PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?creator ?creatorLabel WHERE {
  wd:Q19798744 wdt:P161 ?creator .
  VALUES ?creator {
    wd:Q13499404 wd:Q289380
  }
  OPTIONAL {
    ?creator rdfs:label ?creatorLabel FILTER ( LANG( ?creatorLabel ) = "en" )
  }
}

Brit Marling is a creator of The OA who also acted in it.

Which creator of The OA also acted in it?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 creator of The OA also acted in it?

[Assistant]
Step 1: Identify the entity "The OA" in Wikidata to get its identifier. Then find the creators of "The OA" and check which of them also acted in it. Acting in a TV show or movie is usually represented by the property "cast member" or "actor" in Wikidata.

I will start by searching for the entity "The OA" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. The OA (wd:Q19798744): 2016 American mystery drama television series, instance of television series, instance of web series
2. The Oa, also known as The Oa RSPB Nature Reserve (wd:Q1325866): peninsula in the southwest of Islay, Argyll and Bute, Scotland, UK, instance of nature reserve, instance of peninsula
3. The Oa (wd:Q126204501): Special Protection Area in Scotland, UK, instance of Special Protection Area
4. The Oath, also known as Eiðurinn, Oath (wd:Q27834781): 2016 film by Baltasar Kormákur, instance of film
5. Il giuramento, also known as The Oath (wd:Q1469058): instance of dramatico-musical work, opera by Saverio Mercadante
6. Di Shvue, also known as Di Bundishe Shvue, The Oath (wd:Q5270055): instance of musical work/composition, Jewish song, anthem of the Bund, instance of Yiddish song
7. The Oak, also known as Oak (wd:Q2328850): instance of film, 1992 film
8. Epsom Oaks, also known as Oaks, The Oaks, The Oaks Stakes (wd:Q3347856)
9. The Oatmeal, also known as theoatmeal.com (wd:Q2015830): instance of pseudonym, instance of website, humor website
10. The Oaks (wd:Q20972573): place in Limpopo, South Africa, instance of human settlement

[Assistant]
The entity "The OA" as a 2016 American mystery drama television series is identified as wd:Q19798744.

Step 2: Now I will find the creators of "The OA" (wd:Q19798744). The property for creator in Wikidata is usually "creator" (P170) or "developer" (P178) for TV series. I will check for creators first. Then I will check which of these creators also acted in the series. Acting can be checked by the property "cast member" (P161).

I will first query the creators of "The OA".

[Tool]
Got 2 rows and 2 columns:
| creator                       | creatorLabel        |
| ----------------------------- | ------------------- |
| Zal Batmanglij (wd:Q13499404) | Zal Batmanglij (en) |
| Brit Marling (wd:Q289380)     | Brit Marling (en)   |

[Assistant]
The creators of "The OA" are Zal Batmanglij and Brit Marling.

Step 3: Now I will check which of these creators also acted in "The OA". I will check if either Zal Batmanglij or Brit Marling is listed as a cast member (P161) of "The OA" (wd:Q19798744).

[Tool]
Got 1 row and 2 columns:
| creator                   | creatorLabel      |
| ------------------------- | ----------------- |
| Brit Marling (wd:Q289380) | Brit Marling (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?founder ?founderLabel WHERE {
  wd:Q95 wdt:P112 ?founder .
  OPTIONAL {
    ?founder rdfs:label ?founderLabel FILTER ( LANG( ?founderLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| founder                 | founderLabel     |
| ----------------------- | ---------------- |
| Larry Page (wd:Q4934)   | Larry Page (en)  |
| Sergey Brin (wd:Q92764) | Sergey Brin (en) |

No, Google was not founded by Bill Gates. The founders of Google are Larry Page and Sergey Brin.

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] Was Google founded by Bill Gates?

[Assistant]
To answer the question "Was Google founded by Bill Gates?" I need to verify the founders of Google and check if Bill Gates is among them.

Step 1: Identify the entity for Google.
Step 2: Identify the founders of Google.
Step 3: Check if Bill Gates is listed as a founder of Google.

I will start by searching for the entity "Google" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Google, also known as google.com, Google Inc., Google, Inc., Google LLC, Big G (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc., instance of technology company, instance of identity provider, instance of public company, instance of online service, instance of business
2. Google Search, also known as www.google.com, Google Web Search, Google search engine, Google homepage, google.com (wd:Q9366): search engine by Google LLC, instance of search engine
3. Alphabet Inc., also known as Alphabet, Inc, abc.xyz, Alphabet, Inc., Alphabet Incorporated, Google (wd:Q20800404): American multinational technology conglomerate, instance of holding company, instance of public company, instance of organization, instance of business
4. Google+, also known as Google Plus, G+ (wd:Q356): instance of application programming interface, instance of social networking service, instance of service on Internet, instance of computing platform, instance of online community, instance of cloud computing, social networking service, instance of software
5. .google, also known as dot google (wd:Q20573262): instance of generic top-level domain, top-level Internet domain
6. google, also known as googling, to google (wd:Q1156923): transitive verb, meaning to search for something using the Google search engine, instance of verb
7. Google Google (wd:Q123412777): instance of musical work/composition, Tamil song from Thuppakki movie
8. Google (wd:Q125851407): instance of mobile app, mobile app
9. google (wd:Q107382801): instance of Python package, Python library
10. Google (wd:Q110997421): instance of male given name, given name

[Assistant] The entity for Google as a technology company is wd:Q95. Next, I will check the founders of Google (wd:Q95) to see if Bill Gates is listed among them.

