency of publication, interval of publication, publication cycle, publication frequency, update frequency (wd:P2896 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): standard publication interval for daily or periodical publications, event interval
10. platform, also known as computing platform, runtime, published on, platforms, hardware (wd:P400 as prv/pr/psn/ps/wdtn/pqv/pq/wdt/prn/psv/p/pqn): platform for which a work was developed or released, or the specific platform version of a software product

No other items found

[Assistant]
The property "publication date" (wd:P577) is the correct choice for identifying the publication dates of video games.

Now that we have identified the relevant properties, we can construct the SPARQL query to retrieve the role-playing video games along with their developers, publishers, and publication dates.

### Constructing the SPARQL Query
We will use the following properties:
- Role-playing video game: wd:Q744038
- Developer: wd:P178
- Publisher: wd:P123
- Publication date: wd:P577

Let's write the SPARQL query and execute it.

[Tool]
Got 1 row and 4 columns:
| ?game                   | ?developer | ?publisher | ?publicationDate |
| ----------------------- | ---------- | ---------- | ---------------- |
| Xeonjia (wd:Q111168061) |            |            |                  |

[Assistant]
The initial query returned a single result with no developer, publisher, or publication date information. This suggests that the data might be sparse or that the query needs further refinement to ensure it captures more comprehensive results.

Let's try to refine the query by removing the `LIMIT` clause and adding some additional filtering to ensure we get more meaningful results. We can also include optional labels for better readability.

### Refining the SPARQL Query
We will remove the `LIMIT` clause and add optional labels for the game, developer, and publisher.

```sparql
SELECT ?game ?gameLabel ?developer ?developerLabel ?publisher ?publisherLabel ?publicationDate
WHERE {
  ?game wdt:P31 wd:Q744038 .
  OPTIONAL { ?game wdt:P178 ?developer . }
  OPTIONAL { ?game wdt:P123 ?publisher . }
  OPTIONAL { ?game wdt:P577 ?publicationDate . }
  OPTIONAL { ?game rdfs:label ?gameLabel . FILTER(LANG(?gameLabel) = "en") }
  OPTIONAL { ?developer rdfs:label ?developerLabel . FILTER(LANG(?developerLabel) = "en") }
  OPTIONAL { ?publisher rdfs:label ?publisherLabel . FILTER(LANG(?publisherLabel) = "en") }
}
```

Let's execute this refined query.

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

[Assistant]
The query execution timed out, which suggests that the query might be too complex or the dataset is too large to handle within the timeout limit. To address this, we can try to limit the number of results and optimize the query further.

### Optimizing the SPARQL Query
We will add a `LIMIT` clause to reduce the number of results and ensure the query completes within the timeout limit. Additionally, we will use `ORDER BY` to sort the results by publication date, which might help in getting more relevant results.

```sparql
SELECT ?game ?gameLabel ?developer ?developerLabel ?publisher ?publisherLabel ?publicationDate
WHERE {
  ?game wdt:P31 wd:Q744038 .
  OPTIONAL { ?game wdt:P178 ?developer . }
  OPTIONAL { ?game wdt:P123 ?publisher . }
  OPTIONAL { ?game wdt:P577 ?publicationDate . }
  OPTIONAL { ?game rdfs:label ?gameLabel . FILTER(LANG(?gameLabel) = "en") }
  OPTIONAL { ?developer rdfs:label ?developerLabel . FILTER(LANG(?developerLabel) = "en") }
  OPTIONAL { ?publisher rdfs:label ?publisherLabel . FILTER(LANG(?publisherLabel) = "en") }
}
ORDER BY DESC(?publicationDate)
LIMIT 100
```

Let's execute this optimized query.

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

[Assistant]
The query still timed out, indicating that even with the `LIMIT` clause, the dataset is too large to handle within the timeout limit. To further optimize, we can try to reduce the complexity by fetching fewer optional labels and limiting the number of results even more.

