PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?developer ?developerLabel WHERE {
  wd:Q533822 wdt:P178 ?developer .
  OPTIONAL {
    ?developer rdfs:label ?developerLabel FILTER ( LANG( ?developerLabel ) = "en" )
  }
}

The developer of WordNet is Christiane Fellbaum.

[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

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

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

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

[User] Who developed WordNet?

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

[Tool]
Example 1:
Question:
Who created English Wikipedia?

SPARQL:
SELECT ?uri WHERE {
  wd:Q52 wdt:P170 ?uri .
  ?uri wdt:P31 wd:Q5 .
}

Using entities:
Wikipedia, also known as Wikipedia, the free encyclopedia, The Free Encyclopedia, Wikipedia, the free encyclopedia that anyone can edit, WP, Wikipaedia (wd:Q52): free multilingual online encyclopedia
human, also known as human being, person, people, nonfictional human, non-fictional human (wd:Q5): any member of Homo sapiens, unique extant species of the genus Homo

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
Who created Wikipedia?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q52 wdt:P112 ?uri .
}

Using entities:
Wikipedia, also known as Wikipedia, the free encyclopedia, The Free Encyclopedia, Wikipedia, the free encyclopedia that anyone can edit, WP, Wikipaedia (wd:Q52): free multilingual online encyclopedia

Using properties:
founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt): founder or co-founder of this organization, religion, place or entity, creator

Example 3:
Question:
Who are the developers of DBpedia?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q465 wdt:P112 ?uri .
}

Using entities:
DBpedia, also known as dbpedia.org (wd:Q465): online database project of structured data extracted from Wikipedia

Using properties:
founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt): founder or co-founder of this organization, religion, place or entity, creator

[Assistant] From the examples, it seems that the property "founded by" (wdt:P112) is commonly used to find the developers or founders of projects or organizations. Now I will search for the entity "WordNet" in Wikidata to find its identifier.

[Tool]
Top 10 entity alternatives:
1. WordNet, also known as Princeton WordNet (wd:Q533822): Princeton University's computational lexicon of English, a seman...nodes connected by hypernymy, hyponymy, holonymy, meronymy, etc.
2. word net, also known as wordnet (wd:Q2594143): network of words connected by semantic relationships (synonyms, antonyms, hypernyms, hyponyms, meronyms, holonyms)
3. WordNet (wd:Q125949755)
4. WordNet (wd:Q98000414): chapter in book from 2010
5. WordNet: An Electronic Lexical Database, also known as WordNet, WordNet.  An  Electronic Lexical Database (wd:Q35839029): book edition published in 1998 with Fellbaum as editor
6. Arabic WordNet, also known as AWN (wd:Q28136431)
7. Estonian Wordnet (wd:Q31277898)
8. Malayalam WordNet (wd:Q25112033): WordNet for Malayalam language by CUSAT
9. Chinese WordNet, also known as CWN (wd:Q65924663): Huang et al. wordnet in Chinese
10. GF WordNet (wd:Q112258758): a lexical resource which combines WordNet resources from many languages and makes them compatible within GF

[Assistant] The entity "WordNet" is identified as wd:Q533822 (Princeton WordNet). Now I will check the property "founded by" (wdt:P112) for this entity to see if it contains information about who developed WordNet.

[Tool] Got no rows and 3 columns

[Assistant] The property "founded by" (wdt:P112) does not have any values for WordNet (wd:Q533822). I will now search for other properties related to "developer" or "creator" for the entity WordNet.

[Tool]
Top 10 property alternatives:
1. developer, also known as written by, video game developer, video game dev, game developer, game dev (wd:P178 as p/wdt): organization or person that developed the item, creator
2. software version identifier, also known as software release number, software version number, software release version, software update identifier, software update number (wd:P348 as p/wdt): numeric or nominal identifier of a version of a software program or file format, current or past, has edition or translation, edition number
3. used by, also known as armiger, user, played by, of (wd:P1535 as p/wdt): item or concept that makes use of the subject (use sub-properties when appropriate)
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
5. copyright license, also known as content licence, content license, copyright licence, licence, license (wd:P275 as p/wdt): license under which this copyrighted work is released
6. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as p/wdt): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
7. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant] The property "developer" (wdt:P178) seems to be the correct property for the developer or creator of an item. I will now check the value of the property "developer" (wdt:P178) for the entity WordNet (wd:Q533822).

[Tool]
Got 1 row and 3 columns:
| subject              | property             | object                            |
| -------------------- | -------------------- | --------------------------------- |
| WordNet (wd:Q533822) | developer (wdt:P178) | Christiane Fellbaum (wd:Q4558744) |

[Assistant] The developer of WordNet (wd:Q533822) is Christiane Fellbaum (wd:Q4558744). I will now provide the final answer with this information.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the developer of WordNet using the property 'developer' (wdt:P178). The result identifies Christiane Fellbaum as the developer, which is accurate. The query also optionally retrieves the English label of the developer, which is helpful for readability. The output is correct and complete for the user's question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?highestPoint ?highestPointLabel ?elevation WHERE {
  wd:Q20 wdt:P610 ?highestPoint .
  ?highestPoint wdt:P2044 ?elevation .
  OPTIONAL {
    ?highestPoint rdfs:label ?highestPointLabel FILTER ( LANG( ?highestPointLabel ) = "en" )
  }
}

The highest point of Norway is Galdhøpiggen with an elevation of approximately 2469 meters above sea level.

[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

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

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

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

[User] What is the highest point of Norway?

