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 ?event ?eventLabel ?deaths ?start ?end WHERE {
  ?event wdt:P31 / wdt:P279 * wd:Q1190554 .
  ?event wdt:P1120 ?deaths .
  ?event wdt:P580 ?start .
  ?event wdt:P582 ?end .
  FILTER ( YEAR( ?start ) <= 1920 && YEAR( ?end ) >= 1910 ) OPTIONAL {
    ?event rdfs:label ?eventLabel FILTER ( LANG( ?eventLabel ) = "en" )
  }
}
ORDER BY DESC ( ?deaths )
LIMIT 1

The event that killed the most people in the years 1910 to 1920 is the 1918-1920 flu pandemic, with an estimated death toll of about 50 million people.

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

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

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

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

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

[User] What event killed the most people in the years 1910 to 1920?

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

[Tool]
Example 1:
Question:
Which holidays are celebrated around the world?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?type wdt:P279 * wd:Q1445650 .
  ?uri wdt:P31 ?type .
}

Using entities:
holiday, also known as observances, Praznik, popular festival, observance, holidays (wd:Q1445650): festive day set aside by custom or by law

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

Example 2:
Question:
What is the name of the university where Obama's wife studied?

SPARQL:
SELECT DISTINCT ?uri ?institute WHERE {
  wd:Q76 wdt:P26 / wdt:P69 / wdt:P361 * ?uri .
  ?uri wdt:P31 * / wdt:P279 * wd:Q3918 .
}

Using entities:
university, also known as uni, universities (wd:Q3918): academic institution for further education
Barack Obama, also known as Honorable Barack Obama, BHO, Obama, Barry O Bomber, President Obama (wd:Q76): president of the United States from 2009 to 2017, community organizer, political writer, statesperson, politician, podcaster, memoirist, academic, lawyer, jurist

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
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)
part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

Example 3:
Question:
Give me the capitals of all countries in Africa.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?country wdt:P31 wd:Q6256 .
  ?country wdt:P30 wd:Q15 .
  ?country wdt:P36 ?uri .
}

Using entities:
Africa, also known as African continent (wd:Q15): continent
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

[Assistant]
The question asks for the event that killed the most people in the years 1910 to 1920. This implies we are looking for a historical event with a high death toll within a specific time range.

Step 1: Identify entities related to "event" and "death toll" or "number of deaths."
Step 2: Identify properties related to the date or time of the event.
Step 3: Filter events that occurred between 1910 and 1920.
Step 4: Sort or find the event with the highest death toll.

I will start by searching for properties related to "death toll" or "number of deaths" to find the appropriate property to use in the query.

[Tool]
Top 10 property alternatives:
1. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): total (cumulative) number of people who died since start as a direct result of an event or cause
2. number of casualties, also known as casualities, number of deaths and injuries (wd:P1590 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of people dead or injured because of this event.  Used wh...e data on number of deaths and number of injured is unavailable.
3. number of victims of killer, also known as number of persons killed, number of killed persons, number of homicide victims, kills, kill count (wd:P1345 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): people killed by the subject, both legal and illegal
4. number of injured, also known as injured, injuries, injury toll, non-fatal injuries, number injured (wd:P1339 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of people with non-fatal injuries in an event
5. case fatality rate, also known as fatality rate, CFR, case fatality ratio, case fatality, case fatality risk (wd:P3457 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): proportion of patients who die of a particular medical condition out of all who have this condition within a given time frame
6. death rate, also known as mortality rate (wd:P10091 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): the total number of persons dead per 1,000 population per year
7. number of losses, also known as defeats, games lost, L, losses, lost (wd:P1356 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of sporting matches, games or events lost
8. quantity buried, also known as burials, graves, number of burials, number of people buried (wd:P2324 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of remains buried or interred, quantity
9. number of survivors, also known as survivors (wd:P1561 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): number of people surviving an event
10. category for people who died here, also known as category for place of death, category of people who died here (wd:P1465 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): category item for people who died in this location, related category

[Assistant]
The property "number of deaths" (wdt:P1120) is the most relevant for the death toll of an event.

Next, I will search for properties related to the date or time of the event to filter events between 1910 and 1920. I will search for "date" or "time" related properties.

[Tool]
Top 10 property alternatives:
1. announcement date, also known as released, date teased, made public on, public announcement date, published (wd:P6949 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): time of the first public presentation of a subject by the creator, of information by the media, point in time
2. day in year for periodic occurrence, also known as date, day, day in year, day of periodic occurrence, day of year (wd:P837 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): when a specific holiday or periodic event occurs. Can be used as property or qualifier
3. point in time, also known as at time, as of, year, when, time of event (wd:P585 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): time when an entity begins to exist; for date of official opening use P1619, start time
5. language style, also known as manner, term register, obsolete, register, sense register (wd:P6191 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): to denote of the way a sense of a word is used, e.g., slang, vulgarism, babytalk, colloquialism, etc.
6. start time, also known as start date, since, valid, join time, joined (wd:P580 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): time an entity begins to exist or a statement starts being valid, point in time
7. publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date or point in time when a work was first published or released, point in time
8. public domain date, also known as copyright end date, PD date (wd:P3893 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date the item enters into the public domain in a jurisdiction
9. recording date, also known as recorded date, record date, recdate, rec. date, date of recording (wd:P10135 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): the date when a recording was made, inception
10. date depicted, also known as depicted date, temporal coverage, shown as at date, depicts date, depicted time (wd:P2913 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date represented in a work (for narrative works use P2408)

[Assistant]
The property "point in time" (wdt:P585) is suitable for indicating the date when an event took place.

Now, I will search for entities that are instances of "event" to narrow down the search to events. I will search for the entity "event."

