PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?numberOfSeats WHERE {
  wd:Q33091469 wdt:P1342 ?numberOfSeats .
}

Got 1 row and 1 column:
| numberOfSeats     |
| ----------------- |
| 733 (xsd:decimal) |

The current German Bundestag, which is the 20th German Bundestag, has 733 seats.

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

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

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

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

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

[User] How many seats are there in the current German Bundestag ?

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

[Tool]
Example 1:
Question:
Which state of the United States of America has the highest density?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q35657 ; wdt:P2046 ?area ; wdt:P1082 ?population .
  BIND( ( ?population / ?area ) AS ?density ) .
}
ORDER BY DESC ( ?density )
LIMIT 1

Using entities:
U.S. state, also known as U.S. states, US state, USA state, U.S.A. state, United States states (wd:Q35657): constituent political entity of the United States of America

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
Which television shows were created by John Cleese?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q5398426 .
  {
    ?uri wdt:P170 wd:Q25014 .
  } UNION {
    ?uri wdt:P170 / wdt:P527 wd:Q25014 .
  }
}

Using entities:
John Cleese, also known as John Marwood Cleese (wd:Q25014): English comedian and actor (born 1939), television actor, autobiographer, film producer, film director, screenwriter, stage actor, voice actor, film actor, comedian, writer, actor
television series, also known as TV show, TV-series, television show, TV series (wd:Q5398426): connected set of television program episodes under the same title

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)
has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).

Example 3:
Question:
Who is the governor of Texas?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1439 wdt:P1313 wd:Q5589725 .
  wd:Q5589725 wdt:P1308 ?uri .
}

Using entities:
Texas, also known as Lone Star State, US-TX, TX, Texas, United States, Tex. (wd:Q1439): state of the United States of America
Governor of Texas, also known as Governor of the State of Texas, Texas Governor (wd:Q5589725): head of state and of government of the U.S. state of Texas

Using properties:
position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as wdt): persons who hold and/or held the position
office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as wdt): political office that is fulfilled by the head of the government of this item

[Assistant] The examples did not directly relate to the question about the number of seats in the current German Bundestag. So, I will now search for the entity "German Bundestag" to identify its Wikidata item. Then I will look for a property that indicates the number of seats or members in the Bundestag.

[Tool]
Top 10 entity alternatives:
1. German Bundestag, also known as Bundestag of Germany, German parliament (wd:Q154797): legislature of Germany; parliament
2. 21st German Bundestag, also known as Twenty-first German Bundestag (wd:Q124661964): legislative term from 2025 to 2029 (expected)
3. 20th German Bundestag, also known as Twentieth German Bundestag (wd:Q33091469): legislative term from 2021 to 2025
4. 1st German Bundestag, also known as First German Bundestag (wd:Q30542687): legislative term from 1949 to 1953
5. 2nd German Bundestag, also known as Second German Bundestag (wd:Q30542689): legislative term from 1953 to 1957
6. 19th German Bundestag, also known as Nineteenth German Bundestag (wd:Q30579723): legislative term from 2017 to 2021
7. 18th German Bundestag, also known as Eighteenth German Bundestag (wd:Q15081430): legislative term from 2013 to 2017
8. 10th German Bundestag, also known as Tenth German Bundestag (wd:Q30542755): legislative term from 1983 to 1987
9. 17th German Bundestag, also known as Seventeenth German Bundestag (wd:Q30542764): legislative term from 2009 to 2013
10. 16th German Bundestag, also known as Sixteenth German Bundestag (wd:Q30542763): legislative term from 2005 to 2009

[Assistant]
The entity "German Bundestag" is wd:Q154797, which represents the legislature of Germany. However, the question asks about the current German Bundestag, which refers to the current legislative term. The current legislative term is the 20th German Bundestag (wd:Q33091469), which is from 2021 to 2025.

Next, I will search for properties related to the number of seats or members for the entity "20th German Bundestag" (wd:Q33091469).

[Tool]
Top 10 property alternatives:
1. number of seats, also known as membership quantity, number of seats (members), quantity of members, seats (members) (wd:P1342 as wdt/p): total number of seats/members in an assembly (legislative house or similar)
2. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as wdt/p): presiding member of an organization, group or body, director / manager, significant person
3. elected in, also known as re-elected in, election (wd:P2715 as wdt/p): election in which a person gained a position (as qualifier), or a position or legislative term is/was elected (as main value)
4. meeting of, also known as term of, body meeting, session of, organization meeting, legislative term of (wd:P13188 as wdt/p): subject is a meeting or session of this organization
5. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
6. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
7. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as wdt/p): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
8. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as wdt/p): significant or notable events associated with the subject
9. Commons category, also known as category on Wikimedia Commons, Wikimedia Commons category, Wikimedia Commons cat, Commons cat, commonscat (wd:P373 as wdt/p): name of the Wikimedia Commons category containing files related to this item (without the prefix "Category:")
10. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time

No other items found

[Assistant]
The property "number of seats" (wdt:P1342) is the appropriate property to get the total number of seats/members in an assembly.

I will now write a SPARQL query to get the number of seats for the current German Bundestag, which is the 20th German Bundestag (wd:Q33091469).

[Tool]
Got 1 row and 1 column:
| numberOfSeats     |
| ----------------- |
| 733 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the number of seats for the current German Bundestag (20th German Bundestag, wd:Q33091469) using the property number of seats (wdt:P1342). The answer 733 matches the query result and is accurate. The query is concise and returns the appropriate identifier and value. No further refinement is needed.


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT ?population ?year WHERE {
  wd:Q183 wdt:P1082 ?population .
  wd:Q183 p:P1082 ?statement .
  ?statement ps:P1082 ?population ; pq:P585 ?time .
  BIND( YEAR( ?time ) AS ?year ) FILTER ( ?year >= 2010 )
}
ORDER BY ?year

There is only population data available for Germany for the year 2022, which is 84,358,845. There is no population data for the year 2010 or earlier available in the knowledge graph. Therefore, it is not possible to determine if Germany had a population growth of at least 1% since 2010 based on the available data.