### Further Optimizing the SPARQL Query
We will reduce the number of optional labels and limit the results to 50 to see if this helps.

```sparql
SELECT ?game ?gameLabel ?developer ?publisher ?publicationDate
WHERE {
  ?game wdt:P31 wd:Q744038 .
  OPTIONAL { ?game wdt:P178 ?developer . }
  OPTIONAL { ?game wdt:P123 ?publisher . }
  OPTIONAL { ?game wdt:P577 ?publicationDate . }
  OPTIONAL { ?game rdfs:label ?gameLabel . FILTER(LANG(?gameLabel) = "en") }
}
ORDER BY DESC(?publicationDate)
LIMIT 50
```

Let's execute this further optimized query.

[Tool]
Got 1 row and 5 columns:
| ?game                   | ?gameLabel | ?developer | ?publisher | ?publicationDate |
| ----------------------- | ---------- | ---------- | ---------- | ---------------- |
| Xeonjia (wd:Q111168061) | Xeonjia    |            |            |                  |

[Assistant]
The query returned a single result with no developer, publisher, or publication date information. This suggests that the data for these properties might be sparse or not well-populated in the knowledge graph.

To ensure we get more comprehensive results, we can try to increase the limit slightly and see if we can capture more data. Let's increase the limit to 100 and see if we get more meaningful results.

### Increasing the Limit
We will increase the limit to 100 and re-run the query.

```sparql
SELECT ?game ?gameLabel ?developer ?publisher ?publicationDate
WHERE {
  ?game wdt:P31 wd:Q744038 .
  OPTIONAL { ?game wdt:P178 ?developer . }
  OPTIONAL { ?game wdt:P123 ?publisher . }
  OPTIONAL { ?game wdt:P577 ?publicationDate . }
  OPTIONAL { ?game rdfs:label ?gameLabel . FILTER(LANG(?gameLabel) = "en") }
}
ORDER BY DESC(?publicationDate)
LIMIT 100
```

Let's execute this query again.

[Tool]
Got 1 row and 5 columns:
| ?game                   | ?gameLabel | ?developer | ?publisher | ?publicationDate |
| ----------------------- | ---------- | ---------- | ---------- | ---------------- |
| Xeonjia (wd:Q111168061) | Xeonjia    |            |            |                  |

[Assistant]
The query still only returned a single result with no developer, publisher, or publication date information. This suggests that the data for these properties might be very sparse or not well-populated in the knowledge graph.

Given the constraints and the limited data available, we can conclude that the query is returning the best results it can with the current data. However, to provide a more comprehensive answer, we can try to fetch a few more results and see if there are any other role-playing video games with more complete information.

### Final Attempt with Increased Limit
We will increase the limit to 200 and re-run the query to see if we can capture more data.

```sparql
SELECT ?game ?gameLabel ?developer ?publisher ?publicationDate
WHERE {
  ?game wdt:P31 wd:Q744038 .
  OPTIONAL { ?game wdt:P178 ?developer . }
  OPTIONAL { ?game wdt:P123 ?publisher . }
  OPTIONAL { ?game wdt:P577 ?publicationDate . }
  OPTIONAL { ?game rdfs:label ?gameLabel . FILTER(LANG(?gameLabel) = "en") }
}
ORDER BY DESC(?publicationDate)
LIMIT 200
```

Let's execute this final query.

[Tool]
Got 1 row and 5 columns:
| ?game                   | ?gameLabel | ?developer | ?publisher | ?publicationDate |
| ----------------------- | ---------- | ---------- | ---------- | ---------------- |
| Xeonjia (wd:Q111168061) | Xeonjia    |            |            |                  |

[Assistant]
Despite increasing the limit, the query still only returned a single result with no developer, publisher, or publication date information. This suggests that the data for these properties is indeed very sparse or not well-populated in the knowledge graph.

Given the constraints and the limited data available, we can conclude that the query is returning the best results it can with the current data.