[Tool]
Top 10 entity alternatives:
1. event, also known as statistics event (wd:Q10290214): in statistics and probability theory, set of outcomes to which a probability is assigned
2. occurrence, also known as perdurants, incident, perdurant, occurring, occurrant (wd:Q1190554): occurrence of a fact or object in space-time; instantiation of a property in an object
3. quick time event, also known as event, QTE, quick time events (wd:Q1392636): video game mechanic
4. event, also known as computer event, Event (computing), event (informatics) (wd:Q3291944): computing operation that can be recognized and handled by software
5. event, also known as activity, events, happening (wd:Q1656682): temporary and scheduled happening, like a conference, festival, competition or similar
6. event (wd:Q100235738): objects in time or instantiations of properties in objects (in philosophy)
7. The Event, also known as Event (wd:Q22192553): documentary about the August days of 1991 in Leningrad
8. An Event, also known as Event (wd:Q3506213): 1969 film by Vatroslav Mimica
9. event (wd:Q5416694): in particle physics, set of particle interactions occurring in a brief span of time
10. event (wd:Q5416692): in computer programming, synchronization primitive

[Assistant]
The entity "event" as a temporary and scheduled happening like a conference, festival, competition, or similar (wd:Q1656682) seems to be the most relevant for historical events.

Next, I will build a SPARQL query to find events (instances of wd:Q1656682) that have a "number of deaths" (wdt:P1120) and a "point in time" (wdt:P585) between 1910 and 1920. I will order the results by the number of deaths in descending order to get the event with the highest death toll.

[Tool] Got no rows and 4 columns

[Assistant]
The query returned no results, which might mean that the events with the highest death tolls in that period are not directly classified as instances of "event" (wd:Q1656682) or the date property used is not wdt:P585.

I will try a broader approach by looking for instances of "historical event" (wd:Q1190554) or "disaster" (wd:Q810689) which might include wars, pandemics, and other large-scale events. I will also check for the property "start time" (wdt:P580) and "end time" (wdt:P582) to filter events that happened between 1910 and 1920.

[Tool]
Got 1 row and 5 columns:
| event                               | eventLabel                  | deaths                 | start                               | end                                 |
| ----------------------------------- | --------------------------- | ---------------------- | ----------------------------------- | ----------------------------------- |
| 1918-1920 flu pandemic (wd:Q178275) | 1918-1920 flu pandemic (en) | 50000000 (xsd:decimal) | 1918-01-01T00:00:00Z (xsd:dateTime) | 1920-12-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies events that are instances or subclasses of occurrences (wd:Q1190554) with a number of deaths (wdt:P1120) and filters them by start and end times overlapping the years 1910 to 1920. It orders the results by the number of deaths in descending order and limits to the top result. The answer, the 1918-1920 flu pandemic with about 50 million deaths, is accurate and well supported by the query results. The query also retrieves labels and relevant properties, making the answer clear and complete. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?country WHERE {
  wd:Q5451 wdt:P17 ?country .
}

Got 7 rows and 1 column:
| country                              |
| ------------------------------------ |
| People's Republic of China (wd:Q148) |
| India (wd:Q668)                      |
| Myanmar (wd:Q836)                    |
| Nepal (wd:Q837)                      |
| Pakistan (wd:Q843)                   |
| Afghanistan (wd:Q889)                |
| Bhutan (wd:Q917)                     |

The Himalayas are located in the following countries: China, India, Myanmar, Nepal, Pakistan, Afghanistan, and Bhutan.

[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 countries is the Himalayas located?

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

[Tool]
Example 1:
Question:
Give me all films produced by Steven Spielberg with a budget of at least $80 million.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P162 wd:Q8877 ; wdt:P31 / wdt:P279 * wd:Q11424 ; wdt:P2130 ?cost .
  FILTER ( ?cost > 80000000 )
}

Using entities:
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
Steven Spielberg, also known as Steven Allan Spielberg, Spielberg (wd:Q8877): American filmmaker (born 1946), science fiction writer, television producer, executive producer, film screenwriter, businessperson, art collector, film director, film producer, entrepreneur, screenwriter, film editor, film actor, director, producer, writer, actor

Using properties:
producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as wdt): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]
capital cost, also known as budget, cost, unit cost (wd:P2130 as wdt): amount of money spent on building or producing an object
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 2:
Question:
Which countries are connected by the Rhine?

SPARQL:
SELECT DISTINCT ?uri ?x ?y WHERE {
  wd:Q584 wdt:P17 ?uri .
  ?uri wdt:P31 wd:Q6256 .
}

Using entities:
Rhine (wd:Q584): river in Western Europe to the North Sea
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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

SPARQL:
SELECT DISTINCT ?s1 WHERE {
  ?s1 wdt:P30 wd:Q15 .
  ?s1 wdt:P31 / wdt:P279 * wd:Q8072 .
  ?s1 wdt:P2044 ?o1 .
}
ORDER BY DESC ( ?o1 )
LIMIT 1

Using entities:
Africa, also known as African continent (wd:Q15): continent
volcano (wd:Q8072): natural, surface vent or fissure usually in a mountainous form

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

[Assistant]
From the examples, I see that to find countries where a geographical feature is located, we can use the property "country" (wdt:P17) for the entity representing the geographical feature.

Next, I will search for the entity representing the Himalayas in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Himalayas, also known as Himalaya, Himálaya, Himalaya Mountains, Himálaya Mountains, Himalayan Mountains (wd:Q5451): mountain range in Asia
2. The Himalayas, also known as Himalayas (wd:Q21546296): 2015 film directed by Lee Seok-hoon
3. Himalayas (wd:Q85766587): Welsh rock band
4. Himalayas (wd:Q100353676): painting by Gaganendranath Tagore
5. Himalayas (wd:Q100374811)
6. Himalayas (wd:Q100403347): painting collection of National Gallery of Modern Art, Bangalore
7. Himalayas (wd:Q20441754): painting by Eliot Clark
8. Himalayas (wd:Q20469856): painting by Sidney Nolan
9. Himalayas (wd:Q20469983): painting by Sidney Nolan (AGNSW, 96.1989)
10. Himalayas (wd:L1125498-S1)

[Assistant] The entity representing the mountain range Himalayas is wd:Q5451. Now I will find the countries (wdt:P17) where the Himalayas (wd:Q5451) are located.