[Tool]
Got 2 rows and 2 columns:
| founder                 | founderLabel     |
| ----------------------- | ---------------- |
| Larry Page (wd:Q4934)   | Larry Page (en)  |
| Sergey Brin (wd:Q92764) | Sergey Brin (en) |

[Assistant]
The founders of Google are Larry Page and Sergey Brin. Bill Gates is not listed as a founder of Google.

Now I will check if Bill Gates is the founder of any other company to confirm the distinction. I will search for Bill Gates entity first.

[Tool]
Top 10 entity alternatives:
1. Bill Gates, also known as William Henry Gates, William H. Gates, William Henry Gates III, William H. Gates III, William Gates (wd:Q5284): American businessman, investor, and philanthropist (born 1955), instance of human, philanthropist, entrepreneur, programmer
2. Bill Gates, also known as William Lazenby Gates (wd:Q123411797): English footballer (1944–2023), association football player, instance of human
3. Bill Gates (wd:Q100794547): college basketball player (1959–1959) Boston University, basketball player, instance of human
4. Bill Gates Sr., also known as William Henry Gates II (wd:Q684014): American attorney and philanthropist (1925–2020), instance of human, philanthropist, businessperson, lawyer
5. Bill Gates' flower fly, also known as Eristalis gatesi (wd:Q1953052): flower fly species, instance of taxon
6. Bill Gates's house, also known as Xanadu 2.0 (wd:Q371973): instance of earth shelter, instance of mansion, building
7. Bill Gates Must Die (wd:Q22043547): 2000 song performed by John Vanderslice, instance of musical work/composition
8. Email to Bill Gates (wd:Q23562744): instance of television film, 2007 film by Josh Broecker
9. Bill Gates's strength (wd:Q73153155): scientific article published on 01 November 1999, instance of scholarly article
10. Bill Gates funds geoengineering (wd:Q115430184): scientific article published in 2010, instance of scholarly article

[Assistant] The entity for Bill Gates is wd:Q5284. Now I will check if Bill Gates (wd:Q5284) is listed as a founder of any company.

[Tool]
Got 13 rows and 2 columns, showing the first 5 and last 5 rows below:
| company                                       | companyLabel                        |
| --------------------------------------------- | ----------------------------------- |
| bgC3 (wd:Q1050976)                            | bgC3 (en)                           |
| Microsoft Research (wd:Q1144725)              | Microsoft Research (en)             |
| DATA (wd:Q1181663)                            | DATA (en)                           |
| FWD.us (wd:Q15064314)                         | FWD.us (en)                         |
| The Giving Pledge (wd:Q203807)                | The Giving Pledge (en)              |
| ...                                           | ...                                 |
| TerraPower (wd:Q4050859)                      | TerraPower (en)                     |
| Cascade Investment (wd:Q4206709)              | Cascade Investment (en)             |
| Goalkeepers (Gates Foundation) (wd:Q65062758) | Goalkeepers (Gates Foundation) (en) |
| Gates Foundation (wd:Q655286)                 | Gates Foundation (en)               |
| Xbox Game Studios (wd:Q73801)                 | Xbox Game Studios (en)              |

[Assistant]
Bill Gates is founder of several organizations, but Google is not among them. The founders of Google are Larry Page and Sergey Brin.

I will now finalize the answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?founder ?founderLabel WHERE {
  wd:Q848490 wdt:P112 ?founder .
  OPTIONAL {
    ?founder rdfs:label ?founderLabel FILTER ( LANG( ?founderLabel ) = "en" )
  }
}

The Roland Corporation was founded by Ikutaro Kakehashi.

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 founded the Roland Corporation?

[Assistant]
To answer the question "Who founded the Roland Corporation?", I need to identify the entity for "Roland Corporation" in Wikidata and then find the property that indicates its founder. Typically, the property for founder is P112.

First, I will search for the entity "Roland Corporation" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Roland Corporation, also known as Roland Corp., Roland (wd:Q848490): instance of musical instrument manufacturing company, Japanese audiovisual equipment company, instance of business
2. Roland DG, also known as Roland DG Corporation (wd:Q2162714): instance of enterprise, instance of business
3. Roland Foods Corporation (wd:Q23461918): Food importer in New York
4. Roland DGA Corporation (wd:Q22812960): American arm of Roland DG Corporation, instance of business
5. corporation, also known as corporated entity (wd:Q167037)
6. Roland, also known as Rotholandus, Orlando, Hruodlandus, Hruodland (wd:Q207535): Frankish military leader under Charlemagne and main character of the Song of Roland, instance of legendary figure, instance of human, knight
7. Roland, also known as Roland, Iowa, Roland, IA (wd:Q1925777): instance of city in the United States, city in Iowa
8. Roland, also known as Roland, USA, Roland, Oklahoma, Roland, OK (wd:Q2321457): town in Sequoyah County, Oklahoma, USA, instance of town in the United States
9. Roland, also known as Roland missile, Roland SAM, MIM-115, Euromissile Roland (wd:Q705254)
10. Roland (wd:Q1068487): instance of male given name, male given name

[Assistant] The entity for "Roland Corporation" is wd:Q848490. Now I will check the property for the founder (P112) of this entity.