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

[Tool]
Example 1:
Question:
What is the highest mountain?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q8502 ; wdt:P2044 ?elevation .
}
ORDER BY DESC ( ?elevation )
LIMIT 1

Using entities:
mountain, also known as mt., mtn., mountains, mount (wd:Q8502): large natural elevation of the Earth's surface

Using properties:
elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as wdt): height of the item (geographical object) as measured relative to sea level
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
What is the highest place of Karakoram?

SPARQL:
SELECT ?uri WHERE {
  wd:Q5469 wdt:P610 ?uri
}

Using entities:
Karakoram, also known as Karakoram Mountains, Karakoram Range, Karakoroum, Karakoroum Mountains, Karakorum (wd:Q5469): major mountain range spanning the borders between India, Pakistan, and China

Using properties:
highest point, also known as tallest point, zenith, summit, pinnacle, highest peak (wd:P610 as wdt): point with highest elevation in a region or path, has part(s)

Example 3:
Question:
What is the highest mountain in Italy?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q8502 ; wdt:P17 wd:Q38 ; wdt:P2044 ?elevation .
}
ORDER BY DESC ( ?elevation )
LIMIT 1

Using entities:
Italy, also known as Italia, Republic of Italy, Repubblica Italiana, Italian Republic, ITA (wd:Q38): country in Southern Europe
mountain, also known as mt., mtn., mountains, mount (wd:Q8502): large natural elevation of the Earth's surface

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as wdt): height of the item (geographical object) as measured relative to sea level
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
From the examples, we see two approaches to find the highest point of a country:
1. Query the highest point (property P610) of the country entity.
2. Query mountains (instance of Q8502) in the country and order by elevation (property P2044) to get the highest.

I will first try to find the highest point of Norway using property P610. Let's search for Norway entity first.

[Tool]
Top 10 entity alternatives:
1. Norway, also known as Kingdom of Norway (wd:Q20): country in Northern Europe
2. Norway, also known as Norway, Iowa, Norway, IA (wd:Q1913264): city in Iowa, United States
3. Norway, also known as Norway, MI, Norway, Michigan (wd:Q2480177): city in Dickinson County, Michigan, United States
4. Norway, also known as Norway, SC, Norway, South Carolina (wd:Q3243583): town in South Carolina
5. Kingdom of Norway, also known as Norway, Norwegian Empire (wd:Q2196956): former Kingdom from 872 to 1397
6. Norway, also known as Norway, Maine, Norway, ME (wd:Q2734330): town in Maine, USA
7. Norway, also known as Norway, IN, Norway, Indiana (wd:Q2118814): census-designated place in Indiana
8. Kingdom of Norway, also known as Norway, Norwegian Kingdom (wd:Q2597352): short-lived monarchy in Northern Europe (1814)
9. Norway, also known as Norway, New York, Norway, NY (wd:Q944765): town in New York, USA
10. Norway, also known as Norway, WI (wd:Q3046928): town in Wisconsin, USA

[Assistant] The entity for Norway as a country is wd:Q20. Now I will check if Norway (wd:Q20) has a highest point property (P610).

[Tool]
Got 1 row and 3 columns:
| subject         | property                 | object                    |
| --------------- | ------------------------ | ------------------------- |
| Norway (wd:Q20) | highest point (wdt:P610) | Galdhøpiggen (wd:Q203942) |

[Assistant] Norway's highest point is linked by property P610 and the object is Galdhøpiggen (wd:Q203942). To confirm, I will get the elevation of Galdhøpiggen.

[Tool]
Got 1 row and 3 columns:
| subject                   | property                              | object                |
| ------------------------- | ------------------------------------- | --------------------- |
| Galdhøpiggen (wd:Q203942) | elevation above sea level (wdt:P2044) | 2468.85 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the highest point of Norway using the property 'highest point' (wdt:P610) and its elevation (wdt:P2044). The answer 'Galdhøpiggen' with an elevation of approximately 2469 meters matches the query result and is accurate. The query also optionally retrieves the English label for better readability. The output is correct and complete for the user's question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?inception WHERE {
  wd:Q41304 wdt:P571 ?inception .
}

The Weimar Republic started on November 9, 1918.

[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

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

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

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

[User] When did the Weimar Republic start?

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

[Tool]
Example 1:
Question:
Where is the birthplace of Goethe?

SPARQL:
SELECT ?res WHERE {
  wd:Q5879 wdt:P19 ?res .
}

Using entities:
Johann Wolfgang von Goethe, also known as Johann Wolfgang Von Goethe, Goethe (wd:Q5879): German writer, artist, natural scientist and politician (1749–1832), theatre manager, autobiographer, art historian, travel writer, visual artist, statesperson, mineralogist, art theorist, music critic, philosopher, playwright, theologian, art critic, politician, librettist, librarian, physicist, zoologist, diplomat, aphorist, polymath, botanist, composer, novelist, literary, diarist, painter, writer, jurist, lawyer, poet

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 2:
Question:
when was the founding date of french fifth republic?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q200686 wdt:P571 ?uri .
}

Using entities:
French Fifth Republic, also known as 5th French Republic, French Republic, French 5th Republic, France, Fifth French Republic (wd:Q200686): current system of government of France (1958–present)

Using properties:
inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt): time when an entity begins to exist; for date of official opening use P1619, start time

Example 3:
Question:
Which organizations were founded in 1930?