[Tool]
Got 7 rows and 2 columns:
| country                              | countryLabel                    |
| ------------------------------------ | ------------------------------- |
| People's Republic of China (wd:Q148) | People's Republic of China (en) |
| India (wd:Q668)                      | India (en)                      |
| Myanmar (wd:Q836)                    | Myanmar (en)                    |
| Nepal (wd:Q837)                      | Nepal (en)                      |
| Pakistan (wd:Q843)                   | Pakistan (en)                   |
| Afghanistan (wd:Q889)                | Afghanistan (en)                |
| Bhutan (wd:Q917)                     | Bhutan (en)                     |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the countries where the Himalayas are located using the property 'country' (wdt:P17) for the Himalayas (wd:Q5451). The result matches the human-readable answer listing China, India, Myanmar, Nepal, Pakistan, Afghanistan, and Bhutan. The query follows the rules by returning the actual identifiers of the countries. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?stateBrooke ?stateColin WHERE {
  wd:Q2926117 wdt:P19 ?birthPlaceBrooke .
  ?birthPlaceBrooke wdt:P131 * ?stateBrooke .
  wd:Q87192979 wdt:P19 ?birthPlaceColin .
  ?birthPlaceColin wdt:P131 * ?stateColin .
  FILTER ( ?stateBrooke = ?stateColin )
}

Got 2 rows and 2 columns:
| stateBrooke            | stateColin             |
| ---------------------- | ---------------------- |
| United States (wd:Q30) | United States (wd:Q30) |
| Colorado (wd:Q1261)    | Colorado (wd:Q1261)    |

Yes, Brooke Raboutou and Colin Duffy are from the same state of the USA, which is Colorado.

[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] are brooke raboutou and colin duffy from same state of the usa?

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

[Tool]
Example 1:
Question:
Which movies star both Liz Taylor and Richard Burton?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P161 wd:Q34851 .
  ?uri wdt:P161 wd:Q151973 .
}

Using entities:
Richard Burton, also known as Richard Jenkins, Richard Walter Jenkins, Jr. (wd:Q151973): Welsh actor (1925–1984), film producer, film director, stage actor, film actor, producer, director, diarist, actor
Elizabeth Taylor, also known as Liz Taylor, Elizabeth Rosemond Taylor, Dame Elizabeth Taylor, Dame Elizabeth Rosemond Taylor (wd:Q34851): British-American actress, HIV/AIDS activist, television actor, philanthropist, autobiographer, art collector, film producer, stage actor, film actor, 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 2:
Question:
Who is the novelist of the work a song of ice and fire?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q45875 ?p ?uri .
  ?uri wdt:P106 wd:Q6625963 .
}

Using entities:
A Song of Ice and Fire, also known as A Song of Ice and Fire Series, Game of Thrones, Song of Ice and Fire, ASOIAF (wd:Q45875): series of epic fantasy novels by George R. R. Martin
novelist, also known as novel author, novel writer (wd:Q6625963): writer of novels

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 3:
Question:
Which books by Kerouac were published by Viking Press?

SPARQL:
SELECT DISTINCT ?s1 WHERE {
  ?s1 wdt:P123 wd:Q921536 .
  ?s1 wdt:P31 wd:Q47461344 .
  ?s1 wdt:P50 wd:Q160534 .
}

Using entities:
Jack Kerouac, also known as Jean-Louis Kerouac, Kerouac, Jean-Louis Lebris de Kerouac (wd:Q160534): American writer (1922–1969), screenwriter, prose writer, novelist, writer, poet
written work, also known as creative written work, written delivery (wd:Q47461344): any work expressed in writing, such as inscriptions, manuscripts, documents or maps
Viking Press, also known as Viking, Viking Penguin, The Viking Press (wd:Q921536): American book publisher

Using properties:
publisher, also known as video game publisher, software publisher, comic book publisher, sheet music publisher, publishing house (wd:P123 as wdt): organization or person responsible for publishing books, periodicals, printed music, podcasts, games or software
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)
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] The examples found do not directly relate to the question about Brooke Raboutou and Colin Duffy and their states in the USA. I will now search for the entities "Brooke Raboutou" and "Colin Duffy" in Wikidata to identify their respective states.

[Tool]
Top 10 entity alternatives:
1. Brooke Raboutou (wd:Q2926117): American sport climber, competition climber, rock climber
2. Tera Patrick, also known as Linda Ann Hopkins Shapiro, Sadie Jordan, Tara Patrick, Tera Hopkins, Brooke (wd:Q30628): American pornographic actress, erotic photography model, pornographic actor, autobiographer, film producer, film actor, blogger, model
3. Brooke Scullion, also known as Brooke (wd:Q110619704): Irish musical artist, songwriter, singer
4. Brooke, also known as Brooke, Rutland (wd:Q2620721): village in Rutland, England, United Kingdom
5. Victor Brooke, also known as Brooke, Sir Victor Alexander Brooke, 3rd Bt. (wd:Q3557201): British naturalist (1843-1891), naturalist
6. Brooke, also known as Brooke, Norfolk (wd:Q2350389): village in Norfolk, England, United Kingdom
7. Brooke (wd:Q15300112): crater on Venus
8. Brooke (wd:Q3645341): unisex given name
9. Brooke (wd:Q16860538): family name
10. Jocelyn Brooke, also known as Bernard Jocelyn Brooke, Brooke (wd:Q6207104): British writer and botanist (1908-1966), botanist, writer

[Tool]
Top 10 entity alternatives:
1. Colin Duffy (wd:Q87192979): Sport climber from the United States, climber
2. Colin Duffy (wd:Q5145059): Irish Republican
3. Duffy, also known as Amie Ann Duffy, Aimee Anne Duffy (wd:Q192587): singer-songwriter, Welsh singer, film actor, songwriter, composer, singer
4. hake, also known as colin, Hake fish (wd:Q1289807): fish, ambiguous vernacular name
5. Stephen Duffy, also known as Stephen 'Tin Tin' Duffy, Stephen Tin Tin Duffy, Tin Tin, Duffy, Stephen Anthony James Duffy (wd:Q2000460): English songwriter, vocalist; founding member of Duran Duran, singer-songwriter, songwriter, guitarist, singer
6. Colin, also known as Colin (first name), Colin (given name) (wd:Q495635): male given name
7. Collin College, also known as CCCC, Quad C, Collin County Community College District, Collin County Community College, Collin (wd:Q5147228): community college system in Collin County, TX, headquartered in McKinney
8. Colin (wd:Q3278815): 2008 film by Marc Price
9. Duffy, also known as Duffy, Australian Capital Territory, Duffy, Australian Capital Territory, Australia (wd:Q910857): suburb of Canberra, Australia
10. Colin (wd:Q5144839): American-bred Thoroughbred racehorse

[Assistant] I found the entities for Brooke Raboutou (wd:Q2926117) and Colin Duffy (wd:Q87192979), both are sport climbers from the United States. Next, I will look for their respective states in the USA. I will search for properties related to "state" or "place of origin" for these entities.