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

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

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

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

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

[User] Did Germany have a population growth of at least 1% since 2010?

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

[Tool]
Example 1:
Question:
When was Jack Wolfskin founded?

SPARQL:
SELECT ?date WHERE {
  wd:Q536133 wdt:P571 ?date .
}

Using entities:
Jack Wolfskin, also known as Jack Wolfskin Ausrüstung für Draussen GmbH & Co. KGaA (wd:Q536133): German outdoors clothing and equipment manufacturer and retail chain

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 2:
Question:
In which country is Mecca located?

SPARQL:
SELECT DISTINCT ?res WHERE {
  wd:Q5806 wdt:P131 + ?res .
  ?res wdt:P31 wd:Q6256 .
}

Using entities:
Mecca, also known as Mother of All Settlements, Umm al-Qurā, The Holy City of Mecca, Mecca (Saudi Arabia), mecca (wd:Q5806): Saudi Arabian city and capital of the Makkah province
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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)

Example 3:
Question:
When did the Ming dynasty dissolve?

SPARQL:
SELECT DISTINCT ?date WHERE {
  wd:Q9903 wdt:P576 ?date .
}

Using entities:
Ming dynasty, also known as Ming period, Ming imperium, Ming China, Ming-era, Ming Empire (wd:Q9903): imperial dynasty of China from 1368 to 1644

Using properties:
dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as wdt): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time

[Assistant] The examples found do not directly relate to population growth or demographic statistics. I will now identify the entity for Germany and then find relevant properties related to population growth or population change since 2010.

[Tool]
Top 10 entity alternatives:
1. Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
2. Weimar Republic, also known as German Republic, Weimar Germany, Republic of Germany, Germany, German Reich (wd:Q41304): Germany in the years 1918/1919–1933
3. German Reich, also known as Deutsches Reich, German Empire, German Realm, Germany, Imperial Germany (wd:Q1206012): official name for the German nation state from 1871 to 1945, and name of Germany until 1949
4. Burg Drachenfels, also known as Germany (wd:Q1011486): castle
5. Germany (wd:Q5552078): European Parliament constituency
6. Geilenkirchen-Heinsberg, also known as Germany (wd:Q2268218)
7. Germany, also known as Germany, IN, Germany, Indiana (wd:Q18151573): unincorporated community in Clark County, Indiana
8. Germany (wd:Q19147844): poem by Vladimir Mayakovsky
9. Germany, also known as Ludwig, West (wd:Q3839160): Hetalia character
10. Germany, also known as Germany, Texas, Germany, TX (wd:Q15221573): unincorporated community in Houston County, Texas, United States

[Assistant] The entity for Germany is wd:Q183. Next, I will search for properties related to population growth or population change for this entity.

[Tool]
Top 10 property alternatives:
1. population, also known as inhabitants, human population (wd:P1082 as wdt/p): number of people inhabiting the place; number of people of subject
2. birth rate (wd:P8763 as wdt/p): the total number of live births per 1,000 population
3. urban population (wd:P6343 as wdt/p): number of people living within the territorial entity who live in its urban parts, population
4. total fertility rate (wd:P4841 as wdt/p): average number of children that would be born to a woman over her lifetime who lives in this territorial entity
5. rural population (wd:P6344 as wdt/p): number of people living within the territorial entity who live in its rural parts, population
6. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as wdt/p): market value of all officially recognized final goods and services produced within a country in a given period of time
7. female population (wd:P1539 as wdt/p): number of female people inhabiting the place; number of female people of subject, population
8. demographics of topic, also known as demography of topic (wd:P9241 as wdt/p): item that deals with demographics of the subject
9. male population, also known as male inhabitants, number of males (wd:P1540 as wdt/p): number of male people inhabiting the place; number of male people of subject, population
10. death rate, also known as mortality rate (wd:P10091 as wdt/p): the total number of persons dead per 1,000 population per year

No other items found

[Assistant] The property "population" (wdt:P1082) is the most relevant for population data. To determine population growth since 2010, I will look for population values for Germany (wd:Q183) for the years 2010 and the most recent available year. I will query population values with their respective points in time.

[Tool]
Got 1 row and 2 columns:
| population             | year           |
| ---------------------- | -------------- |
| 84358845 (xsd:decimal) | 2022 (xsd:int) |

[Assistant] The data shows the population of Germany in 2022 as 84,358,845. There is no direct population data for the year 2010 in the results. I will now check if there is population data for the year 2010 or close to it.

[Tool] Got no rows and 2 columns

[Assistant] There is no population data for Germany with a point in time qualifier for the year 2010 or earlier. I will now check if there is any population data without a point in time qualifier that might represent the population around 2010.

[Tool]
Got 1 row and 1 column:
| population             |
| ---------------------- |
| 84358845 (xsd:decimal) |

[Assistant] The only population data available for Germany is 84,358,845, which is the recent data from 2022. Since there is no population data for 2010 or earlier, it is not possible to calculate the population growth since 2010. I will now check if there is any property related to population growth rate or population change rate for Germany.

[Tool]
Top 10 property alternatives:
1. population, also known as inhabitants, human population (wd:P1082 as wdt/p): number of people inhabiting the place; number of people of subject
2. birth rate (wd:P8763 as wdt/p): the total number of live births per 1,000 population
3. total fertility rate (wd:P4841 as wdt/p): average number of children that would be born to a woman over her lifetime who lives in this territorial entity
4. urban population (wd:P6343 as wdt/p): number of people living within the territorial entity who live in its urban parts, population
5. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as wdt/p): market value of all officially recognized final goods and services produced within a country in a given period of time
6. rural population (wd:P6344 as wdt/p): number of people living within the territorial entity who live in its rural parts, population
7. death rate, also known as mortality rate (wd:P10091 as wdt/p): the total number of persons dead per 1,000 population per year
8. female population (wd:P1539 as wdt/p): number of female people inhabiting the place; number of female people of subject, population
9. demographics of topic, also known as demography of topic (wd:P9241 as wdt/p): item that deals with demographics of the subject
10. male population, also known as male inhabitants, number of males (wd:P1540 as wdt/p): number of male people inhabiting the place; number of male people of subject, population

