PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q9545 wdt:P2048 ?tonyBlairHeight .
  wd:Q10993 wdt:P2048 ?tigerWoodsHeight .
  FILTER ( ?tonyBlairHeight > ?tigerWoodsHeight )
}

False

[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] Is Tony Blair taller than Tiger Woods?

[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:
Which movies starring Brad Pitt were directed by Guy Ritchie?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?type wdt:P279 * wd:Q11424 .
  ?uri wdt:P31 ?type ; wdt:P161 wd:Q35332 ; wdt:P57 wd:Q192990 .
}

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
Guy Ritchie, also known as Guy Stuart Ritchie, Guy Stewart Ritchie (wd:Q192990): English filmmaker, film producer, film director, screenwriter, entrepreneur, director, judoka
Brad Pitt, also known as William Bradley Pitt, Brad Jolie-Pitt (wd:Q35332): American actor and filmmaker (born 1963), television producer, executive producer, television actor, film producer, film director, voice actor, film actor, producer, director, model, 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
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)
director, also known as film director, movie director, game director, directed by (wd:P57 as wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator

Example 3:
Question:
Who is the author of the interpretation of dreams?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q726382 wdt:P50 ?uri .
}

Using entities:
The Interpretation of Dreams (wd:Q726382): 1899 written work by Sigmund Freud

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

[Assistant] Based on the examples, we need to find the heights of Tony Blair and Tiger Woods and compare them. Let's first identify the entities for Tony Blair and Tiger Woods.

[Tool]
Top 10 entity alternatives:
1. Tony Blair, also known as Rt. Hon. Tony Blair, Sir Anthony Charles Lynton Blair, Sir Tony Blair, The Rt. Hon. Sir Anthony Charles Lynton Blair PC KC, Anthony Blair (wd:Q9545): Prime Minister of the United Kingdom from 1997 to 2007, autobiographer, politician, diplomat, lawyer
2. Tony Blair (wd:Q7821910): 1999 single by Chumbawamba
3. Tony Blair (wd:Q16429010)
4. Tony Blair (wd:Q28052457): painting by Alastair Adams
5. Tony Blair (wd:Q63892269): musical character in the musical TONY! The Blair Musical; the Prime Minister of the United Kingdom and lead figure of the musical
6. Tony Blair Institute (wd:Q30592102): non-profit organization
7. Tony Blair Associates (wd:Q17513270): organization
8. Tony Blair, MP (wd:Q119583376): painting by Philip Oliver Hale (b.1963), Parliamentary Art Collection
9. premiership of Tony Blair, also known as Blair administration (wd:Q7240404): period of the Government of the United Kingdom
10. The Trial of Tony Blair, also known as Trial of Tony Blair (wd:Q1741389): 2007 film

[Assistant] The correct entity for Tony Blair is the first one, `wd:Q9545`. Now let's find the entity for Tiger Woods.

[Tool]
Top 10 entity alternatives:
1. Tiger Woods, also known as Woods, Tiger, Eldrick Tont Woods, Eldrick "Tiger" Woods, Eldrick Tont "Tiger" Woods (wd:Q10993): American golfer, animal trainer, writer, golfer
2. The Tiger Woods Story, also known as Tiger Woods Story (wd:Q7769261): 1998 television film directed by LeVar Burton
3. Tiger Woods Design (wd:Q7801498): company owned by Tiger Woods
4. Tiger Woods Foundation (wd:Q7801499): organization
5. Tiger Woods (book) (wd:Q55635855): book by Jeff Benedict
6. Phil Ivey, also known as Tiger Woods of Poker (wd:Q318464): American poker player, poker player
7. Tiger Woods PGA Tour (wd:Q2520425): golf videogame series
8. Tiger Woods PGA Tour (wd:Q7801501): 2009 video game
9. The Tiger Woods Dubai (wd:Q7769260)
10. Tiger Woods of Bengal (wd:Q27051671): 2016 film by Danny Mamik

[Assistant] The correct entity for Tiger Woods is the first one, `wd:Q10993`. Next, we need to find the property for height in Wikidata.