[Tool]
Top 10 property alternatives:
1. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
2. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
3. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
4. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
5. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as wdt/p): country a person or a team represents when playing a sport, country
6. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
7. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt/p): educational institution attended by subject, affiliation
8. 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)
9. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
10. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as wdt/p): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of

No other items found

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
4. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
5. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as wdt/p): country a person or a team represents when playing a sport, country
6. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
7. name in native language, also known as native name (wd:P1559 as wdt/p): name of a person in their native language, name
8. family name, also known as clan name, last name, surname (wd:P734 as wdt/p): part of full name of person, name
9. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as wdt/p): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
10. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt/p): educational institution attended by subject, affiliation

No other items found

[Tool]
Got 1 row and 3 columns:
| subject                       | property                 | object               |
| ----------------------------- | ------------------------ | -------------------- |
| Brooke Raboutou (wd:Q2926117) | place of birth (wdt:P19) | Boulder (wd:Q192517) |

[Tool]
Got 1 row and 3 columns:
| subject              | property                                                    | object                      |
| -------------------- | ----------------------------------------------------------- | --------------------------- |
| Boulder (wd:Q192517) | located in the administrative territorial entity (wdt:P131) | Boulder County (wd:Q113029) |

[Tool]
Got 1 row and 3 columns:
| subject                     | property                                                    | object              |
| --------------------------- | ----------------------------------------------------------- | ------------------- |
| Boulder County (wd:Q113029) | located in the administrative territorial entity (wdt:P131) | Colorado (wd:Q1261) |

[Tool]
Got 1 row and 3 columns:
| subject                    | property                 | object                  |
| -------------------------- | ------------------------ | ----------------------- |
| Colin Duffy (wd:Q87192979) | place of birth (wdt:P19) | Broomfield (wd:Q492819) |

[Tool]
Got 1 row and 3 columns:
| subject                 | property                                                    | object              |
| ----------------------- | ----------------------------------------------------------- | ------------------- |
| Broomfield (wd:Q492819) | located in the administrative territorial entity (wdt:P131) | Colorado (wd:Q1261) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the states associated with the birthplaces of Brooke Raboutou and Colin Duffy by traversing the administrative territorial entities (wdt:P131*). It then filters for cases where these states are the same. The execution result shows that both are linked to Colorado (wd:Q1261), confirming they are from the same state. The answer is accurate and complete, and the query follows best practices by returning the actual identifiers. No further refinement is necessary.


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT ( COUNT( DISTINCT ?president ) AS ?count ) WHERE {
  ?president p:P39 ?statement .
  ?statement ps:P39 wd:Q218295 ; pq:P580 ?startTime .
  FILTER ( ?startTime > "1990-12-31" ^^ xsd:date )
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 3 (xsd:int) |

There have been 3 different presidents of Russia who took the position after 1990: Boris Yeltsin, Vladimir Putin, and Dmitry Medvedev.

[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 different presidents of Russia have there been that took the position after 1990?

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

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

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

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

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

Example 2:
Question:
Give me a list of all critically endangered birds.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P171 * wd:Q5113 .
  ?uri wdt:P141 wd:Q219127 .
}

Using entities:
Critically Endangered, also known as CR, critically endangered species (wd:Q219127): IUCN conservation category
bird, also known as avian species, birds (wd:Q5113): class of vertebrates characterized by wings, a feather-covered body and a beak

Using properties:
IUCN conservation status, also known as conservation status (wd:P141 as wdt): conservation status assigned by the International Union for Conservation of Nature
parent taxon, also known as higher taxon, taxon parent (wd:P171 as wdt): closest parent taxon of the taxon in question, subclass of

Example 3:
Question:
In which programming language is GIMP written?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q8038 wdt:P277 ?uri .
}

Using entities:
GIMP, also known as GNU Image Manipulation Program (wd:Q8038): image retouching and editing tool

Using properties:
programmed in, also known as language, programming language, written in (wd:P277 as wdt): the programming language(s) in which the software is developed

[Assistant]
The examples show how to query for specific entities and their properties. Now, let's identify the entities and properties relevant to the question "How many different presidents of Russia have there been that took the position after 1990?"

Step 1: Identify the entity for "president of Russia."
Step 2: Identify the property for the position held (president) and the country (Russia).
Step 3: Identify the property for the start date of the position.
Step 4: Filter the presidents who took the position after 1990.
Step 5: Count the number of distinct presidents.

I will start by searching for the entity "president of Russia."

[Tool]
Top 10 entity alternatives:
1. President of Russia, also known as President of the Russian Federation, President Rossiiskoi Federatsii, President of the Russian Soviet Federative Socialist Republic (wd:Q218295): head of state of the RSFSR (office established in 1991) and Russia
2. Presidential Administration of Russia, also known as Federal State Budgetary Enterpri...ation of the President of Russia, Kremlin, Office of the President of Russia, President Office of Russia, the Kremlin (wd:Q2060629): executive office of the President of Russia
3. Acting President of Russia (wd:Q4127082): acting head of state post in Russia's constitution
4. Executive Order of the President of Russia, also known as Ukaz of the President of Russia, Decree of the President of Russia, Ukase of the President of Russia (wd:Q2061228): Russian legal act
5. Presidential symbols of Russia (wd:Q3920601)
6. Hospital of Directorate of President of Russia, also known as Federal State Budgetary Institution United Hospital with Clinic, United Hospital with Clinic of t...ment of President Office Affairs (wd:Q30890458): hospital in Moscow
7. President of Brazil meets President of Russia (wd:Q17655540): Wikinews article
8. Russian Federation Presidential Certificate of Honour, also known as Certificate of Merit of the President of Russia, Certificate of the President of the Russian Federation (wd:Q211167): honorary award bestowed by the President of Russia
9. Heraldic Council of the President of Russia (wd:Q4135940)
10. lifespan timeline of presidents of Russia (wd:Q28155224)

[Assistant] The entity "President of Russia" is wd:Q218295. Next, I need to find the property that links a person to the position of President of Russia. This is likely a property indicating the position held by a person. I will search for properties related to "position held" for the entity "President of Russia."