No other items found

[Assistant] There is no direct property for population growth rate or population change rate for Germany. Since we only have recent population data for 2022 and no data for 2010 or earlier, it is not possible to determine if Germany had a population growth of at least 1% since 2010 using the available data. I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified that the knowledge graph only contains population data for Germany from the year 2022 onwards and lacks data for 2010 or earlier. The SPARQL query is well-constructed to retrieve population data from 2010 onwards, and the explanation clearly states that it is not possible to determine if Germany had a population growth of at least 1% since 2010 based on the available data. This is a complete and accurate response given the data limitations.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?archipelago ?archipelagoLabel ?numIslands WHERE {
  VALUES ?archipelago {
    wd:Q38095 wd:Q192626
  }
  {
    SELECT ?archipelago ( COUNT( ?island ) AS ?numIslands ) WHERE {
      ?archipelago wdt:P527 ?island .
      ?island wdt:P31 wd:Q23442 .
    }
    GROUP BY ?archipelago
  }
  OPTIONAL {
    ?archipelago rdfs:label ?archipelagoLabel FILTER ( LANG( ?archipelagoLabel ) = "en" )
  }
}
ORDER BY DESC ( ?numIslands )

Got 2 rows and 3 columns:
| archipelago                   | archipelagoLabel       | numIslands   |
| ----------------------------- | ---------------------- | ------------ |
| Galapagos Islands (wd:Q38095) | Galapagos Islands (en) | 20 (xsd:int) |
| Hawaiian Islands (wd:Q192626) | Hawaiian Islands (en)  | 7 (xsd:int)  |

The refined query shows that the Galápagos Islands archipelago has 20 islands, while the Hawaiian Islands archipelago has 7 islands. Therefore, the Galápagos Islands have more islands than the Hawaiian Islands.

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

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

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

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

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

[User] Which archipelago has more islands: the Galápagos Islands or the Hawaiian Islands ?

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

[Tool]
Example 1:
Question:
Where is Syngman Rhee buried?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q171684 wdt:P119 ?uri .
}

Using entities:
Syngman Rhee, also known as Yi Seung-man, Unam, Sŭng-man Yi, Rhee Syng-man, Ri Seung-man (wd:Q171684): President of South Korea from 1948 to 1960, politician, journalist, writer

Using properties:
place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as wdt): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location

Example 2:
Question:
Which companies have more than 1 million employees?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?type wdt:P279 * wd:Q4830453 .
  ?uri wdt:P31 ?type ; wdt:P1128 ?num .
  FILTER ( ?num > 1000000 )
}

Using entities:
business (wd:Q4830453): organization undertaking commercial, industrial, or professional activity

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
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
Who wrote Harry Potter?

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

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

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

[Assistant]
To answer the question "Which archipelago has more islands: the Galápagos Islands or the Hawaiian Islands?", I need to:

1. Identify the Wikidata entities for the Galápagos Islands and the Hawaiian Islands.
2. Find the property that indicates the number of islands in an archipelago.
3. Retrieve the number of islands for both archipelagos.
4. Compare the numbers to determine which has more islands.

I will start by searching for the entities of the Galápagos Islands and the Hawaiian Islands.

[Tool]
Top 10 entity alternatives:
1. Galapagos Islands, also known as Galápagoses, Galápagos Islands, Gallapagos, Gallapagos I., Gallapagos Isl. (wd:Q38095): Archipelago in the Pacific Ocean, part of Ecuador since 1832
2. Galápagos Islands (wd:Q117188122): UNESCO world heritage site in Ecuador
3. Galapagos Islands Expedition, also known as Astor Expedition 1930 (wd:Q132930746): research expedition to the Galapagos Islands 1930
4. Sos Galapagos Islands (wd:Q123373272): 1967 film produced by Paul de Roubaix
5. the Galápagos Islands (wd:L20019-S1)
6. Galápagos Islands xeric scrub, also known as Galápagos Islands scrubland mosaic (wd:Q108049514): terrestrial ecoregion in the Galápagos Islands
7. flora of the Galápagos Islands, also known as flora in the Galápagos Islands, the Galápagos Islands plants, the Galápagos Islands flora, plants of the Galápagos Islands, plants in the Galápagos Islands (wd:Q3073880)
8. Galapagos Biosphere Reserve, also known as Galapagos Islands Biosphere Reserve (wd:Q110564497): UNESCO biosphere reserve in Ecuador
9. Atlas of the Galápagos Islands (wd:Q109285182)
10. Galápagos Islands Xeric Scrub Ecoregion (wd:Q124391072): One Earth Ecoregion

[Assistant]
The entity for the Galápagos Islands as an archipelago is wd:Q38095.

Next, I will search for the entity of the Hawaiian Islands.

[Tool]
Top 10 entity alternatives:
1. Hawaiian Islands, also known as Mokupuni o Hawai‘i, Sandwich Islands (wd:Q192626): archipelago in the Pacific Ocean
2. Northwestern Hawaiian Islands, also known as Northwest Islands, Northwest Hawaiian Islands, Leeward Hawaiian Islands, Leeward Islands (wd:Q183110): small islands and atolls in the Hawaiian archipelago
3. Hawaiian Islands Invitational (wd:Q5684547): football tournament
4. Hawaiian Islands Ministries (wd:Q54857710): American nonprofit organization
5. 2012 Hawaiian Islands Invitational (wd:Q4625747): international football competition
6. Hawaiian Islands Biosphere Reserve (wd:Q5684536)
7. Hawaiian Islands Land Trust, also known as Hawai'i Land Trust (wd:Q16983501): American non-profit organization
8. Flora of the Hawaiian Islands, also known as Flora of Hawaiian Islands (wd:Q123660347): website on the flora of Hawaii
9. Leprosy in Hawaiian Islands (wd:Q93585900)
10. Newlands Resolution, also known as annexation of Hawaii, annexation of the Hawaiian Islands (wd:Q2341456): resolution for U.S. annexation of Hawaii, 1898

[Assistant]
The entity for the Hawaiian Islands as an archipelago is wd:Q192626.