SPARQL:
SELECT * WHERE {
  ?sub wdt:P571 ?year .
  ?sub wdt:P31 / wdt:P131 * wd:Q43229 .
  FILTER ( year( ?year ) = 1930 ) .
}

Using entities:
organization, also known as organizations, organization in sociology, organisation, institution, organisations (wd:Q43229): social entity established to meet needs or pursue goals

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt): time when an entity begins to exist; for date of official opening use P1619, start time

[Assistant]
From the examples, we see that the property "inception" (wdt:P571) is used to find the start or founding date of an entity. We should first identify the entity for "Weimar Republic" and then query its inception date.

Next, I will search for the entity "Weimar Republic" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Weimar Republic, also known as German Republic, Weimar Germany, Republic of Germany, Germany, German Reich (wd:Q41304): Germany in the years 1918/1919–1933
2. flag of the Weimar Republic, also known as the Weimar Republic flag, Weimar Republic flag (wd:Q4485721): flag
3. Landtag (Weimar Republic) (wd:Q1453030): federated state parliament in German Weimar Republic (1919—1934)
4. history of the Weimar Republic, also known as the Weimar Republic history, Weimar Republic history (wd:Q104731094): aspect of German history
5. historian of the Weimar Republic, also known as historian of Weimar Republic, Weimar Republic historian (wd:Q104730830): historian specializing in history of the Weimar Republic
6. hyperinflation in the Weimar Republic (wd:Q695052): occurrence of hyperinflation in early 20th century Germany
7. states of the Weimar Republic (wd:Q3712151): federated states of the Weimar Republic
8. States of the Weimar Republic (wd:Q3712151): federated states of the Weimar Republic
9. Reichsadler of the Weimar Republic, also known as coat of arms of the Weimar Republic (wd:Q25401250)
10. Landtag of Bavaria (Weimar Republic) (wd:Q812353): Parliament of the Free State of Bavaria during the period of the Weimar Republic

[Assistant] The entity "Weimar Republic" corresponds to wd:Q41304. Now I will query the inception (start) date of the Weimar Republic using the property wdt:P571.

[Tool]
Got 1 row and 1 column:
| inception                           |
| ----------------------------------- |
| 1918-11-09T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the inception date (P571) of the Weimar Republic (Q41304) from Wikidata, which is November 9, 1918. The answer matches the query result and is factually accurate. The query is straightforward and returns the expected date without unnecessary complexity. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q2187039 ?p ?o .
}

The number of employees for the Port of Rotterdam Authority (wd:Q2187039) is not available in Wikidata.

[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

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

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

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

[User] How many perople do the Port of Rotterdam employ?

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

[Tool]
Example 1:
Question:
Who is the mayor of Rotterdam?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q34370 wdt:P6 ?uri .
}

Using entities:
Rotterdam, also known as R'dam, Roffa, Rotjeknor (wd:Q34370): city in South Holland, the Netherlands

Using properties:
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

Example 2:
Question:
How many employees does IBM have?

SPARQL:
SELECT ?emloyees WHERE {
  wd:Q37156 wdt:P1128 ?emloyees .
}

Using entities:
IBM, also known as 18M, International Business Machines Corporation (Armonk, NY), International Business Machines Corporation, IBM Corporation, IBM Corp. (wd:Q37156): American multinational technology corporation

Using properties:
employees, also known as workers, staff, personnel, number of employees, employee count (wd:P1128 as wdt): total number of employees of a company at a given "point in time...not deprecated rank). Add data for recent years, don't overwrite

Example 3:
Question:
How many employees does Google have?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q95 wdt:P1128 ?uri .
}

Using entities:
Google, also known as Big G, google.com, Google Inc., Google LLC, Google, Inc. (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc.

Using properties:
employees, also known as workers, staff, personnel, number of employees, employee count (wd:P1128 as wdt): total number of employees of a company at a given "point in time...not deprecated rank). Add data for recent years, don't overwrite

[Assistant] From the examples, it appears that the property for the number of employees is P1128. Now, I need to find the entity for the Port of Rotterdam to use it in the query. I will search for the entity "Port of Rotterdam" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Port of Rotterdam (wd:Q1027807): largest port in Europe, located in the city of Rotterdam, Netherlands
2. Port of Rotterdam Authority, also known as Directie bedrijfsvoering Havenbedrijf   etc. (wd:Q2187039): manager of Rotterdam's port and industrial area in the Netherlands
3. The Port of Rotterdam (wd:Q59543911): painting by Eugène Boudin
4. Portrait of Erasmus of Rotterdam (wd:Q107122548)
5. Portrait of Erasmus of Rotterdam (wd:Q110572054): painting by Hans Holbein the Younger and workshop (David Owsley Museum)
6. Portrait of Erasmus of Rotterdam (wd:Q116966868): painting by Workshop Lucas Cranach the Elder (Landesmuseum für Kunst und Kulturgeschichte Oldenburg)
7. Portrait of Erasmus of Rotterdam (wd:Q116968152): painting by Copy after Lucas Cranach the Elder or Workshop Lucas Cranach the Elder (Sammlung Würth)
8. Portrait of Erasmus of Rotterdam (wd:Q20809158): painting by Hans Holbein the Younger
9. Portrait of Erasmus of Rotterdam (wd:Q110571788): painting by Hans Holbein the Younger and workshop
10. Portrait of Erasmus of Rotterdam writing (wd:Q105684225): painting by Hans Holbein

[Assistant]
There are two relevant entities: "Port of Rotterdam" (wd:Q1027807) which is the largest port in Europe, and "Port of Rotterdam Authority" (wd:Q2187039) which is the manager of Rotterdam's port and industrial area. Since the question is about employment, it is more likely related to the "Port of Rotterdam Authority" as an organization.

Next, I will check if the property P1128 (number of employees) is available for the entity "Port of Rotterdam Authority" (wd:Q2187039).