[Tool]
Top 10 property alternatives:
1. position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): subject currently or formerly holds the object position or public office
2. position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): persons who hold and/or held the position
3. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): position or specialism of a player on a team
4. expression, gesture or body pose, also known as action, expression, facial expression, gesture, movement (wd:P6022 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): qualifier on "depicts" (P180) for human position of an individual in an artwork
5. ranking, also known as peak position, place, placing, position, rank (wd:P1352 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): subject's ordinal position as qualitatively evaluated relative to other members of a group
6. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
7. 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
8. office contested, also known as contested office, contested position, position contested (wd:P541 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): title of office which election will determine the next holder of
9. position held by head of the organization, also known as position held by head of the organisation, secretary's position, president's position, position held by head of the organization, office held by head of the organisation (wd:P2388 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): position of the head of this item
10. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

[Assistant] The property "position held" (wdt:P39) is the one that indicates the position or public office a person currently or formerly holds. Next, I will find the property that indicates the start date of holding a position. I will search for properties related to "start date" or "start time."

[Tool]
Top 10 property alternatives:
1. start time, also known as start date, since, valid, join time, joined (wd:P580 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): time an entity begins to exist or a statement starts being valid, point in time
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): time when an entity begins to exist; for date of official opening use P1619, start time
3. earliest date, also known as no earlier than, terminus post quem, start date (earliest), on or after this date, minimum date (wd:P1319 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): earliest date at which an event could have happened. Use as qualifier for other date properties
4. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
5. Gregorian calendar start date, also known as adoption of the Gregorian calendar, Gregorian calendar first used, first date (N.S.) (wd:P7295 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date the Gregorian calendar was first used
6. date of official opening, also known as launch date, launched, officially opened on, official opening, official opening time (wd:P1619 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date or point in time a place, organization, or event officially opened, start time, inception
7. start of covered period, also known as coverage start date, covered period start (wd:P7103 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): start of period covered by an archive set, a historical book, or a collection
8. service entry, also known as commissioned, time of service entry, service introduction, launch date, in service (wd:P729 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date or point in time on which a piece or class of equipment entered operational service, start time
9. UTC date of spacecraft launch, also known as time of spacecraft launch, spacecraft launch time, spacecraft launch date, launch time, launch date (wd:P619 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date of spacecraft launch in UTC
10. publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date or point in time when a work was first published or released, point in time

[Assistant]
The property "start time" (wdt:P580) indicates the time an entity begins to exist or a statement starts being valid, which can be used as the start date of holding a position.

Now, I will write a SPARQL query to find the distinct presidents of Russia (wd:Q218295) who took the position (wdt:P39) after 1990 (using wdt:P580 for start time) and count them.

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

[Assistant]
The query returned 0, which seems incorrect because there have been presidents of Russia after 1990. The issue might be that the entity wd:Q218295 represents the position "President of Russia" as a general office, but the actual position held by individuals might be represented by different entities or qualifiers.

I will try a different approach: find persons who held the position "President of Russia" (wd:Q218295) using the property "position held" (wdt:P39) and check their start time (wdt:P580) for the position. I will first list some presidents of Russia with their start times to understand the data structure better.

[Tool] Got no rows and 3 columns

[Assistant]
The query returned no results, which suggests that the start time (wdt:P580) might not be used as a qualifier for the position held (wdt:P39) in this case.

I will try to find the presidents of Russia by searching for humans who held the position "President of Russia" (wd:Q218295) and then check their terms of office or start dates using other properties.

I will first find persons who held the position "President of Russia" (wd:Q218295).

[Tool]
Got 3 rows and 2 columns:
| president                   | presidentLabel       |
| --------------------------- | -------------------- |
| Dmitry Medvedev (wd:Q23530) | Dmitry Medvedev (en) |
| Boris Yeltsin (wd:Q34453)   | Boris Yeltsin (en)   |
| Vladimir Putin (wd:Q7747)   | Vladimir Putin (en)  |

[Assistant]
There are three distinct presidents of Russia found who held the position: Boris Yeltsin, Vladimir Putin, and Dmitry Medvedev. Now I need to verify that they took the position after 1990.

I will check the start date of their presidency terms. I will look for the property "term start" or similar for these presidents. I will search for properties related to "term start" for the entity "President of Russia" (wd:Q218295).

[Tool]
Top 10 property alternatives:
1. 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
2. term length of position, also known as term length, time in position, term of position, position term, length of term (wd:P2097 as wdt/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
3. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
4. FAST ID, also known as Faceted Application of Subject Terminology ID, FAST subject heading, fst, worldcat.org/fast (wd:P2163 as wdt/wdtn/p): authority control identifier in WorldCat's “FAST Linked Data” authority file
5. official residence, also known as resides at, lives in, palace, presidential mansion, presidential palace (wd:P263 as wdt/p): the residence at which heads of government and other senior figures officially reside, residence
6. replaces, also known as supersedes, succeeds, replaced, previous job holder, preceded by (wd:P1365 as wdt/p): person, state or item replaced. Use "structure replaces" (P1398)...item was not replaced or predecessor and successor are identical, follows
7. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
8. main regulatory text, also known as regulated by, statutory authorization, statutory authority, legally established by, legal basis (wd:P92 as wdt/p): text setting the main rules by which the subject is regulated

No other items found

[Assistant]
There is no direct property for "term start" for the entity "President of Russia." I will try to find the start date of the presidency for each president by checking the qualifiers of the "position held" (wdt:P39) statements for these individuals.

I will query the start dates (qualifier pq:P580) of the position held (wdt:P39) for Boris Yeltsin, Vladimir Putin, and Dmitry Medvedev.

[Tool]
Got 4 rows and 3 columns:
| president                   | presidentLabel       | startTime                           |
| --------------------------- | -------------------- | ----------------------------------- |
| Boris Yeltsin (wd:Q34453)   | Boris Yeltsin (en)   | 1991-07-10T00:00:00Z (xsd:dateTime) |
| Vladimir Putin (wd:Q7747)   | Vladimir Putin (en)  | 2000-05-07T00:00:00Z (xsd:dateTime) |
| Dmitry Medvedev (wd:Q23530) | Dmitry Medvedev (en) | 2008-05-07T00:00:00Z (xsd:dateTime) |
| Vladimir Putin (wd:Q7747)   | Vladimir Putin (en)  | 2012-05-07T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query returned a count of 0, which is incorrect given the known historical facts. The query attempts to count presidents of Russia who started their term after 1990, but it uses the property P39 (position held) with the qualifier P580 (start time) without ensuring the position is specifically 'President of Russia' (wd:Q218295). However, the entity Q218295 includes both the President of the RSFSR and the President of the Russian Federation, which might cause confusion. Also, the filter uses a dateTime type, but the start time might be stored as a date or a string, so the filter might fail. Furthermore, the query does not retrieve the actual presidents to verify the results.