[Tool]
Got 1 row and 2 columns:
| founder                        | founderLabel           |
| ------------------------------ | ---------------------- |
| Ikutaro Kakehashi (wd:Q322845) | Ikutaro Kakehashi (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?territory ?territoryLabel WHERE {
  VALUES ?territory {
    wd:Q209857 wd:Q6360367
  }
  ?territory wdt:P131 wd:Q131964 .
  OPTIONAL {
    ?territory rdfs:label ?territoryLabel FILTER ( LANG( ?territoryLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| territory                                | territoryLabel                   |
| ---------------------------------------- | -------------------------------- |
| Kingdom of Lombardy–Venetia (wd:Q209857) | Kingdom of Lombardy–Venetia (en) |
| Venetian Province (wd:Q6360367)          | Venetian Province (en)           |

Yes, Venice was at some point part of the Austrian Empire through the Kingdom of Lombardy–Venetia and the Venetian Province, which were territories within the Austrian Empire.

Did Venice at any point belong to the Austrian Empire?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] Did Venice at any point belong to the Austrian Empire?

[Assistant]
To answer whether Venice at any point belonged to the Austrian Empire, I need to check the historical political affiliations or sovereign states of Venice. Specifically, I want to find if there is any historical period when Venice was part of the Austrian Empire.

Step 1: Identify the entity for Venice.
Step 2: Identify the entity for the Austrian Empire.
Step 3: Check historical political affiliations or "part of" relations for Venice to see if it was ever part of the Austrian Empire.

I will start by searching for the entity "Venice" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Venice, also known as Venezia, Venexia, Venice, Italy, Serenissima, Venetia (wd:Q641): instance of Italian city-state, capital city of Veneto, Italy, instance of commune of Italy, instance of car-free place, instance of carfree city, instance of port city, instance of big city, instance of city
2. Republic of Venice, also known as Serenissima Repubblica di Venezia, The Most Serene Republic of Venice, The Republic of Venice, The Serenissima, Venetian Empire (wd:Q4948): former state in Northeastern Italy (697–1797), instance of historical country
3. Venice, also known as Venice, CA, Venice, California, Venice, Los Angeles (wd:Q773853): beachfront neighborhood in Los Angeles, California, USA, instance of neighborhood
4. Venice, also known as Venice, FL, Venice, Florida (wd:Q57325): city in Sarasota County, Florida, United States, instance of city in the United States
5. Venice, also known as IL, Venice, IL, Venice, Illinois (wd:Q579637): instance of city in the United States, city in Illinois, United States
6. Venice, also known as Venice, LA, Venice, Louisiana (wd:Q962040): census designated place in Plaquemines Parish, Louisiana, United States, instance of unincorporated community in the United States, instance of census-designated place in the United States
7. Venice, also known as Venice, New York (wd:Q607094): town in Cayuga County, New York, United States, instance of town in the United States, instance of town of New York
8. Venice, also known as Venice, NE, Venice, Nebraska (wd:Q6160341): instance of census-designated place in the United States, census-designated place in Nebraska
9. Venice, also known as Venice, Utah, Venice, UT (wd:Q7919964): unincorporated community in Sevier County, Utah, United States, instance of unincorporated community in the United States
10. Paolo Salviati, also known as Venice, P. Salviati (wd:Q58242413): Italian photographer, 1818-1894, instance of human, photographer

[Assistant]
The entity "Venice" as a city in Italy is wd:Q641, and the historical state "Republic of Venice" is wd:Q4948. Since the question is about historical belonging, it is more relevant to consider the historical state "Republic of Venice" (wd:Q4948).

Next, I will search for the entity "Austrian Empire" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Austrian Empire, also known as Austria, Kaiserthum Österreich (wd:Q131964): Central European multinational Empire from 1804 to 1867, instance of historical country
2. Austrian colonies, also known as List of former Austrian colonies, Habsburg Monarchy colonies, Austrian colonial empire (wd:Q303598)
3. Imperial Crown of Austria, also known as Crown of the Austrian Empire, Crown of Rudolf II, Austrian Imperial Crown, Austrian Crown (wd:Q303507): Crown of the Emperor of Austria, instance of crown
4. Minister-President of Austria, also known as Minister-President of the Austrian Empire, Minister-president of Austria (wd:Q15902790)
5. economy of the Austrian Empire (wd:Q3718694)
6. Constitutions of the Austrian Empire (wd:Q56364899): instance of aspect of history
7. ambassador to the Austrian Empire (wd:Q110636887)
8. ambassador of the Austrian Empire, also known as ambassador of Austria, Austrian ambassador (wd:Q106085599)
9. foreign minister of Austrian Empire (wd:Q130805004): instance of position, position (–1867)
10. 1850 stamps of the Austrian Empire (wd:Q1447304): instance of stamp series

[Assistant]
The entity for the Austrian Empire is wd:Q131964.

Now, I will check if the historical state "Republic of Venice" (wd:Q4948) was at any point part of or belonged to the Austrian Empire (wd:Q131964). I will look for properties related to "part of," "country," or "sovereign state" for the Republic of Venice that might indicate this relationship.

[Tool] Got no rows and 2 columns

[Assistant]
The direct "part of" (P361) property for the Republic of Venice does not show any affiliation with the Austrian Empire.

Next, I will check if there is any historical "country" (P17) or "sovereign state" (P131 or P47) property for the Republic of Venice that might indicate it belonged to the Austrian Empire at some point. I will also check for any historical "replaced by" or "replaced" properties that might indicate a change in sovereignty.

[Tool] Got no rows and 4 columns

[Assistant]
There are no direct properties like country (P17), located in the administrative territorial entity (P131), contains administrative territorial entity (P47), replaced by (P1365), or replaces (P1366) for the Republic of Venice that indicate it belonged to the Austrian Empire.