[Tool]
Top 10 property alternatives:
1. clearance, also known as span height, height of deck bottom, bridge height, height above water, height above valley floor (wd:P2793 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): distance between surface under bridge and bottom of a bridge deck
2. height, also known as heighth, size, depth over terrain (wd:P2048 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): vertical length of an entity, length
3. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): height of the item (geographical object) as measured relative to sea level
4. height of center of mass, also known as center of mass height, centre of gravity height, centre of mass height, CG height, CGZ (wd:P8497 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): distance between the center of gravity and the bottom of this object
5. duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): length of time of an event or process
6. length, also known as size, long, LOA, distance, dimension (wd:P2043 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): measured dimension of an object
7. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): area occupied by an object
8. width, also known as breadth, bus width, size (wd:P2049 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): width of an object, length
9. height of letters (wd:P12549 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): height of the letters of an inscription, height
10. entry height (wd:P13238 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): height of the entrance above ground level for boarding vehicles

[Assistant] The correct property for height is `wd:P2048`. Now we can construct a SPARQL query to get the heights of both Tony Blair and Tiger Woods and compare them.

[Tool]
Got 1 row and 2 columns:
| tonyBlairHeight    | tigerWoodsHeight  |
| ------------------ | ----------------- |
| 1.83 (xsd:decimal) | 185 (xsd:decimal) |

[Assistant]
The height of Tony Blair is 1.83 meters, and the height of Tiger Woods is 1.85 meters. Therefore, Tiger Woods is taller than Tony Blair.

To confirm this with an ASK query, we can check if Tony Blair's height is less than Tiger Woods' height.

[Tool] True

[Assistant]
The ASK query confirms that Tony Blair's height is indeed less than Tiger Woods' height.

Therefore, the answer to the question "Is Tony Blair taller than Tiger Woods?" is **False**.

Here is the final SPARQL query:

```sparql
ASK WHERE {
  wd:Q9545 wdt:P2048 ?tonyBlairHeight .
  wd:Q10993 wdt:P2048 ?tigerWoodsHeight .
  FILTER(?tonyBlairHeight < ?tigerWoodsHeight)
}
```

And the answer is **False**.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query is almost correct, but the execution result is True, which means that Tony Blair is indeed shorter than Tiger Woods. However, the answer provided is False, which contradicts the execution result. Please update the answer to reflect the correct result of the SPARQL query.

[Assistant]
You're right, my previous response was incorrect. The ASK query result is `True`, which means that Tony Blair is indeed shorter than Tiger Woods. Therefore, the correct answer to the question "Is Tony Blair taller than Tiger Woods?" is **False**.

However, since the ASK query result is `True`, the correct answer should be **True** because the query checks if Tony Blair's height is less than Tiger Woods' height, which it is.

Here is the corrected final SPARQL query and answer:

```sparql
ASK WHERE {
  wd:Q9545 wdt:P2048 ?tonyBlairHeight .
  wd:Q10993 wdt:P2048 ?tigerWoodsHeight .
  FILTER(?tonyBlairHeight < ?tigerWoodsHeight)
}
```

And the answer is **True**.

Let me update the answer accordingly.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query is using the wrong comparison operator. The question asks if Tony Blair is taller than Tiger Woods, but the query checks if Tony Blair's height is less than Tiger Woods' height. The comparison operator should be changed from '<' to '>'.

[Assistant]
You are absolutely right. The comparison operator in the SPARQL query should be changed to `>` to correctly reflect the question "Is Tony Blair taller than Tiger Woods?"

Let's update the SPARQL query and re-run it to ensure the correct result.

Here is the updated SPARQL query:

```sparql
ASK WHERE {
  wd:Q9545 wdt:P2048 ?tonyBlairHeight .
  wd:Q10993 wdt:P2048 ?tigerWoodsHeight .
  FILTER(?tonyBlairHeight > ?tigerWoodsHeight)
}
```

Now, let's execute this updated query.