[Tool] Got no rows and 3 columns

[Assistant] The entity "Port of Rotterdam Authority" (wd:Q2187039) does not have a direct property for the number of employees (P1128). I will now check if the entity "Port of Rotterdam" (wd:Q1027807) has the property P1128 for the number of employees.

[Tool]
Got 1 row and 3 columns:
| subject                         | property              | object               |
| ------------------------------- | --------------------- | -------------------- |
| Port of Rotterdam (wd:Q1027807) | employees (wdt:P1128) | 385000 (xsd:decimal) |

[Assistant] The entity "Port of Rotterdam" (wd:Q1027807) has the property "number of employees" (P1128) with a value of 385000. This seems quite high for a port, so it might be worth verifying if this number is correct or if it refers to a broader category. However, based on the data available, I will now construct the SPARQL query to retrieve the number of employees for the Port of Rotterdam.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The answer states that the Port of Rotterdam employs 385,000 people, which is an unusually high number for a port. This suggests that the value retrieved might be incorrect or misinterpreted. The property P1128 (number of employees) is typically used for companies or organizations, but the Port of Rotterdam is a port facility, not a company, so this property might not be appropriate or might have incorrect data. It is recommended to verify the nature of the entity and check if there is a more suitable property or qualifier to get the correct number of employees. Also, consider that the Port of Rotterdam Authority (the company managing the port) might be the correct entity to query for employee count, not the port itself. Therefore, the SPARQL query and the answer should be revised accordingly.

[Assistant] Thank you for the feedback. I will revise the approach. Since the Port of Rotterdam is a port facility and not a company, the number of employees property might not be appropriate for it. Instead, I will focus on the "Port of Rotterdam Authority" (wd:Q2187039), which is the organization managing the port. I will check again if there is any property related to the number of employees or staff for this entity, possibly with qualifiers or other related properties. I will search for properties related to "employee" or "staff" for the entity "Port of Rotterdam Authority" (wd:Q2187039).

[Tool]
Top 10 property alternatives:
1. has works in the collection, also known as has items in the collection, works in collection, work in collection, museum housing this person's work, items in the collection (wd:P6379 as p/wdt): collection that has works of this person or organisation (use archives at [P485] for archives)
2. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
3. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
4. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as p/wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
6. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
7. legal form, also known as legal structure, structured as (wd:P1454 as p/wdt): legal form of an entity, instance of

No other items found

[Assistant] There are no direct properties related to employees or staff for the entity "Port of Rotterdam Authority" (wd:Q2187039). I will now try a broader search for properties related to "staff" or "employees" in general to see if there is any other property that might be relevant.

[Tool]
Top 10 property alternatives:
1. employees, also known as workers, staff, personnel, number of employees, employee count (wd:P1128 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): total number of employees of a company at a given "point in time...not deprecated rank). Add data for recent years, don't overwrite
2. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): educational institution attended by subject, affiliation
3. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): sports teams or clubs that the subject represents or represented, member of
4. category for employees of the organization, also known as Academic staff, category for employees of the organisation, Professor (wd:P4195 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): Wikimedia category for people who work or worked at this organization
5. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
6. maximum capacity, also known as capacity, complement, crew, number of seats, seating capacity (wd:P1083 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): number of people allowed for a venue or vehicle
7. significant person, also known as significant people, sigper, sign. person, relevant person, relevant people (wd:P3342 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): person linked to the item in any possible way
8. theorized by, also known as author, supported by, suggested by, proposer, proposed by (wd:P8403 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): subject who suggested or proposed this concept or immaterial invention
9. author, also known as writer, written by, poet, playwright, maker (wd:P50 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
10. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as ps/wdt/prn/wdtn/p/psv/pr/prv/pq/pqn/psn/pqv): author of song lyrics, author

[Assistant] The property P1128 "employees" is the most relevant for the number of employees or staff. Since the "Port of Rotterdam Authority" does not have this property directly, I will check if there are any statements or qualifiers related to employees for this entity. I will list all properties and values for the entity "Port of Rotterdam Authority" (wd:Q2187039) to see if there is any relevant information.

[Tool]
Got 66 rows and 3 columns, showing the first 10 rows below:
| subject                                   | property                                  | object                                       |
| ----------------------------------------- | ----------------------------------------- | -------------------------------------------- |
| Port of Rotterdam Authority (wd:Q2187039) | instance of (wdt:P31)                     | corporation (wd:Q167037)                     |
| Port of Rotterdam Authority (wd:Q2187039) | country (wdt:P17)                         | Netherlands (wd:Q55)                         |
| Port of Rotterdam Authority (wd:Q2187039) | Commons category (wdt:P373)               | Port of Rotterdam Authority                  |
| Port of Rotterdam Authority (wd:Q2187039) | inception (wdt:P571)                      | 2004-01-01T00:00:00Z (xsd:dateTime)          |
| Port of Rotterdam Authority (wd:Q2187039) | official website (wdt:P856)               | <http://www.portofrotterdam.com/>            |
| Port of Rotterdam Authority (wd:Q2187039) | headquarters location (wdt:P159)          | Rotterdam (wd:Q34370)                        |
| Port of Rotterdam Authority (wd:Q2187039) | legal form (wdt:P1454)                    | corporation (wd:Q167037)                     |
| Port of Rotterdam Authority (wd:Q2187039) | has works in the collection (wdt:P6379)   | Stadsarchief Rotterdam (wd:Q3912134)         |
| Port of Rotterdam Authority (wd:Q2187039) | copyright status as a creator (wdt:P7763) | works protected by copyrights (wd:Q73555012) |
| Port of Rotterdam Authority (wd:Q2187039) | Google Knowledge Graph ID (wdtn:P2671)    | <http://g.co/kg/g/1218r9yh>                  |
| ...                                       | ...                                       | ...                                          |

[Assistant] The "Port of Rotterdam Authority" entity has many properties, but none of the first 10 rows show the number of employees. I will now specifically check if there is any statement with property P1128 (number of employees) for this entity, including qualifiers or references.