Since the Republic of Venice existed until 1797, I will check historical events or successor states related to it to see if the Austrian Empire took control after its end. I will look for the "dissolved, abolished or demolished date" (P576) and "replaced by" (P1365) properties and their values.

[Tool] Got no rows and 4 columns

[Assistant]
There are no direct properties for dissolved date (P576) or replaced by (P1365) for the Republic of Venice.

I will try a different approach: I will check the historical timeline or events related to Venice (wd:Q641) to see if there is any indication of it belonging to the Austrian Empire. I will look for "historical territorial entity" (P131) or "part of" (P361) properties for Venice that might indicate this.

[Tool] Got no rows and 4 columns

[Assistant]
There are no direct "part of" (P361) or "located in the administrative territorial entity" (P131) properties for Venice (wd:Q641) indicating historical belonging to the Austrian Empire.

I will now check if there is any historical event or historical territorial entity related to Venice that might indicate Austrian rule. I will search for historical territorial entities or historical countries that Venice was part of.

[Tool]
Got 1 row and 2 columns:
| historicalEntity                          | historicalEntityLabel            |
| ----------------------------------------- | -------------------------------- |
| Metropolitan City of Venice (wd:Q3678587) | Metropolitan City of Venice (en) |

[Assistant]
Venice (wd:Q641) is currently part of the Metropolitan City of Venice (wd:Q3678587), which is a modern administrative entity, not a historical country.

I will now try to find if the Austrian Empire (wd:Q131964) had any territorial claims or historical territories that included Venice. I will check the territories or subdivisions of the Austrian Empire.

[Tool]
Got 17 rows and 2 columns, showing the first 5 and last 5 rows below:
| territory                                      | territoryLabel                        |
| ---------------------------------------------- | ------------------------------------- |
| Kingdom of Hungary (wd:Q171150)                | Kingdom of Hungary (en)               |
| Kingdom of Lombardy–Venetia (wd:Q209857)       | Kingdom of Lombardy–Venetia (en)      |
| Military Frontier (wd:Q221242)                 | Military Frontier (en)                |
| Military Frontier (wd:Q221242)                 | Military Frontier (en)                |
| Kingdom of Galicia and Lodomeria (wd:Q2396442) | Kingdom of Galicia and Lodomeria (en) |
| ...                                            | ...                                   |
| Venetian Province (wd:Q6360367)                | Venetian Province (en)                |
| Lands of the Bohemian Crown (wd:Q686971)       | Lands of the Bohemian Crown (en)      |
| Lands of the Bohemian Crown (wd:Q686971)       | Lands of the Bohemian Crown (en)      |
| Trstená (wd:Q847350)                           | Trstená (en)                          |
| Trstená (wd:Q847350)                           | Trstená (en)                          |

[Assistant]
Among the territories of the Austrian Empire, I found "Kingdom of Lombardy–Venetia" (wd:Q209857) and "Venetian Province" (wd:Q6360367) which seem related to Venice.

I will now check if Venice (wd:Q641) was part of the Kingdom of Lombardy–Venetia or the Venetian Province during the Austrian Empire period.

[Tool] Got no rows and 2 columns

[Assistant]
Venice (wd:Q641) does not have a direct property P131 (located in the administrative territorial entity) linking it to the Kingdom of Lombardy–Venetia (wd:Q209857) or the Venetian Province (wd:Q6360367).

I will now check if the Kingdom of Lombardy–Venetia or Venetian Province has any properties indicating that Venice was its capital or part of it. I will look for "capital" (P36) or "contains administrative territorial entity" (P150) properties.

[Tool] Got no rows and 4 columns

[Assistant]
The Kingdom of Lombardy–Venetia and the Venetian Province do not have direct properties indicating Venice as their capital or as part of their administrative territorial entities.

I will now check the historical timeline of Venice (wd:Q641) to see if there is any mention of Austrian rule or the Austrian Empire in its history. I will look for historical events or "significant event" (P793) properties related to Venice.

[Tool]
Got 1 row and 2 columns:
| event                       | eventLabel           |
| --------------------------- | -------------------- |
| excommunication (wd:Q49822) | excommunication (en) |

[Assistant]
There is only one significant event (excommunication) listed for Venice (wd:Q641), which does not relate to Austrian rule.

I will now try a different approach: I will check the historical country or empire that Venice (wd:Q641) was part of by looking for "historical country" (P17) or "historical empire" properties or any historical territorial entity properties.

[Tool]
Got 2 rows and 2 columns:
| historicalCountry | historicalCountryLabel |
| ----------------- | ---------------------- |
| Italy (wd:Q38)    | Italy (en)             |
| Italy (wd:Q38)    | Italy (en)             |

[Assistant]
Venice (wd:Q641) is currently part of Italy (wd:Q38), which is a historical country as well, but there is no direct indication of it being part of the Austrian Empire here.

I will now check the historical country or empire for the Republic of Venice (wd:Q4948) by looking for "replaced by" (P1365) or "replaces" (P1366) properties to see if it was succeeded by the Austrian Empire or any of its territories.

[Tool] Got no rows and 4 columns

[Assistant]
There are no direct "replaced by" or "replaces" properties for the Republic of Venice (wd:Q4948).

I will now check the historical timeline of the Republic of Venice to see if there is any mention of the Austrian Empire or Austrian rule in its history. I will look for "significant event" (P793) properties related to the Republic of Venice.

[Tool] Got no rows and 2 columns

[Assistant]
There are no significant events listed for the Republic of Venice (wd:Q4948) that mention the Austrian Empire or Austrian rule.