Now, I will search for the property that indicates the number of islands in an archipelago. I will search for properties related to "number of islands".

[Tool]
Top 10 property alternatives:
1. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
2. number of branches, also known as branches, store count, shop count, number of supermakerts, number of shops (wd:P8368 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of branches or stores affiliated with a chain, brand or company
3. is a number of, also known as a number of, the number of, quantifies, number of, is the number of (wd:P11279 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): this entity is a number representing the quantity of this item
4. number of housing units, also known as dwelling-places, housing units, number of dwelling-places (wd:P10814 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of housing units (dwellings) in a specific place (such as city, county, state, country etc.)
5. number of records, also known as entries, rows, records, quantitiy of records, number of rows (wd:P4876 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of values of an identifier or records in a catalog
6. number of houses (wd:P4080 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of houses in given territorial entity
7. collection or exhibition size, also known as size of collection, size of exhibition, number of records, exhibition size, number of objects (wd:P1436 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of items in a collection or exhibition
8. island code of Indonesia, also known as Indonesian island code (wd:P11163 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): identification code for islands of the Republic of Indonesia
9. number of points/goals/set scored, also known as goals scored, score for, points scored, number of points, number of goals (wd:P1351 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): goals / points scored in a match or an event used as qualifier to the participant. Use P1358 for league points.
10. Indonesian Small Islands Directory ID, also known as Direktori Pulau-Pulau Kecil Indonesia ID, DPKI, DPKI ID, PPK-KKP (wd:P4227 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): identifier for DPKI directory of small islands by the Indonesian government

[Assistant] The search did not return a direct property for "number of islands." I will try searching for properties related to "island count" or "count of islands" to find a more specific property.

[Tool]
Top 10 property alternatives:
1. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
2. quantity, also known as amount, total number, total, qty, occurrences (wd:P1114 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of instances of this subject in the universe of the subje...e actual number of instances in Wikidata may be lower or higher)
3. is a number of, also known as a number of, the number of, quantifies, number of, is the number of (wd:P11279 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): this entity is a number representing the quantity of this item
4. number of houses (wd:P4080 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of houses in given territorial entity
5. number of processor cores, also known as number of cores, processor cores, number of CPU cores, CPU cores, cores (wd:P1141 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of independent actual processing units (*not* threads)
6. number of housing units, also known as dwelling-places, housing units, number of dwelling-places (wd:P10814 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of housing units (dwellings) in a specific place (such as city, county, state, country etc.)
7. member count, also known as total members, number of members, count of members, amount of members, membership (wd:P2124 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of entities that are part of an organization at a particular time
8. number of branches, also known as branches, store count, shop count, number of supermakerts, number of shops (wd:P8368 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of branches or stores affiliated with a chain, brand or company
9. number of likes, also known as post likes, post reaction count, post reactions, post upvote count, post upvotes (wd:P10649 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of likes, favorites, stars, upvotes, or reactions received on a social media post or profile
10. island code of Indonesia, also known as Indonesian island code (wd:P11163 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): identification code for islands of the Republic of Indonesia

[Assistant]
There is no direct property explicitly named "number of islands" or similar. However, I know that archipelagos are often linked to their constituent islands through the property "has part" (wdt:P527). I can count the number of islands that are part of each archipelago by querying the number of parts that are instances of islands.

I will now write a query to count the number of islands (instances of island) that are part of the Galápagos Islands (wd:Q38095).

[Tool]
Got 1 row and 1 column:
| numIslands   |
| ------------ |
| 20 (xsd:int) |

[Assistant]
The Galápagos Islands archipelago has 20 islands according to the data.

Next, I will write a similar query to count the number of islands that are part of the Hawaiian Islands (wd:Q192626).

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

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The answer correctly identifies that the Galápagos Islands have more islands than the Hawaiian Islands, based on the counts 20 and 7 respectively. However, the SPARQL query returns multiple duplicate rows for each archipelago instead of a single row per archipelago with the count. This is due to the outer pattern matching islands again after the subquery that already counts islands. The query should be simplified to only return one row per archipelago with the count of islands, without repeating the ?archipelago wdt:P527 ?island pattern outside the subquery. Also, the query returns 27 rows instead of just 2, which is unexpected for this question. Refining the query to remove duplicates and ensure only the two archipelagos are returned with their island counts would improve clarity and correctness of the output.

[Assistant] Thank you for the feedback. I will refine the SPARQL query to remove the duplicate rows and ensure it returns only one row per archipelago with the count of islands. I will do this by using a subquery to count the islands for each archipelago and then return the results with labels without repeating the pattern outside the subquery. I will also ensure the query only returns results for the two specified archipelagos.

[Tool]
Got 2 rows and 3 columns:
| archipelago                   | archipelagoLabel       | numIslands   |
| ----------------------------- | ---------------------- | ------------ |
| Galapagos Islands (wd:Q38095) | Galapagos Islands (en) | 20 (xsd:int) |
| Hawaiian Islands (wd:Q192626) | Hawaiian Islands (en)  | 7 (xsd:int)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of islands for both the Galápagos Islands and the Hawaiian Islands by using the 'has part' property (wdt:P527) and filtering for instances of islands (wd:Q23442). The query returns the expected counts (20 for Galápagos and 7 for Hawaiian), which matches known data. The answer clearly states which archipelago has more islands based on the query result. The query also includes English labels for readability. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?river ?riverLabel ( MAX( ?length ) AS ?maxLength ) WHERE {
  VALUES ?river {
    wd:Q1471 wd:Q1644
  }
  ?river wdt:P2043 ?length .
  OPTIONAL {
    ?river rdfs:label ?riverLabel FILTER ( LANG( ?riverLabel ) = "en" )
  }
}
GROUP BY ?river ?riverLabel

The Elbe river is longer than the Seine river. The maximum length value for the Elbe river is approximately 1094.26 km, while the length of the Seine river is approximately 776.67 km. Therefore, the Elbe river is longer based on the maximum length values.