Suggested improvements:
- Confirm the correct entity for 'President of Russia' after 1990, likely wd:Q30461 (President of the Russian Federation).
- Use the correct property and qualifiers to get the start date of the presidency.
- Retrieve the actual presidents and their start dates to verify correctness.
- Use xsd:date for filtering if the start time is a date.
- Return the list of presidents to check the results before counting.

The current query needs to be reworked to correctly identify presidents who took office after 1990 and to return the correct count.

[Assistant]
Thank you for the feedback. I will rework the query considering the following:

1. Use the correct entity for "President of Russia" after 1990, which is likely wd:Q30461 (President of the Russian Federation).
2. Retrieve the actual presidents and their start dates to verify correctness before counting.
3. Use xsd:date for filtering the start date.
4. Ensure the position held is specifically "President of the Russian Federation" (wd:Q30461).

I will first list the presidents who held the position "President of the Russian Federation" (wd:Q30461) along with their start dates to verify the data.

[Tool]
Got 3,541 rows and 3 columns, showing the first 5 and last 5 rows below:
| president                         | presidentLabel           | startTime                           |
| --------------------------------- | ------------------------ | ----------------------------------- |
| Catherine Goldstein (wd:Q1050970) | Catherine Goldstein (en) | 1991-01-01T00:00:00Z (xsd:dateTime) |
| Jack Gajos (wd:Q111434926)        | Jack Gajos (en)          | 1991-01-01T00:00:00Z (xsd:dateTime) |
| Robert Laurent (wd:Q107175322)    | Robert Laurent (en)      | 1991-01-01T00:00:00Z (xsd:dateTime) |
| Maria Marques (wd:Q107190504)     | Maria Marques (en)       | 1991-01-01T00:00:00Z (xsd:dateTime) |
| Alain Pitoun (wd:Q107659176)      | Alain Pitoun (en)        | 1991-01-01T00:00:00Z (xsd:dateTime) |
| ...                               | ...                      | ...                                 |
| Nabil Dmaidi (wd:Q99979980)       | Nabil Dmaidi (en)        | 2025-01-05T00:00:00Z (xsd:dateTime) |
| Nathalie Charnaux (wd:Q43196742)  | Nathalie Charnaux (en)   | 2025-01-09T00:00:00Z (xsd:dateTime) |
| Jana Maškarová (wd:Q108383534)    | Jana Maškarová (en)      | 2025-01-27T00:00:00Z (xsd:dateTime) |
| Lamri Adoui (wd:Q98176980)        | Lamri Adoui (en)         | 2025-01-30T00:00:00Z (xsd:dateTime) |
| wd:Q133454626                     |                          | 2025-03-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The query returned many results, including many individuals who are not presidents of Russia. This suggests that the property "position held" (wdt:P39) with the position "President of the Russian Federation" (wd:Q30461) is used for many other entities as well.

I will refine the query to only consider humans (wd:Q5) who held the position "President of the Russian Federation" (wd:Q30461) and retrieve their start dates. This should filter out irrelevant entities.

[Tool]
Got 3,524 rows and 3 columns, showing the first 5 and last 5 rows below:
| president                         | presidentLabel           | startTime                           |
| --------------------------------- | ------------------------ | ----------------------------------- |
| Catherine Goldstein (wd:Q1050970) | Catherine Goldstein (en) | 1991-01-01T00:00:00Z (xsd:dateTime) |
| Alain Pitoun (wd:Q107659176)      | Alain Pitoun (en)        | 1991-01-01T00:00:00Z (xsd:dateTime) |
| Maria Marques (wd:Q107190504)     | Maria Marques (en)       | 1991-01-01T00:00:00Z (xsd:dateTime) |
| Pierre Bolet (wd:Q111192834)      | Pierre Bolet (en)        | 1991-01-01T00:00:00Z (xsd:dateTime) |
| Robert Laurent (wd:Q107175322)    | Robert Laurent (en)      | 1991-01-01T00:00:00Z (xsd:dateTime) |
| ...                               | ...                      | ...                                 |
| Nabil Dmaidi (wd:Q99979980)       | Nabil Dmaidi (en)        | 2025-01-05T00:00:00Z (xsd:dateTime) |
| Nathalie Charnaux (wd:Q43196742)  | Nathalie Charnaux (en)   | 2025-01-09T00:00:00Z (xsd:dateTime) |
| Jana Maškarová (wd:Q108383534)    | Jana Maškarová (en)      | 2025-01-27T00:00:00Z (xsd:dateTime) |
| Lamri Adoui (wd:Q98176980)        | Lamri Adoui (en)         | 2025-01-30T00:00:00Z (xsd:dateTime) |
| wd:Q133454626                     |                          | 2025-03-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The query still returns many results that are not actual presidents of Russia. This indicates that the position "President of the Russian Federation" (wd:Q30461) is linked to many entities that are not relevant.

I will try a different approach: I will look for the known presidents of Russia (Boris Yeltsin, Vladimir Putin, Dmitry Medvedev) and check their start dates for the position "President of the Russian Federation" (wd:Q30461) to confirm the correct data.

I will query the start dates of the presidency for these three known presidents.

[Tool] Got no rows and 3 columns

[Assistant]
The query returned no results for the known presidents with the position "President of the Russian Federation" (wd:Q30461). This suggests that the position held by these individuals might still be linked to the entity "President of Russia" (wd:Q218295) rather than "President of the Russian Federation" (wd:Q30461).

I will retry the query for the known presidents with the position "President of Russia" (wd:Q218295) but will use xsd:date for filtering and retrieve their start dates.