Since direct properties and historical events do not provide a clear answer, I will now check the historical country or empire for the Kingdom of Lombardy–Venetia (wd:Q209857) and Venetian Province (wd:Q6360367) to see if they are part of the Austrian Empire (wd:Q131964). This might indirectly indicate that Venice was under Austrian rule through these entities.

[Tool]
Got 2 rows and 2 columns:
| parent                       | parentLabel          |
| ---------------------------- | -------------------- |
| Austrian Empire (wd:Q131964) | Austrian Empire (en) |
| Austrian Empire (wd:Q131964) | Austrian Empire (en) |

[Assistant]
Both the Kingdom of Lombardy–Venetia (wd:Q209857) and the Venetian Province (wd:Q6360367) are located in the Austrian Empire (wd:Q131964).

This indicates that Venice was at some point part of these territories under the Austrian Empire.

I will now finalize the answer based on this information.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?work ) AS ?count ) WHERE {
  ?work wdt:P144 wd:Q79037 .
  {
    ?work wdt:P1441 wd:Q1621261 .
  } UNION {
    ?work wdt:P674 wd:Q1621261 .
  }
}

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

According to the current data in Wikidata, there are 0 works that are based on Spider-Man and have Venom as a character or present in the work.

How many works that are based on Spider-Man has Venom been a part 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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] How many works that are based on Spider-Man has Venom been a part of?

[Assistant]
To answer this question, I need to find works that are based on Spider-Man and check in how many of these works Venom has been a part of.

Step 1: Identify the entities for "Spider-Man" and "Venom."
Step 2: Identify the property that relates works to Spider-Man (e.g., "based on" or "adaptation of").
Step 3: Identify the property that relates Venom to these works (e.g., "character in" or "cast member").
Step 4: Count the number of such works.

I will start by searching for the entities "Spider-Man" and "Venom" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Spider-Man, also known as Wallcrawler, The Amazing Spider-Man, The Human Spider, The Fantastic Spider-Man, Spidey (wd:Q79037): fictional character in Marvel Comics, instance of comics character, instance of mutate, businessperson, photographer, superhero, scientist, inventor, teacher
2. Spider-Man (wd:Q484442): 2002 American film directed by Sam Raimi, instance of film
3. Spider-Man, also known as Marvel's Spider-Man (wd:Q25340029): 2018 video game developed by Insomniac Games, instance of video game
4. Spider-Man, also known as Spider-Man: The Animated Series (wd:Q569934): American animated television series from 1994–1998, instance of animated television series
5. Miles Morales, also known as Spider-Man, Ultimate Spider-Man, Miles Gonzalo Morales (wd:Q59826): fictional character in Marvel Comics, instance of fictional human, instance of mutate, superhero, student
6. Spider-Man, also known as Spider-Man 2000 (wd:Q288296): instance of video game, 2000 video game
7. Marvel's Spider-Man, also known as Spider-Man (wd:Q28207200): instance of animated television series, American animated television series
8. Peter Parker, also known as Peter 1, Spider-Man, Peter-One, Peter One, Peter #1 (wd:Q23991129): fictional character from the Marvel Cinematic Universe, instance of fictional human, instance of film character
9. Spider-Man, also known as Supaidāman (wd:Q2087538): Japanese-US late 1970's television series, instance of television series
10. Spider-Man (wd:Q2333456): US late 1960s animated television series, instance of animated television series

[Assistant]
The most relevant entity for Spider-Man as a fictional character is wd:Q79037.

Now I will search for the entity "Venom" to identify its Wikidata entity.

[Tool]
Top 10 entity alternatives:
1. Venom (wd:Q23006268): 2018 American film directed by Ruben Fleischer, instance of film
2. Venom (wd:Q192861): instance of musical group, British heavy metal band
3. Venom (wd:Q1621261): fictional character in Marvel Comics, instance of set of comics characters, instance of animated character, instance of comics character, instance of Symbiote
4. venom, also known as venoms, zootoxin, animal venom (wd:Q3386847)
5. UH-1Y Venom, also known as UH1Y Venom, Venom, UH-1Y Super Huey, UH-1 Yankee, UH-1 Venom (wd:Q2529305)
6. DH.112 Venom, also known as de Havilland Venom, de Havilland DH.112 Venom, DH112, Venom, de Havilland DH 112 (wd:Q284767)
7. Michael Page, also known as the venenous cactus, MVP, Venom, Michael Jerome Reece-Page (wd:Q6833334): Brazilian jiu-jitsu practitioner, English mixed martial artist, mixed martial arts fighter, instance of human, martial artist, kickboxer, karateka, boxer
8. Eddie Brock, also known as King in Black, Toxin, Venom, Edward Charles Brock, Anti-Venom (wd:Q2604715): fictional character in Marvel Comics, instance of fictional vigilante, instance of animated character, instance of comics character, instance of fictional human, government agent, superhero, vigilante, reporter
9. Venom, also known as Venom (Music from the Motion Picture) (wd:Q57326696): 2018 song by Eminem, instance of single
10. Venom (wd:Q776607): 2005 film by Jim Gillespie, instance of film

[Assistant]
The most relevant entity for Venom as a fictional character in Marvel Comics is wd:Q1621261.

Next, I will find works that are based on Spider-Man (wd:Q79037). I will search for properties that indicate "based on" or "adaptation of" to find works related to Spider-Man.