[Tool] Got no rows and 3 columns

[Assistant]
There are no statements with the property P1128 (number of employees) for the entity "Port of Rotterdam Authority" (wd:Q2187039). Given this, it seems that the number of employees for the Port of Rotterdam Authority is not available in Wikidata.

I will now provide a final response stating that the number of employees for the Port of Rotterdam Authority is not available in Wikidata.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified that the number of employees for the Port of Rotterdam Authority is not available in Wikidata. The ASK query confirms that the entity exists and has some properties, but none provide the employee count. The answer is accurate and complete given the data available.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?film ) AS ?count ) WHERE {
  ?film wdt:P31 wd:Q842256 ; wdt:P577 ?date .
  FILTER ( YEAR( ?date ) = 1978 ) .
  FILTER ( ?film != wd:Q267721 ) .
}

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

There are no other musical films launched in the same year (1978) as Grease.

[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

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

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

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

[User] How many other musical films were launched the same year as Grease?

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

[Tool]
Example 1:
Question:
List all the musicals with music by Leonard Bernstein.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q2743 ; wdt:P86 wd:Q152505 .
}

Using entities:
Leonard Bernstein (wd:Q152505): American conductor and composer (1918–1990), film score composer, musicologist, conductor, composer, pianist
musical, also known as musical play, stage musical, musical theatre, musical theater, lyric drama (wd:Q2743): stage work that combines songs, music, spoken dialogue, acting, and dance

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as wdt): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator

Example 2:
Question:
List all the musicals with music by Elton John.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 / wdt:P279 * wd:Q58483083 ; wdt:P86 wd:Q2808 .
}

Using entities:
Elton John, also known as Reggie Dwight, Rockaday Johnnie, Reg Dwight, Prince Rhino, Sir Elton Hercules John (wd:Q2808): British singer, songwriter and musician, HIV/AIDS activist, recording artist, keyboardist, film actor, composer, musician, lyricist, pianist, singer
dramatico-musical work, also known as musico-dramatic work, dramatic-musical work, dramatic musical work (wd:Q58483083): opera, musical play or show, revue or pantomime for which music ...ecially written; for ballet use "choreographic work" (Q58483088)

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as wdt): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator

[Assistant]
From the examples, I see that "musical films" can be identified as instances of a class related to musical films or musicals. The property "instance of" (wdt:P31) is used to identify the type of an entity. Also, the launch or publication year of a film can be found using the property "publication date" (wdt:P577).

Step 1: Identify the entity for the film "Grease".
Step 2: Find the publication year of "Grease".
Step 3: Find other musical films released in the same year.
Step 4: Count how many such musical films exist excluding "Grease".

I will start by searching for the entity "Grease".

[Tool]
Top 10 entity alternatives:
1. fat, also known as grease, fats and oils, fat or oil, dietary fats, dietary fat (wd:Q127980): esters of three fatty acid chains and the alcohol glycerol, one of the three main macronutrients, also known as triglycerides
2. Grease (wd:Q267721): 1978 film by Randal Kleiser
3. grease, also known as lubricating grease, grease lubricant (wd:Q629823): semi-solid, oily lubricant
4. Grease (wd:Q611626): 1972 musical
5. Grease (wd:Q728791): original song written and composed by Barry Gibb; from the 1978 film "Grease", performed by Frankie Valli
6. Grease (wd:Q3776108): 2010 video game
7. Grease (wd:Q104861673): American media franchise
8. Grease (wd:Q114518793): episode of Cheers (S9 E6)
9. Grease (wd:Q116013684): sardana by Martí de Joan
10. Grease (wd:Q126836847): vocal track by Mina; 1986 studio recording; cover version

[Assistant] The entity for the 1978 film "Grease" is wd:Q267721. Next, I will find the publication year of this film.

[Tool]
Got 2 rows and 1 column:
| publicationDate                     |
| ----------------------------------- |
| 1978-06-13T00:00:00Z (xsd:dateTime) |
| 1978-09-28T00:00:00Z (xsd:dateTime) |

[Assistant] The film "Grease" was released in the year 1978 (two dates in 1978). Now, I will find other musical films that were launched in the same year, 1978. I will search for films that are instances of "musical film" or subclasses of it and have the publication date in 1978. Then I will count how many such films exist excluding "Grease". I will first identify the entity for "musical film".

[Tool]
Top 10 entity alternatives:
1. musical film, also known as film musical, musical movie (wd:Q842256): film genre
2. musical film (wd:L428534-S1)
3. Musical Films (wd:Q121091316): production company
4. Theorising the film musical (wd:Q57622181): doctoral thesis
5. College Course Film: THE HOLLYWOOD MUSICAL (wd:Q108309950): journal article from 'Journal of the University Film and Video Association' published in 1983
6. The Beatles. Una filmografía musical (wd:Q125618465): 1995 edition of written work by Magí Crusells
7. The Beatles. Una filmografía musical (wd:Q125618437): written work by Magí Crusells
8. High School Musical: El Desafio (Mexican film), also known as High School Musical: el desafío (wd:Q2636649): 2008 film directed by Eduardo Ripari
9. Rock This Town Musical Film Fest Pau (wd:Q125736952)
10. film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock

[Assistant] The entity for the musical film genre is wd:Q842256. Now I will write a query to count all musical films (instances of wd:Q842256) released in 1978 excluding "Grease" (wd:Q267721).