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

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

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

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

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

[User] which river is longer, the Seine or Elbe？

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

[Tool]
Example 1:
Question:
How heavy is Jupiter's lightest moon?

SPARQL:
SELECT * WHERE {
  ?res wdt:P31 wd:Q61702557 .
  ?res wdt:P2067 ?mass .
}
ORDER BY ?mass
LIMIT 1

Using entities:
moon of Jupiter, also known as Jovial moon, Jovian satellite, moons of Jupiter, natural satellite of Jupiter (wd:Q61702557): natural satellite orbiting Jupiter

Using properties:
mass, also known as displacement, molecular mass, molecular weight, weight (wd:P2067 as wdt): mass (in colloquial usage also known as weight) of the item
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 is the son of Sonny and Cher?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P22 wd:Q179150 .
  ?uri wdt:P25 wd:Q12003 .
}

Using entities:
Cher, also known as Cher Allman, Cher Bono, Cheryl Sarkisian, Cheryl LaPiere, Cherilyn Sarkisian (wd:Q12003): American singer, actress and television personality, recording artist, television actor, character actor, film director, film actor, singer, actor
Sonny Bono, also known as Salvatore Phillip "Sonny" Bono, S. Christy, Scott Christy, Salvatore Phillip Bono, Prince Carter (wd:Q179150): American entertainer, musician and politician (1935–1998), singer-songwriter, television actor, record producer, screenwriter, restaurateur, politician, film actor, singer, actor

Using properties:
father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as wdt): female parent of the subject. For stepmother, use "stepparent" (P3448), parent

Example 3:
Question:
Who is the founder of Penguin Books?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q1336200 wdt:P112 ?o1 .
}

Using entities:
Penguin Books, also known as Penguin Books, Limited (wd:Q1336200): British publishing house

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]
The examples found are not directly related to rivers or their lengths, so I will proceed with the following steps:
1. Search for the entities "Seine" and "Elbe" to confirm their Wikidata IDs.
2. Search for the property related to the length of a river.
3. Construct a query to compare the lengths of the Seine and Elbe rivers.

[Tool]
Top 10 entity alternatives:
1. Seine, also known as river Seine, Seine River (wd:Q1471): river in France
2. Seine, also known as Seine River, river Seine (wd:Q1471): river in France
3. Seine, also known as Paris Department, Seine Department (wd:Q1142326): former French department (1790–1968)
4. 10735 Seine, also known as (10735) Seine, Seine (wd:Q1083941): asteroid
5. seine net, also known as drag net, dragnet, seine (wd:Q56204502): type of fishing net that is dragged through the water
6. Seine (wd:Q7446844): painting series by Vincent van Gogh
7. The Seine River, also known as Seine (wd:Q19969035): sculpture by Antoine Coysevox
8. Seine (wd:Q6123971): organization
9. Seine, also known as IMO 7726847 (wd:Q114141169): dredger
10. Rüdiger Seine, also known as Seine (wd:Q36669584): botanist

[Tool]
Top 10 entity alternatives:
1. Elbe, also known as Elba, Łaba, Labe, Łobjo (wd:Q1644): major river in Central Europe
2. Elbe, also known as Elba, Łaba, Labe, Łobjo (wd:Q1644): major river in Central Europe
3. Elbe (wd:Q689718): municipality in Lower Saxony, Germany
4. Elbe (wd:Q689718): municipality in Lower Saxony, Germany
5. Elbe, also known as Elbe, WA, Elbe, Washington (wd:Q1325167): census designated place in Pierce County, Washington, United States
6. Elbe, also known as Godwana, MV Greenpeace, Maryland, Greenpeace, IMO 5100427 (wd:Q6719575): tugboat
7. Elbe (wd:Q896094): water stream in western Germany, tributary of the Eder
8. Elbe (wd:Q5353680): sailing ship built in 1887
9. Elbe, also known as IMO 9514793 (wd:Q1325104): motor ship built in 2009
10. Elbe, also known as IMO 9199957 (wd:Q1583684): motor ship built in 2000

[Tool]
Top 10 property alternatives:
1. duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): length of time of an event or process
2. length, also known as size, long, LOA, distance, dimension (wd:P2043 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): measured dimension of an object
3. block size, also known as block length (wd:P2599 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): size of block for this block cipher or hash function
4. perimeter, also known as boundary length, circumference, coastline (wd:P2547 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): linear distance around the outside of an object
5. term length of position, also known as term length, time in position, term of position, position term, length of term (wd:P2097 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): length of time in years (unit: Q577) a person (usually a politician) is to serve in a particular position. Do not add bounds., duration
6. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): area occupied by an object
7. width, also known as breadth, bus width, size (wd:P2049 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): width of an object, length
8. height, also known as heighth, size, depth over terrain (wd:P2048 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): vertical length of an entity, length
9. beam, also known as width, breadth, BOA (wd:P2261 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): width of a ship at its widest point measured at its nominal waterline
10. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): height of the item (geographical object) as measured relative to sea level

[Assistant]
The entities for the rivers are:
- Seine: wd:Q1471
- Elbe: wd:Q1644

The property for length (measured dimension of an object) is wdt:P2043.

Now I will construct a query to get the lengths of both rivers and compare them.

[Tool]
Got 3 rows and 3 columns:
| river            | riverLabel | length                |
| ---------------- | ---------- | --------------------- |
| Seine (wd:Q1471) | Seine (en) | 776.67 (xsd:decimal)  |
| Elbe (wd:Q1644)  | Elbe (en)  | 367.644 (xsd:decimal) |
| Elbe (wd:Q1644)  | Elbe (en)  | 1094.26 (xsd:decimal) |

[Assistant] The query results show two different lengths for the Elbe river: 367.644 and 1094.26. The Seine river length is 776.67. To clarify which length is the correct or more relevant one for the Elbe, I will check if there are qualifiers or additional information for these length values.