[Tool]
Top 10 property alternatives:
1. based on, also known as modelled after, inspired by, iteration of, modeled after, input (wd:P144 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, subproperty of references work, tradition or theory, subproperty of inspired by
2. criterion used, also known as on the basis of, reason for distinction, respectively to, with reference to, with respect to (wd:P1013 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): property by which a distinction or classification is made
3. natural product of taxon, also known as comes from (taxon), derived from, fruit of (taxon), made from, produced by taxon (wd:P1582 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): links a natural product with its source (animal, plant, fungal, algal, etc.)
4. derived from lexeme, also known as word origin, etymology, origin of a word, history of a word, derived from (wd:P5191 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): most direct lexeme(s) this one has developed from
5. after a work by, also known as inspiring artist, artist who inspired this, inspirational artist, copy of a work by, based on a work by (wd:P1877 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): artist whose work strongly inspired / was copied in this item, subproperty of significant person
6. statement supported by, also known as according to, claimed by, per, recognized by, stated by (wd:P3680 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): entity that supports a given statement
7. determination method or standard, also known as methodology, standard, rationale, method of determination, measured by (wd:P459 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): how a value is determined, or the standard by which it is declared
8. derivative work, also known as is source work of, is the basis for, iteration, reboot, remake (wd:P4969 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): new work of art (film, book, software, etc.) derived from major part of this work
9. object sense, also known as derived from sense, sense derivation (wd:P5980 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): (qualifier) statement applies only to listed senses of statement's object
10. semantic derivation of, also known as derived from sense, sense derived from sense (wd:P12410 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): links a lexeme sense to a particular sense it is derived from

[Assistant]
The property "based on" (wdt:P144) seems to be the most relevant to find works based on Spider-Man.

Now I will find works that have "based on" (wdt:P144) Spider-Man (wd:Q79037). I will check the type of these works to ensure they are creative works (e.g., films, books, TV series).

Then, I will find which of these works have Venom (wd:Q1621261) as a character or part of the cast. I will search for properties that relate characters or cast members to works.

[Tool]
Top 10 property alternatives:
1. present in work, also known as appeared in, is shown in, in work, in narrative, from work (wd:P1441 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
2. personality trait of fictional character, also known as traits, trait of fictitious character, trait of fictional character, trait, personal quality of fictitious character (wd:P9652 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): particular personality trait which applies to this fictional character
3. character role, also known as plays, role, performer of, as, acting role (wd:P453 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
4. characters, also known as appears in this work (wd:P674 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): characters which appear in this item (like plays, operas, operettas, books, comics, films, TV series, video games)
5. CJKV variant character, also known as variant sinogram, Z-variant, variant sinograph, variant radical, variant ideograph (wd:P5475 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): equivalent form of this CJKV ideographic character used in different regions or writing systems over time
6. character type, also known as stock character, stereotype, dere, -dere, character stereotype (wd:P9071 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): generic character type that this fictional character represents, subproperty of manifestation of
7. name of the character role, also known as role named as, role name, name of the role, name of the character, name of role (wd:P4633 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): name by which a character role is recorded in a database or ment...ably a specific performance of a theatrical production of a play, subproperty of name
8. shown with features, also known as depicted with features, features depicted, features shown (wd:P1354 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): secondary features depicted in a work. Use as qualifier for "depicts" (P180)
9. notable role, also known as notable for character role, notable for role, notable character role (wd:P10606 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): role in a theatrical, motion picture, television, or other work that a performer is particularly known for, subproperty of notable work
10. has characteristic, also known as trait, has quality, inherent property, object has characteristic, parameter (wd:P1552 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible

[Assistant]
The property "present in work" (wdt:P1441) and "characters" (wdt:P674) seem relevant to find if Venom is part of a work.

I will now construct a query to find works based on Spider-Man (wd:Q79037) using property "based on" (wdt:P144) and check if Venom (wd:Q1621261) is present in these works using property "present in work" (wdt:P1441) or "characters" (wdt:P674). I will count the number of such works.

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

[Assistant]
The query result shows that there are 0 works that are based on Spider-Man and have Venom as a character or present in the work according to the current data in Wikidata.

I will now try to broaden the search by checking if there are works that are adaptations or derivative works of Spider-Man and include Venom. I will use the property "derivative work" (wdt:P4969) to find works derived from Spider-Man and check if Venom is present in those works.

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

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?predecessor ?predecessorLabel WHERE {
  wd:Q1115291 wdt:P1365 ?predecessor .
  ?predecessor rdfs:label ?predecessorLabel .
  FILTER ( LANG( ?predecessorLabel ) = "en" )
}

Got 1 row and 2 columns:
| predecessor                    | predecessorLabel       |
| ------------------------------ | ---------------------- |
| Ayutthaya Kingdom (wd:Q841364) | Ayutthaya Kingdom (en) |

The kingdom that preceded the Thonburi Kingdom is the Ayutthaya Kingdom.

Which kingdom preceded the Thonburi Kingdom ?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 kingdom preceded the Thonburi Kingdom ?

[Assistant]
To answer the question "Which kingdom preceded the Thonburi Kingdom?" I need to identify the Thonburi Kingdom entity in Wikidata and then find the kingdom that existed before it, likely the predecessor kingdom.