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of musical films released in the same year as Grease (1978), excluding Grease itself. The query uses the appropriate properties and filters, and the result (0) matches the answer given. The output is correct and complete.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?marianaDepth ?everestHeight WHERE {
  wd:Q459173 wdt:P2044 ?marianaDepth .
  wd:Q513 wdt:P2044 ?everestHeight .
}

The depth of the Mariana Trench (Challenger Deep) is 10984 meters below sea level, and the height of Mount Everest above sea level is 8848.86 meters. Therefore, the Mariana Trench is deeper than Mount Everest is high.

[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

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

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

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

[User] Is the Mariana Trench deeper than Mount Everest is high (above sea level)?

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

[Tool]
Example 1:
Question:
What is the highest mountain?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q8502 ; wdt:P2044 ?elevation .
}
ORDER BY DESC ( ?elevation )
LIMIT 1

Using entities:
mountain, also known as mt., mtn., mountains, mount (wd:Q8502): large natural elevation of the Earth's surface

Using properties:
elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as wdt): height of the item (geographical object) as measured relative to sea level
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
What country is Mount Everest in?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q513 wdt:P17 ?uri .
}

Using entities:
Mount Everest, also known as Chomolungma, Chomolangma, Zhumulangma, World highest peak, Sagarmāthā (wd:Q513): Earth's highest mountain above sea level, located in the Mahalangur Himal sub-range of the Himalayas

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

Example 3:
Question:
What is the second highest mountain on Earth?

SPARQL:
SELECT ?res WHERE {
  ?res wdt:P31 / wdt:P279 * wd:Q8502 .
  ?res wdt:P2044 ?elevation .
  ?res wdt:P30 / wdt:P361 wd:Q2 .
}
ORDER BY DESC ( ?elevation )
LIMIT 1
OFFSET 1

Using entities:
Earth, also known as World, The Blue Planet, Planet Earth, Mother Earth (wd:Q2): third planet from the Sun in the Solar System
mountain, also known as mt., mtn., mountains, mount (wd:Q8502): large natural elevation of the Earth's surface

Using properties:
elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as wdt): height of the item (geographical object) as measured relative to sea level
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))

[Assistant]
From the examples, we see that the property for elevation above sea level is wdt:P2044. We need to find the depth of the Mariana Trench and the height of Mount Everest above sea level. Then we can compare these two values.

Step 1: Find the depth of the Mariana Trench.
Step 2: Find the height of Mount Everest above sea level.
Step 3: Compare the two values to answer the question.

Let's start with step 1 and find the depth of the Mariana Trench. I will search for the Mariana Trench entity first.

[Tool]
Top 10 entity alternatives:
1. Mariana Trench (wd:Q510): deepest oceanic trench on Earth
2. Marianas Trench (wd:Q3291259): Canadian pop rock band
3. "Mariana Trench" T-waves (wd:Q87292168): scientific article published on 01 April 2015
4. Marianas Trench Marine National Monument (wd:Q6612760): US national monument in the Mariana Archipelago
5. Document Recovered From The Marianas Trench (wd:Q60032271): a tale from the SCP web-based collaborative writing project
6. Obligately barophilic bacterium from the Mariana trench (wd:Q35470633): scientific article
7. Self-powered soft robot in the Mariana Trench (wd:Q118298491)
8. So, How Deep Is the Mariana Trench? (wd:Q63230174)
9. oceanic trench, also known as deep sea trench, trench, submarine trench (wd:Q119253): depressions of the sea floor
10. Silybum marianum, also known as milkthistle, variegated thistle, St. Mary's thistle, Scotch thistle, Saint Mary's thistle (wd:Q193798): species of plant of genus Silybum in family Asteraceae

[Assistant] The Mariana Trench entity is wd:Q510. Now I will find the depth of the Mariana Trench using the appropriate property. I will search for properties related to depth for this entity.

[Tool]
Top 10 property alternatives:
1. lowest point, also known as extreme point deepest, extreme point lowest, deepest point (wd:P1589 as p/wdt): point with lowest elevation in a region or path
2. bathymetry image, also known as file bathymetry, bathymetric map, bathymetric chart (wd:P207 as p/wdt): image showing bathymetric chart, bathymetric map
3. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as p/wdt): height of the item (geographical object) as measured relative to sea level
4. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as p/wdt): body of water on or next to which a place is located, location
5. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
8. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
9. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
10. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as wdtn/wdt/p): identifier from an international authority file of names, subjects, and organizations

No other items found

[Assistant] The property "lowest point" (wdt:P1589) seems to be the most relevant to represent the depth of the Mariana Trench. Let's query the lowest point value for the Mariana Trench.

[Tool]
Got 1 row and 1 column:
| lowestPoint                  |
| ---------------------------- |
| Challenger Deep (wd:Q459173) |

[Assistant] The lowest point of the Mariana Trench is the Challenger Deep (wd:Q459173). Now, I will find the depth of the Challenger Deep. I will search for properties related to depth for this entity.

[Tool]
Top 10 property alternatives:
1. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as p/wdt): height of the item (geographical object) as measured relative to sea level
2. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as p/wdt): body of water on or next to which a place is located, location
3. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
4. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
5. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
6. country, also known as sovereign state, state, land, host country (wd:P17 as p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
7. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
8. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
9. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as wdtn/wdt/p): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)
10. locator map image, also known as locator map, map image, map (wd:P242 as p/wdt): geographic map image which highlights the location of the subject within some larger entity, image

No other items found

[Assistant] There is no direct property for depth for the Challenger Deep. Let's check if there is an elevation above sea level (wdt:P2044) for the Challenger Deep, which might be a negative value representing depth.