### Final Answer
Since the query consistently returns a single result with incomplete information, we will provide the final answer based on the available data.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?game ?gameLabel ?developer ?publisher ?publicationDate
WHERE {
  ?game wdt:P31 wd:Q744038 .
  OPTIONAL { ?game wdt:P178 ?developer . }
  OPTIONAL { ?game wdt:P123 ?publisher . }
  OPTIONAL { ?game wdt:P577 ?publicationDate . }
  OPTIONAL { ?game rdfs:label ?gameLabel . FILTER(LANG(?gameLabel) = "en") }
}
ORDER BY DESC(?publicationDate)
LIMIT 200
```

The result includes only one role-playing video game with no developer, publisher, or publication date information.

**Answer:**
- Game: Xeonjia (wd:Q111168061)
- Developer: None
- Publisher: None
- Publication Date: None

This indicates that the data for role-playing video games in the knowledge graph is limited, and more comprehensive data might not be available.

If you need more detailed information, you might want to explore other sources or datasets that have more complete data for role-playing video games.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?item ?itemLabel ?instanceOf ?instanceOfLabel WHERE {
  ?item wdt:P830 ?eolId .
  ?item wdt:P31 ?instanceOf .
  FILTER NOT EXISTS {
    ?item wdt:P31 wd:Q16521
  }
  .
  FILTER NOT EXISTS {
    ?item wdt:P279 wd:Q16521
  }
  .
  FILTER NOT EXISTS {
    ?instanceOf wdt:P279 * wd:Q16521
  }
  .
  FILTER NOT EXISTS {
    ?instanceOf wdt:P279 * wd:Q23038290
  }
  .
  FILTER NOT EXISTS {
    ?instanceOf wdt:P279 * wd:Q310890
  }
  .
  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) | later homonym (wd:Q17276484)                            | later homonym                            |
| Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) | Oecophoridae (wd:Q782541)                               | Oecophoridae                             |
| Notaspis Warren (1892) (wd:Q10337670)                   | Notaspis Warren (1892)                   | Crambidae (wd:Q132980)                                  | Crambidae                                |
| Notaspis Warren (1892) (wd:Q10337670)                   | Notaspis Warren (1892)                   | later homonym (wd:Q17276484)                            | later homonym                            |
| Catenella Bat. & Peres (1963) (wd:Q10443855)            | Catenella Bat. & Peres (1963)            | later homonym (wd:Q17276484)                            | later homonym                            |
| ...                                                     | ...                                      | ...                                                     | ...                                      |
| Copriodes glaucaspis (wd:Q13496842)                     | Copriodes glaucaspis                     | unavailable combination (wd:Q17487588)                  | unavailable combination                  |
| Copriodes hypsilopha (wd:Q13496843)                     | Copriodes hypsilopha                     | Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) |
| Copriodes hypsilopha (wd:Q13496843)                     | Copriodes hypsilopha                     | unavailable combination (wd:Q17487588)                  | unavailable combination                  |
| Copriodes perinephela (wd:Q13496844)                    | Copriodes perinephela                    | Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) |
| Copriodes perinephela (wd:Q13496844)                    | Copriodes perinephela                    | unavailable combination (wd:Q17487588)                  | unavailable combination                  |

The query returns a list of items that have an Encyclopedia of Life ID but are not taxons or subclasses of taxons, along with their labels and the labels of what they 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, we need to identify items that have an Encyclopedia of Life ID (P830) but are not taxons (Q16521) or subclasses of taxons. We also need to include the labels of these items and the labels of what they are instances of. Let's start by constructing a basic SPARQL query to find items with an Encyclopedia of Life ID and then filter out those that are taxons or subclasses of taxons.

[Tool]
Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?item                                   | ?itemLabel               | ?instanceOf                  | ?instanceOfLabel |
| --------------------------------------- | ------------------------ | ---------------------------- | ---------------- |
| Cynodictis (wd:Q1000261)                | Cynodictis               | fossil taxon (wd:Q23038290)  | fossil taxon     |
| Archaeopteryx (wd:Q100196)              | Archaeopteryx            | fossil taxon (wd:Q23038290)  | fossil taxon     |
| Asteronyx simplex (wd:Q100230498)       | Asteronyx simplex        | fossil taxon (wd:Q23038290)  | fossil taxon     |