[Tool] False

[Assistant]
The updated ASK query result is `False`, which means that Tony Blair is not taller than Tiger Woods.

Therefore, the correct answer to the question "Is Tony Blair taller than Tiger Woods?" is **False**.

Here is the final SPARQL query:

```sparql
ASK WHERE {
  wd:Q9545 wdt:P2048 ?tonyBlairHeight .
  wd:Q10993 wdt:P2048 ?tigerWoodsHeight .
  FILTER(?tonyBlairHeight > ?tigerWoodsHeight)
}
```

And the answer is **False**.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q26707663 wdt:P19 ?birthPlace .
  FILTER NOT EXISTS {
    ?birthPlace wdt:P31 wd:Q6256
  }
  OPTIONAL {
    ?birthPlace rdfs:label ?birthPlaceLabel .
    FILTER ( LANG( ?birthPlaceLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| birthPlace            | birthPlaceLabel |
| --------------------- | --------------- |
| Buri Ram (wd:Q327510) | Buri Ram (en)   |

Lisa Manoban was born in Buri Ram.

[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] Where was K-pop star Lisa Manoban born?

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

[Tool]
Example 1:
Question:
In which countries do people speak Japanese?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P37 wd:Q5287 .
}

Using entities:
Japanese, also known as Japanese language, Japanesic (wd:Q5287): language spoken in East Asia
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 2:
Question:
When was Jack Wolfskin founded?

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

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

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

Example 3:
Question:
What is the capital of Canada?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q16 wdt:P36 ?o1 .
}

Using entities:
Canada, also known as CA, CAN, Dominion of Canada, ISO 3166-1:CA (wd:Q16): country in North America

Using properties:
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] Based on the examples, we need to identify the entity for Lisa Manoban and the property for place of birth. Let's start by searching for the entity "Lisa Manoban".

[Tool]
Top 10 entity alternatives:
1. Lisa, also known as Pranpriya Manobal, Lisa Manobal, Lalisa Manoban, Lalisa Manobal (wd:Q26707663): Thai rapper, singer, model, dancer and actress (born 1997), singer-songwriter, fashion model, photo model, songwriter, dancer, rapper, singer, actor, model
2. Lisa, also known as Lalisa Manoban, Lisa Manobal, Pranpriya Manobal, Lalisa Manobal (wd:Q26707663): Thai rapper, singer, model, dancer and actress (born 1997), singer-songwriter, fashion model, photo model, songwriter, dancer, rapper, singer, actor, model
3. Lisa Ann, also known as Valeska, Lisa Ann Murphy, Nailin Palin, Lisa Ann Vision, Valeska Encina (wd:Q233259): American pornographic actress, pornographic actor, radio personality, film director, talent agent, film actor, stripper, actor
4. Apple Lisa, also known as Lisa, The Lisa (wd:Q371482): personal computer by Apple Inc.
5. LiSA, also known as Risa Oribe, Oribe Risa, Love is Same All (wd:Q333333): Japanese singer-songwriter (born 1987), composer, singer
6. Laser Interferometer Space Antenna, also known as eLISA, Evolved Laser Interferometer Space Antenna, LISA (wd:Q841982): third large mission of Cosmic Vision; gravitational-wave space observatory
7. Lisa, also known as Lisza (wd:Q3242363): commune in Brașov County, Romania
8. Lisa (wd:Q12724902): commune in Teleorman County, Romania
9. Lisa (wd:Q2726275): village in Moravica District, Serbia
10. Lisa, also known as Lisa (given name), Lisa (first name) (wd:Q1588186): female given name

[Assistant] The correct entity for Lisa Manoban is wd:Q26707663. Now let's search for the property "place of birth".