[Tool]
Got 1 row and 1 column:
| elevation            |
| -------------------- |
| -10984 (xsd:decimal) |

[Assistant]
The elevation above sea level for the Challenger Deep is -10984 meters, which represents its depth below sea level.

Now let's find the height above sea level of Mount Everest (wd:Q513). I will query the elevation above sea level for Mount Everest.

[Tool]
Got 1 row and 1 column:
| elevation             |
| --------------------- |
| 8848.86 (xsd:decimal) |

[Assistant]
The height above sea level of Mount Everest is 8848.86 meters.

Now I will compare the depth of the Mariana Trench (10984 meters) with the height of Mount Everest (8848.86 meters) to answer the question.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer correctly compares the depth of the Mariana Trench (Challenger Deep) and the height of Mount Everest above sea level using the property elevation above sea level (wdt:P2044). The SPARQL query retrieves the depth as a negative value and the height as a positive value, which is appropriate. The reasoning that the Mariana Trench is deeper than Mount Everest is high is accurate based on the retrieved values. The query and answer are complete and correct.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?suffragette ?suffragetteLabel ?goal ?goalLabel WHERE {
  wd:Q322170 wdt:P463 wd:Q1967499 .
  wd:Q1967499 wdt:P3712 wd:Q205204 .
  wd:Q322170 rdfs:label ?suffragetteLabel
  FILTER ( LANG( ?suffragetteLabel ) = "en" ) wd:Q205204 rdfs:label ?goalLabel FILTER ( LANG( ?goalLabel ) = "en" ) BIND( wd:Q322170 AS ?suffragette ) BIND( wd:Q205204 AS ?goal )
}

The suffragettes (wd:Q322170) stood for women's suffrage (wd:Q205204), which is the right of women to vote.

[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

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

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

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

[User] What did the suffragettes stand for?

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

[Tool] No examples found

[Assistant] There are no similar examples found for this question. Now, I will search for the entity "suffragettes" in Wikidata to understand what it refers to and to find relevant information about what they stood for.

[Tool]
Top 10 entity alternatives:
1. suffragette, also known as suffragettes (wd:Q322170): member of the Woman's Social and Political Union who advocated for women's right to vote
2. suffragettes (wd:L328761-F2)
3. Coontown Suffragettes (wd:Q20004604): 1914 silent short film
4. Song Suffragettes (wd:Q28401911): All Female Songwriter Round
5. The Suffragettes (wd:Q20477383): painting by Victor Pasmore
6. The Clam-Shell Suffragettes (wd:Q20802220): 1915 short film
7. The medical suffragettes (wd:Q50179887): scientific article
8. A Cure for Suffragettes (wd:Q24238887): 1913 film by Edward Dillon
9. Kate Sheppard National Memorial, also known as Tribute to the Suffragettes (wd:Q23073296): memorial to the women's suffrage campaign, located in Christchurch, New Zealand
10. Historiography of the Suffragettes (wd:Q64876675)

[Assistant]
The entity "suffragette" (wd:Q322170) refers to a member of the Woman's Social and Political Union who advocated for women's right to vote. This gives us a clear indication that the suffragettes stood for women's right to vote.

To confirm and elaborate on what the suffragettes stood for, I will look for statements or properties related to the entity wd:Q322170 that describe their goals or causes.

[Tool]
Got 401 rows and 3 columns, showing the first 10 rows below:
| subject                  | property                                       | object                                                                                |
| ------------------------ | ---------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| suffragette (wd:Q322170) | instance of (wdt:P31)                          | ideology (wd:Q7257)                                                                                |
| suffragette (wd:Q322170) | Commons category (wdt:P373)                    | Women's suffrage activists                                                                                |
| suffragette (wd:Q322170) | image (wdt:P18)                                | <http://commons.wikimedia.org/wiki/Special:FilePath/Suffragettes%20taking%20part%20in%20a%20pageant%20by%20the%20National%20Union%20of%20Women%E2%80%99s%20Suffrage%20Societies%2C%20June%201908.jpg> |
| suffragette (wd:Q322170) | subclass of (wdt:P279)                         | woman (wd:Q467)                                                                                |
| suffragette (wd:Q322170) | on focus list of Wikimedia project (wdt:P5008) | Art+Feminism (wd:Q24909800)                                                                                |
| suffragette (wd:Q322170) | field of work (wdt:P101)                       | vandalism (wd:Q6160)                                                                                |
| suffragette (wd:Q322170) | different from (wdt:P1889)                     | suffragist (wd:Q27532437)                                                                                |
| suffragette (wd:Q322170) | topic's main category (wdt:P910)               | wd:Q8824062                                                                                |
| suffragette (wd:Q322170) | member of (wdt:P463)                           | Women's Social and Political Union (wd:Q1967499)                                                                                |
| suffragette (wd:Q322170) | named after (wdt:P138)                         | suffragist (wd:Q27532437)                                                                                |
| ...                      | ...                                            | ...                                                                                |

[Assistant]
The entity suffragette (wd:Q322170) is an instance of ideology (wd:Q7257) and is a member of the Women's Social and Political Union (wd:Q1967499). It is also different from suffragist (wd:Q27532437), which might be a related but distinct concept.