[Tool]
Got 2 rows and 3 columns:
| subject         | property           | object                |
| --------------- | ------------------ | --------------------- |
| Elbe (wd:Q1644) | length (wdt:P2043) | 367.644 (xsd:decimal) |
| Elbe (wd:Q1644) | length (wdt:P2043) | 1094.26 (xsd:decimal) |

[Tool]
Got 2 rows and 3 columns:
| subject         | property         | object                                       |
| --------------- | ---------------- | -------------------------------------------- |
| Elbe (wd:Q1644) | length (p:P2043) | s:Q1644-6609B336-EBE8-4C03-94BD-2B03F59F3661 |
| Elbe (wd:Q1644) | length (p:P2043) | s:Q1644-8D3D5BA5-2B3A-4079-AF17-1B9463A21B34 |

[Tool]
Got 7 rows and 3 columns:
| subject                                      | property            | object                                       |
| -------------------------------------------- | ------------------- | -------------------------------------------- |
| s:Q1644-6609B336-EBE8-4C03-94BD-2B03F59F3661 | length (ps:P2043)   | 367.644 (xsd:decimal)                        |
| s:Q1644-6609B336-EBE8-4C03-94BD-2B03F59F3661 | wikibase:rank       | wikibase:NormalRank                          |
| s:Q1644-6609B336-EBE8-4C03-94BD-2B03F59F3661 | rdf:type            | wikibase:BestRank                            |
| s:Q1644-6609B336-EBE8-4C03-94BD-2B03F59F3661 | prov:wasDerivedFrom | ref:dba7fcddeb2a585f224ff1b8e09659995064613b |
| s:Q1644-6609B336-EBE8-4C03-94BD-2B03F59F3661 | length (psn:P2043)  | v:4b8de5245a5b7d16287e58a11b59c9cc           |
| s:Q1644-6609B336-EBE8-4C03-94BD-2B03F59F3661 | length (psv:P2043)  | v:1b27fb0780f4fa93a26048b114ab2f85           |
| s:Q1644-6609B336-EBE8-4C03-94BD-2B03F59F3661 | rdf:type            | wikibase:Statement                           |

[Tool]
Got 7 rows and 3 columns:
| subject                                      | property            | object                                       |
| -------------------------------------------- | ------------------- | -------------------------------------------- |
| s:Q1644-8D3D5BA5-2B3A-4079-AF17-1B9463A21B34 | length (ps:P2043)   | 1094.26 (xsd:decimal)                        |
| s:Q1644-8D3D5BA5-2B3A-4079-AF17-1B9463A21B34 | wikibase:rank       | wikibase:NormalRank                          |
| s:Q1644-8D3D5BA5-2B3A-4079-AF17-1B9463A21B34 | rdf:type            | wikibase:BestRank                            |
| s:Q1644-8D3D5BA5-2B3A-4079-AF17-1B9463A21B34 | prov:wasDerivedFrom | ref:0d6e8705da58124a62dd04f022a25f5a47482f4e |
| s:Q1644-8D3D5BA5-2B3A-4079-AF17-1B9463A21B34 | length (psn:P2043)  | v:90c0350e77ef9b6a17103630a86de5e4           |
| s:Q1644-8D3D5BA5-2B3A-4079-AF17-1B9463A21B34 | length (psv:P2043)  | v:5f24a6fd69a5906b2ace8545ae258272           |
| s:Q1644-8D3D5BA5-2B3A-4079-AF17-1B9463A21B34 | rdf:type            | wikibase:Statement                           |

[Assistant]
The Elbe river has two length statements with different values:
- 367.644 (with a reference)
- 1094.26 (with a reference)

Both statements have the rank "BestRank" and "NormalRank," so both are considered valid but the 1094.26 length is likely the more accepted or recent value.

The Seine river length is 776.67.

Based on these values, the Elbe river (1094.26) is longer than the Seine river (776.67).

I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The answer correctly identifies that the Elbe river is longer than the Seine river based on the lengths retrieved. However, the SPARQL query returns two different length values for the Elbe river (367.644 and 1094.26), which is inconsistent and may cause confusion. The query should be refined to select the maximum length value for each river to avoid ambiguity. Additionally, the answer should mention that the maximum length value for the Elbe river is used for comparison.

[Assistant] Thank you for the feedback. I will refine the SPARQL query to select the maximum length value for each river to avoid ambiguity. Then I will update the answer to mention that the maximum length value for the Elbe river is used for comparison.

[Tool]
Got 2 rows and 3 columns:
| river            | riverLabel | maxLength             |
| ---------------- | ---------- | --------------------- |
| Seine (wd:Q1471) | Seine (en) | 776.67 (xsd:decimal)  |
| Elbe (wd:Q1644)  | Elbe (en)  | 1094.26 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the maximum length values for both the Seine and Elbe rivers using their Wikidata identifiers. The query groups by river and label, and the results clearly show that the Elbe river is longer than the Seine river. The answer is accurate and well-supported by the query results. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coordinate WHERE {
  wd:Q1717891 wdt:P625 ?coordinate .
}

The coordinates of the "Sender Teutoburger Wald" broadcasting tower are POINT(8.821830 51.905880). This corresponds to latitude 51.905880 and longitude 8.821830.

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

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

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

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

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

[User] At what coordinates was the "Sender Teutoburger Wald" erected?

[Assistant] Let's start by looking at some 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:
Which languages are spoken in Estonia?

SPARQL:
SELECT * WHERE {
  wd:Q191 wdt:P2936 ?lang .
}

Using entities:
Estonia, also known as ee, Eesti, Eesti Vabariik, EST, Estland (wd:Q191): country in Northern Europe

Using properties:
language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt): language widely used (spoken or written) in this place or at this event or organisation

Example 3:
Question:
Which city has the least inhabitants?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q515 ; wdt:P1082 ?population .
}
ORDER BY ?population
LIMIT 1

Using entities:
city, also known as cities (wd:Q515): large human settlement

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
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]
The question asks for the coordinates of the "Sender Teutoburger Wald." This suggests that "Sender Teutoburger Wald" is likely an entity (a structure or place) in Wikidata, and the coordinates would be a property of that entity.