Step 1: Search for the Thonburi Kingdom entity in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Thonburi Kingdom (wd:Q1115291): instance of historical country, former country
2. kingdom, also known as regna, regnum (wd:Q36732): instance of rank in zoology, instance of rank in botany, instance of taxonomic rank, taxonomic rank
3. realm, also known as kingdom, kingdom (politics) (wd:Q1250464)
4. The Kingdom, also known as Kingdom (wd:Q467582): 2007 film directed by Peter Berg, instance of film
5. Kingdom (wd:Q30947892): instance of television series, 2019 South Korean TV series
6. kingdom, also known as realm (wd:Q417175)
7. Thonburi, also known as Thonburi Si Mahasamut (wd:Q6580711): instance of territory, area of Bangkok
8. Kingdom, also known as Kingudamu (wd:Q1058984): instance of manga series, Japanese manga series
9. Kingdom (wd:Q18328031): instance of television series, 2014 TV series
10. Finnjet, also known as GTS Finnjet, IMO 7359632, Kingdom (wd:Q1418193): instance of car ferry, ship built in 1977

[Assistant] The Thonburi Kingdom is identified as wd:Q1115291 in Wikidata. Now I will look for the predecessor kingdom of the Thonburi Kingdom using the property "predecessor" or similar properties.

[Tool]
Got 157 rows and 3 columns, showing the first 10 rows below:
| subject                        | property                                           | object                                                                                |
| ------------------------------ | -------------------------------------------------- | --------------------------------------------------------------------------------------- |
| Thonburi Kingdom (wd:Q1115291) | instance of (wdt:P31)                              | historical country (wd:Q3024240)                                                        |
| Thonburi Kingdom (wd:Q1115291) | Commons category (wdt:P373)                        | Thonburi Kingdom                                                                        |
| Thonburi Kingdom (wd:Q1115291) | inception (wdt:P571)                               | 1768-01-01T00:00:00Z (xsd:dateTime)                                                     |
| Thonburi Kingdom (wd:Q1115291) | followed by (wdt:P156)                             | Rattanakosin Kingdom (wd:Q1155700)                                                      |
| Thonburi Kingdom (wd:Q1115291) | topic's main category (wdt:P910)                   | wd:Q10210525                                                                            |
| Thonburi Kingdom (wd:Q1115291) | religion or worldview (wdt:P140)                   | Theravāda (wd:Q132265)                                                                  |
| Thonburi Kingdom (wd:Q1115291) | dissolved, abolished or demolished date (wdt:P576) | 1782-01-01T00:00:00Z (xsd:dateTime)                                                     |
| Thonburi Kingdom (wd:Q1115291) | locator map image (wdt:P242)                       | <http://commons.wikimedia.org/wiki/Special:FilePath/Kingdom%20of%20thonburi%201782.png> |
| Thonburi Kingdom (wd:Q1115291) | capital (wdt:P36)                                  | Thonburi (wd:Q6580711)                                                                  |
| Thonburi Kingdom (wd:Q1115291) | replaces (wdt:P1365)                               | Ayutthaya Kingdom (wd:Q841364)                                                          |
| ...                            | ...                                                | ...                                                                                |

[Assistant]
The property "replaces" (wdt:P1365) for the Thonburi Kingdom (wd:Q1115291) points to the Ayutthaya Kingdom (wd:Q841364). This suggests that the Ayutthaya Kingdom preceded the Thonburi Kingdom.

I will now confirm the label of the predecessor kingdom (wd:Q841364) to ensure it is the Ayutthaya Kingdom.

[Tool]
Got 1 row and 1 column:
| label                  |
| ---------------------- |
| Ayutthaya Kingdom (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?inceptionDate WHERE {
  wd:Q693956 wdt:P571 ?inceptionDate .
}

The Hamburg S-Bahn was officially opened in the year 1907.

When was the Hamburg S-Bahn officially opened?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] When was the Hamburg S-Bahn officially opened?

[Assistant] To answer the question about the official opening date of the Hamburg S-Bahn, I will first search for the entity "Hamburg S-Bahn" in Wikidata to identify its unique identifier. Then, I will look for properties related to the opening date or inception date of this entity.

[Tool]
Top 10 entity alternatives:
1. Hamburg S-Bahn (wd:Q693956): metro railway in Hamburg, Germany, instance of S-Bahn
2. Hamburg City S-Bahn, also known as City-S-Bahn, City-Tunnel (wd:Q321980): instance of railway line, railway tunnel
3. S-Bahnhof Hamburg-Altona station, also known as Hamburg-Altona(S), Hamburg-Altona (S-Bahn), Altona (S-Bahn) (wd:Q70585725): instance of underground railway station, instance of underground station, instance of through station, instance of railway station, railway station in Germany, instance of S-Bahn station, instance of Bahnhofsteil
4. S-Bahn Hamburg GmbH (wd:Q99869216): German railway company operating the Hamburg S-Bahn, instance of railway undertaking
5. Hamburg Airport S-Bahn line (wd:Q1430696): instance of airport rail link, instance of railway tunnel, instance of railway line, railway line in Germany
6. Train Simulator: Hamburg S1 S-Bahn Route Add-On (wd:Q108105621): instance of downloadable content, Train Simulator DLC
7. Hamburg, also known as Hamburg, Germany, Hamburg, Freie und Hansestadt, Free and Hanseatic City of Hamburg (wd:Q1055): instance of urban municipality in Germany, instance of Einheitsgemeinde of Germany, instance of federated state of Germany, city and state in the North of Germany, instance of urban district of Hamburg, instance of free imperial city, instance of Hanseatic city, instance of city-state, instance of metropolis, instance of port city, instance of big city
8. Hamburger SV, also known as HamburgerSV, Hamburg Sport Club, Hamburg SV, H.S.V., HSV (wd:Q51974): German sports club based in Hamburg, with its largest branch being its football department, instance of association football club, instance of sports club
9. Hamburg, also known as Hamburg, Minnesota, Hamburg, MN (wd:Q1005682): city in Carver County, Minnesota, United States, instance of city in the United States
10. Hamburg, also known as Hamburg, IA, Hamburg, Iowa (wd:Q998718): city in Fremont County, Iowa, United States, instance of city in the United States

[Assistant] The entity "Hamburg S-Bahn" corresponds to wd:Q693956 in Wikidata. Next, I will look for properties related to the opening date or inception date of this entity. Common properties for such information include "inception" (P571) or "date of official opening." I will check the properties of this entity to find the relevant date.