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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 pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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 pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): the object is a country that recognizes the subject as its citizen, country
4. birthday, also known as b-day, bday, birth day (wd:P3150 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
5. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): full name of a person at birth, if different from their current, generally used name, name
6. category for people born here, also known as category for place of birth, category of people born here (wd:P1464 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): category item that groups people born in this place, related category
7. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): place where a statement is valid, applies to part
8. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
9. country, also known as sovereign state, state, land, host country (wd:P17 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
10. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant]
The correct property for "place of birth" is wd:P19. Now we can construct a simple SPARQL query to find out where Lisa Manoban was born.

Let's execute the following SPARQL query:

```sparql
SELECT ?birthPlace WHERE {
  wd:Q26707663 wdt:P19 ?birthPlace .
}
```

This query selects the value of the `place of birth` property for the entity representing Lisa Manoban.

[Tool]
Got 2 rows and 1 column:
| birthPlace            |
| --------------------- |
| Buri Ram (wd:Q327510) |
| Thailand (wd:Q869)    |

[Assistant]
The query returned two results: Buri Ram (wd:Q327510) and Thailand (wd:Q869). Since Buri Ram is a more specific location, it is likely the correct place of birth. However, to ensure clarity, we can include both results in our answer.

Let's refine the query to include labels for better readability:

```sparql
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q26707663 wdt:P19 ?birthPlace .
  OPTIONAL { ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = "en") }
}
```

This query will provide both the IRI and the English label for the place of birth.

Let's execute this refined query.

[Tool]
Got 2 rows and 2 columns:
| birthPlace            | birthPlaceLabel |
| --------------------- | --------------- |
| Buri Ram (wd:Q327510) | Buri Ram (en)   |
| Thailand (wd:Q869)    | Thailand (en)   |

[Assistant]
The refined query confirms that Lisa Manoban was born in Buri Ram, Thailand.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q26707663 wdt:P19 ?birthPlace .
  OPTIONAL { ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = "en") }
}
```

Answer: Lisa Manoban was born in Buri Ram, Thailand.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query returns both Buri Ram and Thailand as birth places. However, Buri Ram is the more specific location where Lisa Manoban was born. To improve the answer, the SPARQL query should filter out the less specific location (Thailand) and only return Buri Ram.

[Assistant]
Thank you for the feedback. To refine the query, we can add a filter to ensure that only the more specific location (Buri Ram) is returned. We can achieve this by checking the type of the birth place and ensuring it is a city or a more specific location rather than a country.

Let's update the query to include this filter:

```sparql
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q26707663 wdt:P19 ?birthPlace .
  ?birthPlace wdt:P31 wd:Q515 .  # Ensure the birth place is a city
  OPTIONAL { ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = "en") }
}
```

This query will only return the birth place if it is a city (wd:Q515).

Let's execute this updated query.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the filter to ensure the birth place is a city did not return any results. This might be because Buri Ram is not classified as a city (wd:Q515) in Wikidata. Instead, it might be classified as a different type of location, such as a district or a town.

Let's try a more flexible approach by checking if the birth place is a more specific location than a country. We can do this by ensuring that the birth place is not a country (wd:Q6256).

Here is the updated query:

```sparql
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q26707663 wdt:P19 ?birthPlace .
  FILTER NOT EXISTS { ?birthPlace wdt:P31 wd:Q6256 }  # Ensure the birth place is not a country
  OPTIONAL { ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = "en") }
}
```

This query will return the birth place only if it is not a country.

Let's execute this updated query.

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 267 for token EOF with content '' (the input most likely does not follow the grammar)

[Assistant]
It looks like there was a syntax error in the SPARQL query. The issue might be due to the comment inside the query. Let's remove the comment and re-execute the query.

Here is the corrected query:

```sparql
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q26707663 wdt:P19 ?birthPlace .
  FILTER NOT EXISTS { ?birthPlace wdt:P31 wd:Q6256 }
  OPTIONAL { ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = "en") }
}
```

Let's execute this corrected query.

[Tool]
Got 1 row and 2 columns:
| birthPlace            | birthPlaceLabel |
| --------------------- | --------------- |
| Buri Ram (wd:Q327510) | Buri Ram (en)   |

[Assistant]
The corrected query successfully returned Buri Ram as the birth place of Lisa Manoban, which is the more specific location.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q26707663 wdt:P19 ?birthPlace .
  FILTER NOT EXISTS { ?birthPlace wdt:P31 wd:Q6256 }
  OPTIONAL { ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = "en") }
}
```

Answer: Lisa Manoban was born in Buri Ram.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query successfully retrieves the birthplace of Lisa Manoban, which is Buri Ram, and provides the IRI for the location.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?character WHERE {
  ?character wdt:P451 wd:Q4205826 .
  ?character wdt:P451 wd:Q4463198 .
}

Geralt of Rivia (wd:Q2492923)

[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] among the characters in the witcher, who has two unmarried partners, Yennefer of Vengerberg and Triss Merigold?

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

[Tool]
Example 1:
Question:
Who is the tallest basketball player?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q3665646 ; wdt:P2048 ?height .
}
ORDER BY DESC ( ?height )
LIMIT 1

Using entities:
basketball player, also known as basketballer, basketeer, cager, hoopster, professional basketball player (wd:Q3665646): person who plays in basketball

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)
height, also known as heighth, size, depth over terrain (wd:P2048 as wdt): vertical length of an entity, length

Example 2:
Question:
How many companies were founded by the founder of Facebook?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) AS ?c ) WHERE {
  ?uri wdt:P112 wd:Q36215 .
  ?uri wdt:P31 / wdt:P279 * wd:Q783794 .
}

Using entities:
Mark Zuckerberg, also known as The Zuck, Zuck, Zuckerberg, Mark Elliott Zuckerberg, The Zucc (wd:Q36215): American Internet entrepreneur, chief executive officer, patron of the arts, computer scientist, philanthropist, entrepreneur, programmer
company, also known as co., firm (wd:Q783794): legal entity representing an association of people, whether natural, legal or a mixture of both, with a specific objective

Using properties:
founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt): founder or co-founder of this organization, religion, place or entity, creator
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
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

[Assistant] Based on the examples, we can see how to structure our SPARQL query. We need to identify the characters in The Witcher who have Yennefer of Vengerberg and Triss Merigold as their partners. Let's first find the entities for Yennefer of Vengerberg and Triss Merigold.

[Tool]
Top 10 entity alternatives:
1. Yennefer of Vengerberg, also known as Yenna, Yen (wd:Q4205826): fictional sorceress from the Witcher series, conspirator, magician, adviser
2. Vengerberg (wd:Q9368391)
3. Pseudotanais yenneferae (wd:Q107100133): species of crustacean

[Assistant] The correct entity for Yennefer of Vengerberg is `wd:Q4205826`. Now let's find the entity for Triss Merigold.

[Tool]
Top 10 entity alternatives:
1. Triss Merigold, also known as Fourteenth of the Hill, Merigold the Fearless (wd:Q4463198): fictional sorceress from the Witcher series, magician, adviser, healer
2. Merigold, also known as Merigold (Mississippi), Merigold, Mississippi, Merigold, MS (wd:Q867528): town in Bolivar County, Mississippi, United States
3. Triss (wd:Q3204428): 2002 novel by Brian Jacques
4. Triss (wd:Q15113667): character in the Shannara, military personnel
5. Merigold (wd:Q37520933): family name
6. Trissino (wd:Q47238): Italian comune
7. Trissolcus (wd:Q14495753): genus of insects
8. Trissernis (wd:Q7844073): genus of insects
9. Trissodoris (wd:Q5226655): genus of insects
10. Trisselwand (wd:Q2454152): mountain in the Totes Gebirge in Styria

[Assistant] The correct entity for Triss Merigold is `wd:Q4463198`. Next, we need to find the property that represents having a partner in the context of The Witcher. Let's search for a property related to "partner" or "relationship" for these characters.