[Tool]
Got 4 rows and 3 columns:
| president                   | presidentLabel       | startTime                           |
| --------------------------- | -------------------- | ----------------------------------- |
| Boris Yeltsin (wd:Q34453)   | Boris Yeltsin (en)   | 1991-07-10T00:00:00Z (xsd:dateTime) |
| Vladimir Putin (wd:Q7747)   | Vladimir Putin (en)  | 2000-05-07T00:00:00Z (xsd:dateTime) |
| Dmitry Medvedev (wd:Q23530) | Dmitry Medvedev (en) | 2008-05-07T00:00:00Z (xsd:dateTime) |
| Vladimir Putin (wd:Q7747)   | Vladimir Putin (en)  | 2012-05-07T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the distinct presidents of Russia who started their term after 1990 by filtering on the start time of their position as president (wd:Q218295). The answer matches the known historical fact that Boris Yeltsin, Vladimir Putin, and Dmitry Medvedev have been presidents of Russia since 1990. The query uses appropriate properties and entities and returns the count as requested. The output is correct and complete.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?work ) AS ?count ) WHERE {
  wd:Q7245 wdt:P800 ?work .
  ?work wdt:P31 ?type .
  VALUES ?type {
    wd:Q7725634 wd:Q8261 wd:Q49084
  }
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 2 (xsd:int) |

According to Wikidata, Mark Twain wrote 2 literary works classified as either literary work, novel, or short story: 'Adventures of Huckleberry Finn' and 'The Adventures of Tom Sawyer'. The data might be incomplete, as these are his two most famous works.

[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 literary works did Mark Twain write in his lifetime?

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

[Tool]
Example 1:
Question:
Give me all companies in the advertising industry.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q4830453 ; wdt:P452 wd:Q39809 .
}

Using entities:
marketing, also known as communications, sales, public relations, publicity, promotion (wd:Q39809): study and process of promoting, distributing, and selling products or services to customers
business (wd:Q4830453): organization undertaking commercial, industrial, or professional activity

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)
industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as wdt): specific industry of company or organization, part of

Example 2:
Question:
Where is Sungkyunkwan University?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  VALUES ?p {
    wdt:P17 wdt:P276 wdt:P131
  }
  wd:Q41085 ?p ?uri .
}

Using entities:
Sungkyunkwan University, also known as 성균관대학교 (wd:Q41085): private university in Seoul, South Korea

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
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

Example 3:
Question:
Give me all companies in Munich.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?type wdt:P279 * wd:Q4830453 .
  ?uri wdt:P31 ?type ; wdt:P159 wd:Q1726 .
}

Using entities:
Munich, also known as Monachium, Münich, München, Munchen, Muenchen (wd:Q1726): capital and most populous city of Bavaria, Germany
business (wd:Q4830453): organization undertaking commercial, industrial, or professional activity

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
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)

[Assistant] The examples did not directly relate to literary works or authors. Next, I will search for the entity "Mark Twain" in Wikidata to find his identifier.

[Tool]
Top 10 entity alternatives:
1. Mark Twain, also known as Samuel L. Clemens, Samuel Langhorne Clemens, Quintus Curtius Snodgrass, Samuel Clemens (wd:Q7245): American author and humorist (1835–1910), science fiction writer, opinion journalist, children's writer, autobiographer, travel writer, prose writer, journalist, humorist, novelist, aphorist, teacher, writer
2. 2362 Mark Twain, also known as Mark Twain (wd:Q959983): asteroid
3. Mark Twain (wd:Q6770075): crater on Mercury
4. Mark Twain (wd:Q6770076): 2001 documentary film on the life of Mark Twain directed by Ken Burns
5. Mark Twain (wd:Q66716403): 1873 article in Cartoon portraits and biographical sketches of men of the day
6. Mark Twain, also known as Mark Twain, St. Louis (wd:Q6770071): neighborhood of St. Louis, Missouri, United States
7. Rosa 'Mark Twain', also known as Mark Twain (wd:Q83668756): rose cultivar
8. Mark Twain (wd:Q116958637): bronze sculpture by unidentified artist
9. Mark Twain (wd:Q20174185): painting by Charles Noel Flagg
10. Mark Twain (wd:Q79493007): print by Samuel Johnson Woolf (American, 1880-1948) (1920.11)

[Assistant] The entity for Mark Twain as an American author and humorist is wd:Q7245. Next, I will search for properties related to literary works or writings associated with Mark Twain.

[Tool]
Top 10 property alternatives:
1. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as wdt/p): notable scientific, artistic or literary work, or other work of significance among subject's works
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as wdt/p): language in which the writer has written their work, languages spoken, written or signed
4. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
5. has works in the collection, also known as has items in the collection, works in collection, work in collection, museum housing this person's work, items in the collection (wd:P6379 as wdt/p): collection that has works of this person or organisation (use archives at [P485] for archives)
6. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as wdt/p): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
7. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
8. SELIBR ID, also known as LIBRIS, National Library of Sweden, SE-LIBR ID (wd:P906 as wdt/wdtn/p): identifier per National Library of Sweden Libris library catalog
9. 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
10. The Literary Encyclopedia person ID, also known as LE author ID, LE person ID, Literary Encyclopedia author ID, Literary Encyclopedia person ID, Literary Encyclopedia person identifier (wd:P11870 as wdt/p): identifier for an author in The Literary Encyclopedia

No other items found

[Assistant] The property "notable work" (wdt:P800) seems to be the most relevant to find literary works written by Mark Twain. I will now write a SPARQL query to count the number of notable works of Mark Twain.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 2 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly counts the number of notable works (wdt:P800) attributed to Mark Twain (wd:Q7245). However, the answer states "2 notable literary works," which might be misleading because the property P800 includes notable works in general, not necessarily only literary works. Also, the count of 2 seems low for Mark Twain, who is known for multiple literary works. It would be better to refine the query to specifically count literary works authored by Mark Twain, for example by filtering works that are instances of literary work (e.g., instance of wd:Q7725634 or similar). This would provide a more accurate and comprehensive answer to the question about how many literary works Mark Twain wrote in his lifetime.

[Assistant] Thank you for the feedback. I will refine the query to count the number of works authored by Mark Twain that are specifically instances of literary works. First, I will search for the entity representing "literary work" to use it as a filter in the query.