[Tool]
Got 150 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                                                    | object                                                                                |
| --------------------------- | ----------------------------------------------------------- | ------------------------------------------------------------------------------------------ |
| Hamburg S-Bahn (wd:Q693956) | instance of (wdt:P31)                                       | S-Bahn (wd:Q95723)                                                                         |
| Hamburg S-Bahn (wd:Q693956) | country (wdt:P17)                                           | Germany (wd:Q183)                                                                          |
| Hamburg S-Bahn (wd:Q693956) | located in the administrative territorial entity (wdt:P131) | Hamburg (wd:Q1055)                                                                         |
| Hamburg S-Bahn (wd:Q693956) | coordinate location (wdt:P625)                              | POINT(10.000000 53.550000) (geo:wktLiteral)                                                |
| Hamburg S-Bahn (wd:Q693956) | Commons category (wdt:P373)                                 | S-Bahn Hamburg                                                                             |
| Hamburg S-Bahn (wd:Q693956) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/S-Bahn%20Hamburg%20Type%20474%201.jpg> |
| Hamburg S-Bahn (wd:Q693956) | part of (wdt:P361)                                          | wd:Q2234721                                                                                |
| Hamburg S-Bahn (wd:Q693956) | inception (wdt:P571)                                        | 1907-01-01T00:00:00Z (xsd:dateTime)                                                        |
| Hamburg S-Bahn (wd:Q693956) | has part(s) (wdt:P527)                                      | S3 (wd:Q19368685)                                                                          |
| Hamburg S-Bahn (wd:Q693956) | official website (wdt:P856)                                 | <http://www.s-bahn-hamburg.de/>                                                            |
| ...                         | ...                                                         | ...                                                                                |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?productionCompany ?productionCompanyLabel ?dissolutionDate WHERE {
  wd:Q143276 wdt:P272 ?productionCompany .
  OPTIONAL {
    ?productionCompany rdfs:label ?productionCompanyLabel FILTER ( LANG( ?productionCompanyLabel ) = "en" )
  }
  OPTIONAL {
    ?productionCompany wdt:P576 ?dissolutionDate
  }
}

The production company of Samurai Champloo is Manglobe. Manglobe has a dissolution date, indicating it is no longer existing.

Is the production company of samurai champloo still existing?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Is the production company of samurai champloo still existing?

[Assistant]
To answer this question, I need to identify the production company of the anime "Samurai Champloo" and then check if that production company is still existing (i.e., not dissolved or defunct).

Step 1: Search for the entity "Samurai Champloo" in Wikidata to get its identifier.
Step 2: Find the production company associated with "Samurai Champloo."
Step 3: Check the status of the production company to see if it is still existing.

I will start with step 1 and search for the entity "Samurai Champloo."

[Tool]
Top 10 entity alternatives:
1. Samurai Champloo (wd:Q143276): instance of anime television series, Japanese anime television series
2. Samurai Champloo (wd:Q66138325): instance of manga series, Japanese manga series
3. Samurai Champloo: Sidetracked, also known as Samurai Champloo HIPHOP Samurai Action (wd:Q3548610): instance of video game, 2006 video game
4. Samurai Champloo soundtrack releases, also known as Music of Samurai Champloo (wd:Q106856784): instance of Wikipedia article covering multiple soundtrack releases, Wikipedia article covering multiple soundtrack releases
5. Samurai Champloo Music Record: Departure, also known as Departure (wd:Q7413091): 2004 soundtrack album by Nujabes / Fat Jon, instance of album
6. Samurai Champloo Music Record: Playlist (wd:Q104829743): 2004 soundtrack album by tsutchie, instance of album
7. Samurai Champloo Music Record: Masta, also known as Masta (wd:Q104829750): 2004 soundtrack album by FORCE OF NATURE / tsutchie, instance of album
8. Samurai Champloo Music Record: Impression, also known as Impression (wd:Q3149468): 2004 soundtrack album by Force of Nature / Nujabes / Fat Jon, instance of album
9. Postmodern Is Old Hat: Samurai Champloo (wd:Q56608596): instance of scholarly article, article
10. samurai, also known as buke, bushi (wd:Q38142)

[Assistant] The entity "Samurai Champloo" as an anime television series is identified as wd:Q143276. Next, I will find the production company associated with this entity.

[Tool]
Got 1 row and 2 columns:
| productionCompany     | productionCompanyLabel |
| --------------------- | ---------------------- |
| Manglobe (wd:Q645476) | Manglobe (en)          |

[Assistant] The production company of the anime "Samurai Champloo" is Manglobe (wd:Q645476). Now, I will check if Manglobe is still existing or if it has been dissolved. I will look for any property indicating its dissolution or end of existence.

[Tool] True

[Assistant] Manglobe has a dissolution date, which means it is no longer existing. Therefore, the production company of Samurai Champloo is not still existing. I will now provide the final answer.

[Tool] Stopped generation process