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as wdt/p): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
2. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as wdt/p): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
3. 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)
4. 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
5. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt/p): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
6. student, also known as teacher to, teacher of, had student, students, pupils (wd:P802 as wdt/p): notable student(s) of the subject individual, significant person
7. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt/p): maker of this creative work or other object (where no more specific property exists)
8. 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)
9. enemy, also known as opponent, rival, archvillain, archrival, archnemesis (wd:P7047 as wdt/p): opponent character or group of this fictive character or group, significant person
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The property `unmarried partner` (wd:P451) seems to be the most appropriate for representing a romantic partner in the context of The Witcher. Now, let's construct a SPARQL query to find the character who has both Yennefer of Vengerberg and Triss Merigold as unmarried partners.

Here is the initial SPARQL query:

```sparql
SELECT DISTINCT ?character WHERE {
  ?character wdt:P451 wd:Q4205826 .
  ?character wdt:P451 wd:Q4463198 .
}
```

Let's execute this query to see if it returns the expected result.

[Tool]
Got 1 row and 1 column:
| character                     |
| ----------------------------- |
| Geralt of Rivia (wd:Q2492923) |

[Assistant]
The SPARQL query has returned the expected result: Geralt of Rivia (wd:Q2492923) is the character who has both Yennefer of Vengerberg and Triss Merigold as unmarried partners.

Here is the final SPARQL query and answer:

```sparql
SELECT DISTINCT ?character WHERE {
  ?character wdt:P451 wd:Q4205826 .
  ?character wdt:P451 wd:Q4463198 .
}
```

Answer: Geralt of Rivia (wd:Q2492923)

Now, let's provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected result. It identifies Geralt of Rivia as the character who has two unmarried partners, Yennefer of Vengerberg and Triss Merigold. The query follows the rules and does not include unnecessary computations or filters. Well done!


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?mayor ) AS ?count ) WHERE {
  ?mayor wdt:P39 wd:Q30185 .
  ?mayor wdt:P19 wd:Q1055 .
  ?mayor wdt:P21 wd:Q6581072 .
}

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

Hamburg has had 2 different female mayors.

[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 female mayors did Hamburg have?

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

[Tool]
Example 1:
Question:
How many children did Benjamin Franklin have?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) as ?c ) WHERE {
  wd:Q34969 wdt:P40 ?uri .
}

Using entities:
Benjamin Franklin, also known as The First American, Silence Dogood, Poor Richard, Ben Franklin, Franklin (wd:Q34969): American polymath and statesman (1706–1790), politician, polymath, diplomat, writer

Using properties:
child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

Example 2:
Question:
Which books were written by Danielle Steel?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P50 wd:Q72653 .
  ?uri wdt:P136 ?genre .
  ?genre wdt:P279 * wd:Q571 .
}

Using entities:
book, also known as books (wd:Q571): medium for recording information (words or images) typically on bound pages or more abstractly in electronic or audio form
Danielle Steel, also known as Danielle Fernandes Dominique Schülein-Steel, Danielle Fernandes Dominique Schuelein-Steel (wd:Q72653): children's writer, American writer, novelist, writer

Using properties:
genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
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
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

Example 3:
Question:
Which state of the United States of America has the highest density?

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

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

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

[Assistant] Based on the examples, we need to identify the relevant entities and properties for our question. We are looking for female mayors of Hamburg. Let's first search for the entity representing Hamburg.