Step 1: Search for the entity "Sender Teutoburger Wald" in Wikidata to find its identifier.
Step 2: Once the entity is found, look for the property that represents coordinates (usually "coordinate location" with property P625).
Step 3: Construct a SPARQL query to retrieve the coordinates of the entity.

I will start by searching for the entity "Sender Teutoburger Wald."

[Tool]
Top 10 entity alternatives:
1. Sender Teutoburger Wald, also known as Sender Bielstein (wd:Q1717891): broadcasting tower in Germany
2. Teutoburg Forest, also known as Osning, Teutoburger Wald (wd:Q109773): forest in Germany
3. Teutoburger Wald (wd:Q61991772): protected landscape in Lower Saxony, Germany
4. Golfclub Teutoburger Wald (wd:Q27861899)
5. Östlicher Teutoburger Wald (wd:Q62090959): nature reserve in Bielefeld-West, Germany
6. Östlicher Teutoburger Wald (wd:Q60777562): nature reserve in Kreis Lippe, Germany
7. Östlicher Teutoburger Wald (wd:Q60689960): protected area in the European Union defined by the habitats directive in Nordrhein-Westfalen, Germany
8. Sandsteinzug Teutoburger Wald (wd:Q60689997): protected area in the European Union defined by the habitats directive in Nordrhein-Westfalen, Germany
9. Sender Waldburg (wd:Q2270643)
10. Teutoburger Wald-Eisenbahn, also known as Teutoburger Wald Eisenbahn, TWE (wd:Q2407391)

[Assistant] The entity "Sender Teutoburger Wald" corresponds to the broadcasting tower in Germany with the identifier wd:Q1717891. Now, I will look for the coordinates property (usually P625) of this entity.

[Tool]
Top 10 property alternatives:
1. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
2. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as wdt/p): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
3. 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/p): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
6. height, also known as heighth, size, depth over terrain (wd:P2048 as wdt/p): vertical length of an entity, length
7. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

No other items found

[Assistant] The property "coordinate location" (wdt:P625) is the correct property for the coordinates of the entity. Now I will construct a SPARQL query to get the coordinates of "Sender Teutoburger Wald" (wd:Q1717891).

[Tool]
Got 1 row and 1 column:
| coordinate                                 |
| ------------------------------------------ |
| POINT(8.821830 51.905880) (geo:wktLiteral) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the coordinates of the 'Sender Teutoburger Wald' broadcasting tower using the property P625 (coordinate location). The answer provides the coordinates in the correct format with latitude and longitude clearly stated. The query follows the rules by returning the actual identifier and the coordinate literal. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?headOfState ?headOfStateLabel WHERE {
  wd:Q17 wdt:P35 ?headOfState .
  OPTIONAL {
    ?headOfState rdfs:label ?headOfStateLabel FILTER ( LANG( ?headOfStateLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| headOfState           | headOfStateLabel |
| --------------------- | ---------------- |
| Naruhito (wd:Q217096) | Naruhito (en)    |

The current head of state of Japan, the country where Ghost in the Shell is born, is Naruhito.

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

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

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

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

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

[User] in the country where ghost in the shell is born, who is the current head of the state?

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

[Tool]
Example 1:
Question:
What was the last movie with Alec Guinness?

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

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

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

Example 2:
Question:
Give me all movies with Tom Cruise.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P161 wd:Q37079 .
}

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

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

Example 3:
Question:
Who is the tallest player of the Atlanta Falcons?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P54 wd:Q272059 ; wdt:P2048 ?height .
}
ORDER BY DESC ( ?height )
LIMIT 1

Using entities:
Atlanta Falcons, also known as Falcons (wd:Q272059): American football team

Using properties:
height, also known as heighth, size, depth over terrain (wd:P2048 as wdt): vertical length of an entity, length
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

[Assistant] First, I need to identify the country where "Ghost in the Shell" is born. "Ghost in the Shell" is a Japanese media franchise, so I will search for the entity "Ghost in the Shell" to confirm its origin country. Then I will find the current head of state of that country.

[Tool]
Top 10 entity alternatives:
1. Ghost in the Shell (wd:Q1066948): 1995 film by Mamoru Oshii
2. Ghost in the Shell, also known as Ghost in the Shell 3D, Ghost in the Shell: An IMAX 3D Experience (wd:Q22575835): 2017 film directed by Rupert Sanders
3. Ghost in the Shell (wd:Q92580): Japanese media franchise
4. Ghost in the Shell (wd:Q259804): 1997 video game
5. Ghost in the Shell, also known as Kōkaku Kidōtai, Koukaku Kidoutai (wd:Q92582): manga by Masamune Shirow
6. Ghost in the Shell (wd:Q11699759): 2005 mixtape by Styles P
7. Ghost in the shell (wd:Q124841206): scientific article published in 2021
8. M01 Chant I - Making of Cyborg, also known as Theme From Ghost In The Shell, 謡I-Making of Cyborg, Making of Cyborg, Ghost in the Shell Main theme, Ghost In The Shell (wd:Q126960525): Musical composition by Kenji Kawai
9. The Ghost in the Shell, also known as Ghost in the Shell, Kōkaku Kidōtai, Koukaku Kidoutai (wd:Q126095177): 2026 Japanese anime television series
10. Ghost in the Shell 2: Innocence, also known as Innocence (wd:Q1058469): 2004 film by Mamoru Oshii

[Assistant] The entity "Ghost in the Shell" as a Japanese media franchise is wd:Q92580. Now I will find the country of origin for this entity.

[Tool]
Got 1 row and 3 columns:
| subject                        | property                     | object         |
| ------------------------------ | ---------------------------- | -------------- |
| Ghost in the Shell (wd:Q92580) | country of origin (wdt:P495) | Japan (wd:Q17) |

[Assistant] The country of origin for "Ghost in the Shell" is Japan (wd:Q17). Now I will find the current head of state of Japan.