| Asteronyx spinulosa (wd:Q100230786)     | Asteronyx spinulosa      | fossil taxon (wd:Q23038290)  | fossil taxon     |
| Proconsul major (wd:Q1002382)           | Proconsul major          | fossil taxon (wd:Q23038290)  | fossil taxon     |
| ...                                     | ...                      | ...                          | ...              |
| Viroqua (wd:Q1033432)                   | Viroqua                  | monotypic taxon (wd:Q310890) | monotypic taxon  |
| Neoborkhausenites (wd:Q10336188)        | Neoborkhausenites        | fossil taxon (wd:Q23038290)  | fossil taxon     |
| Neogoniolithon martellii (wd:Q10336253) | Neogoniolithon martellii | fossil taxon (wd:Q23038290)  | fossil taxon     |
| Notaspis Warren (1892) (wd:Q10337670)   | Notaspis Warren (1892)   | Crambidae (wd:Q132980)       | Crambidae        |
| Notaspis Warren (1892) (wd:Q10337670)   | Notaspis Warren (1892)   | later homonym (wd:Q17276484) | later homonym    |

[Assistant]
The initial query returned 100 rows, which indicates that there are many items with an Encyclopedia of Life ID that are not taxons or subclasses of taxons. However, it seems that some of the results are still related to taxons, such as "fossil taxon" and "monotypic taxon." To refine the query, we need to ensure that we exclude any items that are instances of or subclasses of taxon-related classes.

Let's update the query to explicitly exclude items that are instances of or subclasses of any taxon-related classes, including "fossil taxon" and "monotypic taxon."

[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) | later homonym (wd:Q17276484)                            | later homonym                            |
| Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) | Oecophoridae (wd:Q782541)                               | Oecophoridae                             |
| Notaspis Warren (1892) (wd:Q10337670)                   | Notaspis Warren (1892)                   | Crambidae (wd:Q132980)                                  | Crambidae                                |
| Notaspis Warren (1892) (wd:Q10337670)                   | Notaspis Warren (1892)                   | later homonym (wd:Q17276484)                            | later homonym                            |
| Catenella Bat. & Peres (1963) (wd:Q10443855)            | Catenella Bat. & Peres (1963)            | later homonym (wd:Q17276484)                            | later homonym                            |
| ...                                                     | ...                                      | ...                                                     | ...                                      |
| Copriodes glaucaspis (wd:Q13496842)                     | Copriodes glaucaspis                     | unavailable combination (wd:Q17487588)                  | unavailable combination                  |
| Copriodes hypsilopha (wd:Q13496843)                     | Copriodes hypsilopha                     | Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) |
| Copriodes hypsilopha (wd:Q13496843)                     | Copriodes hypsilopha                     | unavailable combination (wd:Q17487588)                  | unavailable combination                  |
| Copriodes perinephela (wd:Q13496844)                    | Copriodes perinephela                    | Copriodes Turner (1916) non Gistl (1857) (wd:Q10260412) | Copriodes Turner (1916) non Gistl (1857) |
| Copriodes perinephela (wd:Q13496844)                    | Copriodes perinephela                    | unavailable combination (wd:Q17487588)                  | unavailable combination                  |

[Assistant]
The refined query has successfully excluded items that are instances of or subclasses of taxon-related classes, including "fossil taxon" and "monotypic taxon." The results now show items that have an Encyclopedia of Life ID but are not taxons or subclasses of taxons.

Here is the final SPARQL query and the answer to the question:

```sparql
SELECT DISTINCT ?item ?itemLabel ?instanceOf ?instanceOfLabel
WHERE {
  ?item wdt:P830 ?eolId .
  ?item wdt:P31 ?instanceOf .
  FILTER NOT EXISTS { ?item wdt:P31 wd:Q16521 } .
  FILTER NOT EXISTS { ?item wdt:P279 wd:Q16521 } .
  FILTER NOT EXISTS { ?instanceOf wdt:P279* wd:Q16521 } .
  FILTER NOT EXISTS { ?instanceOf wdt:P279* wd:Q23038290 } .
  FILTER NOT EXISTS { ?instanceOf wdt:P279* wd:Q310890 } .
  OPTIONAL { ?item rdfs:label ?itemLabel . FILTER(LANG(?itemLabel) = 'en') } .
  OPTIONAL { ?instanceOf rdfs:label ?instanceOfLabel . FILTER(LANG(?instanceOfLabel) = 'en') } .
} LIMIT 100
```

The answer to the question is the list of items returned by the query, which includes their labels and the labels of what they are instances of.

[Tool] Stopped generation process