To find what the ideology or cause of suffragettes was, I will look for statements related to the ideology (wd:Q7257) or the Women's Social and Political Union (wd:Q1967499) that describe their goals or causes. I will start by looking at the Women's Social and Political Union.

[Tool]
Got 222 rows and 3 columns, showing the first 10 rows below:
| subject                                          | property                                           | object                                                                                |
| ------------------------------------------------ | -------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- |
| Women's Social and Political Union (wd:Q1967499) | instance of (wdt:P31)                              | organization (wd:Q43229)                                                                                |
| Women's Social and Political Union (wd:Q1967499) | country (wdt:P17)                                  | United Kingdom of Great Britain and Ireland (wd:Q174193)                                                      |
| Women's Social and Political Union (wd:Q1967499) | Commons category (wdt:P373)                        | Women's Social and Political Union                                                                            |
| Women's Social and Political Union (wd:Q1967499) | image (wdt:P18)                                    | <http://commons.wikimedia.org/wiki/Special:FilePath/Annie%20Kenney%20and%20Christabel%20Pankhurst%20REST.png> |
| Women's Social and Political Union (wd:Q1967499) | inception (wdt:P571)                               | 1903-10-10T00:00:00Z (xsd:dateTime)                                                                           |
| Women's Social and Political Union (wd:Q1967499) | short name (wdt:P1813)                             | WSPU (en)                                                                                |
| Women's Social and Political Union (wd:Q1967499) | on focus list of Wikimedia project (wdt:P5008)     | Art+Feminism (wd:Q24909800)                                                                                |
| Women's Social and Political Union (wd:Q1967499) | headquarters location (wdt:P159)                   | London (wd:Q84)                                                                                |
| Women's Social and Political Union (wd:Q1967499) | dissolved, abolished or demolished date (wdt:P576) | 1917-01-01T00:00:00Z (xsd:dateTime)                                                                           |
| Women's Social and Political Union (wd:Q1967499) | founded by (wdt:P112)                              | Emmeline Pankhurst (wd:Q211519)                                                                               |
| ...                                              | ...                                                | ...                                                                                |

[Assistant] The Women's Social and Political Union (wd:Q1967499) is an organization founded in the United Kingdom. To find what they stood for, I will look for properties related to their goals, causes, or ideology. I will search for properties related to "goal" or "cause" for this entity.

[Tool]
Top 10 property alternatives:
1. has goal, also known as intention, mission, objective, objective of project or action, project of (wd:P3712 as p/wdt): desired result or outcome
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
3. movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as p/wdt): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as p/wdt): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
6. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
7. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as p/wdt): founder or co-founder of this organization, religion, place or entity, creator
8. short name, also known as short title, shortname, abbreviation, shortened name, initialism (wd:P1813 as p/wdt): short name of a place, organisation, person, journal, wikidata property, etc. Used by some Wikipedia templates., name
9. political ideology, also known as editorial viewpoint, has political ideology, ideology, official ideology, official political ideology (wd:P1142 as p/wdt): political ideology of an organization or person or of a work (such as a newspaper)
10. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as p/wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place

No other items found

[Assistant] The property "has goal" (wdt:P3712) seems to be the most relevant to find the goals or what the Women's Social and Political Union stood for. I will query the value of this property for the Women's Social and Political Union (wd:Q1967499).

[Tool]
Got 1 row and 3 columns:
| subject                                          | property             | object                        |
| ------------------------------------------------ | -------------------- | ----------------------------- |
| Women's Social and Political Union (wd:Q1967499) | has goal (wdt:P3712) | women's suffrage (wd:Q205204) |

[Assistant]
The Women's Social and Political Union had the goal of "women's suffrage" (wd:Q205204), which means the right of women to vote.

To provide a more complete answer, I will also retrieve the label of "women's suffrage" to confirm its meaning.

[Tool]
Got 85 rows and 3 columns, showing the first 10 rows below:
| subject                       | property   | object                              |
| ----------------------------- | ---------- | ----------------------------------- |
| women's suffrage (wd:Q205204) | rdfs:label | Ayollarning saylov huquqi (uz)      |
| women's suffrage (wd:Q205204) | rdfs:label | ceart vótála do mhná (ga)           |
| women's suffrage (wd:Q205204) | rdfs:label | Cêniyan rê heqa reyi (diq)          |
| women's suffrage (wd:Q205204) | rdfs:label | dreptul de vot al femeilor (ro)     |
| women's suffrage (wd:Q205204) | rdfs:label | droit de vote des femmes (fr)       |
| women's suffrage (wd:Q205204) | rdfs:label | Drwè di vòt di sé fanm (gcr)        |
| women's suffrage (wd:Q205204) | rdfs:label | E drejta e grave për të votuar (sq) |
| women's suffrage (wd:Q205204) | rdfs:label | Emakumeen sufragismoa (eu)          |
| women's suffrage (wd:Q205204) | rdfs:label | Frauenwahlrecht (de)                |
| women's suffrage (wd:Q205204) | rdfs:label | Haki ya wanawake kupiga kura (sw)   |
| ...                           | ...        | ...                                 |

[Assistant]
The label "women's suffrage" in English is "women's suffrage," which means the right of women to vote.

I now have enough information to answer the question: The suffragettes stood for women's right to vote, also known as women's suffrage. I will provide this answer along with the relevant entities.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer correctly identifies that the suffragettes stood for women's suffrage, i.e., the right of women to vote. The SPARQL query is well-constructed, retrieving the suffragettes entity and linking it to their goal of women's suffrage using appropriate properties. The query also retrieves English labels for readability. The answer is complete, accurate, and directly addresses the user's question.