[Tool]
Top 10 property alternatives:
1. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as wdt/p): political office that is fulfilled by the head of state of this item
2. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as wdt/p): official with the highest formal authority in a country/state, director / manager, chairperson
3. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt/p): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
4. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as wdt/p): political office that is fulfilled by the head of the government of this item
5. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
6. diplomatic relation, also known as political relation, political relations, foreign relations, foreign relation, diplomatic relations (wd:P530 as wdt/p): diplomatic relations of the country
7. executive body, also known as executive branch (wd:P208 as wdt/p): branch of government for the daily administration of the territorial entity
8. basic form of government, also known as form of government, government, type of government (wd:P122 as wdt/p): subject's government
9. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt/p): seat of government of a country, province, state or other type of administrative territorial entity
10. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as wdt/p): label for the items in their official language  or their original language, name

No other items found

[Tool]
Got 1 row and 3 columns:
| subject        | property                | object                |
| -------------- | ----------------------- | --------------------- |
| Japan (wd:Q17) | head of state (wdt:P35) | Naruhito (wd:Q217096) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies Japan as the country where 'Ghost in the Shell' was born and retrieves the current head of state, Naruhito. The query uses the appropriate property (wdt:P35) for the head of state and includes an optional label retrieval in English. The answer is accurate and complete based on the data from Wikidata. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?mannerOfDeath ?mannerOfDeathLabel WHERE {
  wd:Q23434 wdt:P1196 ?mannerOfDeath .
  OPTIONAL {
    ?mannerOfDeath rdfs:label ?mannerOfDeathLabel FILTER ( LANG( ?mannerOfDeathLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| mannerOfDeath       | mannerOfDeathLabel |
| ------------------- | ------------------ |
| suicide (wd:Q10737) | suicide (en)       |

Ernest Hemingway died by suicide.

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

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

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

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

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

[User] In which manner did Hemingway die?

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

[Tool]
Example 1:
Question:
What is the profession of Frank Herbert?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q7934 wdt:P106 ?o1 .
}

Using entities:
Frank Herbert, also known as Jr. Franklin Patrick Herbert, Jr. Franklin Herbert, Frank Patrick Herbert, Jr. Frank Patrick Herbert, Franklin Herbert (wd:Q7934): American writer (1920–1986), science fiction writer, prose writer, photographer, journalist, novelist, writer

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

Example 2:
Question:
Who killed Caesar?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q1048 wdt:P157 ?o1 .
}

Using entities:
Julius Caesar, also known as Divine Julius (wd:Q1048): Roman general and dictator (100 – 44 BC), ancient Roman military personnel, Ancient Roman politician, Ancient Roman historian, Ancient Roman priest, military leader, politician, historian, memoirist, writer, orator, ruler, poet

Using properties:
killed by, also known as slaughtered by, slain by, shot dead by, murderer, murdered by (wd:P157 as wdt): person or organization who killed the subject, significant person

Example 3:
Question:
Which U.S. states are in the same time zone as Utah?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q829 wdt:P421 ?timezone .
  ?uri wdt:P31 wd:Q35657 ; wdt:P421 ?timezone .
  FILTER ( ?uri != wd:Q829 )
}

Using entities:
U.S. state, also known as U.S. states, US state, USA state, U.S.A. state, United States states (wd:Q35657): constituent political entity of the United States of America
Utah, also known as Beehive State, State of Utah, Utah, United States, US-UT, UT (wd:Q829): state of the United States of America

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

[Assistant]
The examples show how to query for the manner of death or the killer of a person using properties like "killed by" (wdt:P157). For Hemingway's manner of death, we need to find the appropriate property that describes how he died.

Step 1: Identify the entity for Hemingway.
Step 2: Find the property that corresponds to "manner of death" or similar.
Step 3: Query for the value of that property for Hemingway.

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

[Tool]
Top 10 entity alternatives:
1. Ernest Hemingway, also known as Ernest Miller Hemingway, Ernest Miller Hemmingway, Hemingway, Papa, E. Hemingway (wd:Q23434): American author and journalist (1899–1961), short story writer, war correspondent, screenwriter, prose writer, playwright, journalist, novelist, writer, poet
2. 3656 Hemingway, also known as Hemingway (wd:Q567952): asteroid
3. Hemingway, also known as Hemingway, South Carolina, Hemingway, SC (wd:Q1984173): human settlement in Williamsburg County, South Carolina, United States of America
4. Death in the Afternoon, also known as Hemingway, Hemingway Champagne (wd:Q5247370): cocktail made up of absinthe and Champagne
5. Hemingway (wd:Q15139117): crater on Mercury, novelist
6. Hemingway (wd:Q5711834): fictional character in Marvel Comics
7. Hemingway (wd:Q16870685): family name
8. Hemingway (wd:Q2157602): single by BLØF
9. Hemingway (wd:Q16641530): 2012 film by Derek Hockenbrough
10. Hemingway (wd:Q130532850): given name

[Assistant] The entity for Ernest Hemingway is wd:Q23434. Now, I will search for properties related to "manner of death" or "cause of death" for this entity.

[Tool]
Top 10 property alternatives:
1. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as wdt/p): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
2. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt/p): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
3. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt/p): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
4. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as wdt/p): dissolved, abolished or demolished date, date on which the subject died, end time
5. place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as wdt/p): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
6. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
7. medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt/p): any state relevant to the health of an organism, including diseases and positive conditions
8. work period (end), also known as floruit end, floruit (end of work), flourished (end), retirement, work ends (wd:P2032 as wdt/p): end of period during which a person or group flourished (fl. = "floruit") in their professional activity, end time, floruit
9. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as wdt/p): significant or notable events associated with the subject
10. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): 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 "manner of death" (wdt:P1196) seems to be the most appropriate to answer the question about how Hemingway died. I will now write a SPARQL query to get the manner of death for Ernest Hemingway (wd:Q23434).

[Tool]
Got 1 row and 2 columns:
| mannerOfDeath       | mannerOfDeathLabel |
| ------------------- | ------------------ |
| suicide (wd:Q10737) | suicide (en)       |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the manner of death for Ernest Hemingway using the property 'manner of death' (wdt:P1196). The query returns the identifier and the English label 'suicide', which directly answers the user's question. The answer is accurate and complete based on the data from Wikidata. No further refinement is necessary.