[Tool]
Top 10 entity alternatives:
1. literary work, also known as work in literature, work (literature), work (literary), literary text (wd:Q7725634): written work read for enjoyment or edification
2. DARK HORSE by Michèle Betty, also known as Literary work (wd:Q125465635): Book by Michèle Betty
3. Dura-Europos archival photograph of back of P. CtYBR inv. DP 111, also known as Literary work (wd:Q119126424): archival photograph of back of p. ctybr inv. dp 111 from dura-europos
4. Dura-Europos archival photograph of front of P. CtYBR inv. DP 92, also known as Literary work (wd:Q119126432): archival photograph of front of p. ctybr inv. dp 92 from dura-europos
5. Dura-Europos archival photograph of front of P. CtYBR inv. DP 89, also known as Literary work (wd:Q119126448): archival photograph of front of p. ctybr inv. dp 89 from dura-europos
6. Dura-Europos archival photograph of front of P. CtYBR inv. DP 87, also known as Literary work (wd:Q119126454): archival photograph of front of p. ctybr inv. dp 87 from dura-europos
7. Dura-Europos archival photograph of front of P. CtYBR inv. DP 64, also known as Literary work (wd:Q119126503): archival photograph of front of p. ctybr inv. dp 64 from dura-europos
8. Dura-Europos archival photograph of back of P. CtYBR inv. DP 64, also known as Literary work (wd:Q119126501): archival photograph of back of p. ctybr inv. dp 64 from dura-europos
9. Dura-Europos archival photograph of back of P. CtYBR inv. DP 44, also known as Literary work (wd:Q119126531): archival photograph of back of p. ctybr inv. dp 44 from dura-europos
10. Dura-Europos archival photograph of back of P. CtYBR inv. DP 92, also known as Literary work (wd:Q119126431): archival photograph of back of p. ctybr inv. dp 92 from dura-europos

[Assistant] The entity for literary work is wd:Q7725634. I will now refine the SPARQL query to count the number of works by Mark Twain that are instances of literary work (wd:Q7725634).

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 2 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly counts the number of literary works that Mark Twain wrote which are explicitly classified as instances of literary work in Wikidata. However, the result of 2 seems quite low given Mark Twain's prolific writing career. This might be due to incomplete or inconsistent data in Wikidata or the query's strict filtering for instance of literary work (wd:Q7725634). It would be beneficial to consider other relevant subclasses or related properties that might capture more of his works, such as novels, short stories, or other literary forms. Also, including labels optionally could help verify the works retrieved. Therefore, the query is sensible but needs refinement to ensure completeness and accuracy of the answer.

[Assistant] Thank you for the feedback. To improve completeness, I will explore subclasses of "literary work" (wd:Q7725634) to include works that are instances of these subclasses as well. This may capture novels, short stories, and other literary forms. I will first find subclasses of wd:Q7725634.

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

[Assistant] The query failed due to the use of the SERVICE wikibase:label, which is not supported by the endpoint. I will rewrite the query without using SERVICE and just retrieve the subclasses IRIs.

[Tool]
Got 10 rows and 1 column:
| subclass                          |
| --------------------------------- |
| comics (wd:Q1004)                 |
| captivity narrative (wd:Q1035168) |
| Dramatic text (wd:Q10381029)      |
| chess book (wd:Q103820137)        |
| multi-volume work (wd:Q10432278)  |
| wd:Q10512799                      |
| leiwen (wd:Q10529868)             |
| Inventarium Sveciæ (wd:Q10536424) |
| humoresque (wd:Q1056378)          |
| legal commentary (wd:Q105688416)  |

[Assistant] I found some subclasses of literary work, but many seem unrelated or too specific. I will try to find subclasses that are more relevant to Mark Twain's works, such as novels or short stories. I will search for subclasses of literary work with "novel" or "story" in their label.

[Tool]
Top 10 entity alternatives:
1. novel, also known as novels (wd:Q8261): narrative text, normally of a substantial length and in the form of prose describing a fictional and sequential story
2. Novel, also known as Novel, Haute-Savoie (wd:Q666207): commune in Haute-Savoie, France
3. Dear John, also known as Novel (wd:Q1169623): novel by Nicholas Sparks
4. novelty, also known as new, newness, novel (wd:Q12544101): quality or state of not having been seen before or of being new
5. Novel, also known as Alonzo Mario Stevenson (wd:Q7064534): American hip-hop artist, record producer, songwriter, musician, singer
6. Novel (wd:Q7064535): 2008 Malayalam film directed by East Coast Vijayan
7. Novel (wd:Q12500934): 2003 album by singer Joey Pearson
8. novel, also known as novella (wd:Q16934232): new decree or edict in Roman law
9. Argo-T, also known as IMO 5258456, Ines I, Monique, Novel, Plancius (wd:Q115674085): cargo vessel built in 1961
10. Novel (wd:Q37242877): family name

[Assistant] The entity for novel is wd:Q8261. I will also search for the entity for short story.

[Tool]
Top 10 entity alternatives:
1. short story, also known as tale (wd:Q49084): brief work of literature, usually written in narrative prose
2. flash fiction, also known as fast fiction, microfiction, nanofiction, short short story, sudden fiction (wd:Q5457615): style of fictional literature or fiction of extreme brevity
3. Short Story (wd:Q48816140): British thoroughbred racehorse (1923-after 1939)
4. short short story (wd:Q20825947): short story of a much smaller volume
5. Short Story (wd:Q114545764): episode of Family Matters (S1 E3)
6. Short Story (wd:Q102383766): episode of Even Stevens (S03 E09)
7. [Short story] (wd:Q77987583): scientific article published on 01 February 1999
8. Short Story (wd:Q15754649): journal
9. short story (wd:L1235263-S2)
10. short story (wd:L734123-S1)

[Assistant] The entity for short story is wd:Q49084. I will now refine the SPARQL query to count the number of works by Mark Twain that are instances of literary work (wd:Q7725634) or novel (wd:Q8261) or short story (wd:Q49084).

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 2 (xsd:int) |

[Assistant] The count is still 2, which suggests that only two works are classified under these types for Mark Twain in Wikidata. To verify, I will retrieve the labels of these works to see which ones are counted.

[Tool]
Got 2 rows and 2 columns:
| work                                        | workLabel                           |
| ------------------------------------------- | ----------------------------------- |
| Adventures of Huckleberry Finn (wd:Q215410) | Adventures of Huckleberry Finn (en) |
| The Adventures of Tom Sawyer (wd:Q326914)   | The Adventures of Tom Sawyer (en)   |

[Tool] Stopped generation process