[Tool]
Top 10 entity alternatives:
1. Hamburg, also known as Free and Hanseatic City of Hamburg, Hamburg, Germany, Hamburg, Freie und Hansestadt (wd:Q1055): city and state in the North of Germany
2. Hamburger SV, also known as Hamburg SV, HSV, H.S.V., Hamburg Sport Club, HamburgerSV (wd:Q51974): German sports club based in Hamburg, with its largest branch being its football department
3. Hamburg, also known as Hamburg, IA, Hamburg, Iowa (wd:Q998718): city in Fremont County, Iowa, United States
4. Hamburg, also known as Hamburg, AR, Hamburg, Arkansas (wd:Q79657): city in Ashley County, Arkansas, United States
5. Hamburg, also known as Hamburg, Minnesota, Hamburg, MN (wd:Q1005682): city in Carver County, Minnesota, United States
6. Hamburg, also known as Hamburg, New Jersey, Hamburg, NJ (wd:Q1082931): borough in Sussex County, New Jersey, United States
7. Hamburg, also known as Hamburg, New York, Hamburg, NY (wd:Q742785): town in Erie County, New York, United States
8. Hamburg, also known as Hamburg, IL (wd:Q2672139): village in Calhoun County, Illinois, United States
9. Hamburg, also known as Hamburg, PA, Hamburg, Pennsylvania (wd:Q1181264): borough in Berks County, Pennsylvania, United States
10. Hamburg, also known as Hamburgh (wd:Q939795): breed of chicken developed in Germany and Holland prior to 1700

[Assistant] The correct entity for Hamburg, the city and state in Germany, is `wd:Q1055`. Now, let's find the property that represents the mayor of a city.

[Tool]
Top 10 property alternatives:
1. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
2. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): official with the highest formal authority in a country/state, director / manager, chairperson
3. rector, also known as chancellor, university president, Rector (academia), president (wd:P1075 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): senior official in an educational institution., director / manager, chairperson
4. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): presiding member of an organization, group or body, director / manager, significant person
5. successful candidate, also known as election winner, winning candidate, winner of election, election won by, elected (wd:P991 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): person(s) or political organization(s) elected after the election, candidate, winner
6. position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): persons who hold and/or held the position
7. position held, also known as function, held position, holds position, job, office held (wd:P39 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): subject currently or formerly holds the object position or public office
8. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
9. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): the object is a country that recognizes the subject as its citizen, country
10. elected in, also known as re-elected in, election (wd:P2715 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): election in which a person gained a position (as qualifier), or a position or legislative term is/was elected (as main value)

[Assistant]
The property `wdt:P6` seems to be the most appropriate for representing the mayor of a city. However, it is important to note that this property might also represent other heads of government. To ensure we are specifically looking for mayors, we can use the property `wdt:P39` (position held) and filter for the specific position of mayor.

Next, we need to find the entity representing the position of mayor. Let's search for the entity "mayor" to get the correct identifier.

[Tool]
Top 10 entity alternatives:
1. mayor, also known as Mayor (wd:Q30185): head of municipal government such as a town or city
2. burgomaster, also known as mayor, burgmeister, burgermeister, burgemeester (wd:Q177529): archaic term for a mayor (to be used with P39)
3. Mayor of Castile, also known as Mayor, Munia Mayor Sanchez, Muniadona of Castile, Mayor o Munia (wd:Q260831): Queen of Navarre
4. Jesus María, also known as Mayor (wd:Q731893): Colombian municipality of the department of Santander
5. The Mayor, also known as Mayor, Special Citizen (wd:Q27952232): 2017 South Korean film by Park In-je
6. city head, also known as town head, mayor, head of city, head of town (wd:Q4145633): position
7. Mayor (wd:Q6797626): family name
8. Mayor (wd:Q93478533): 2020 documentary film by David Osit
9. mayor, also known as mayor (Germany), mayor of a place in Germany (wd:Q17175157): mayor of a German town
10. Mayordomo mayor of the King of Spain, also known as Mayordomo mayor, Mayordomo mayor del Rey de España (wd:Q6797876): High Steward of the King of Spain

[Assistant]
The correct entity for the position of mayor is `wd:Q30185`. Now, we can construct a SPARQL query to find the female mayors of Hamburg. We will use the property `wdt:P39` to find individuals who held the position of mayor and filter for those who are female.

Let's start by finding the individuals who held the position of mayor in Hamburg.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the query did not return any results. This might be because the property `wdt:P6` is not being used correctly in this context. Instead, let's try using only `wdt:P39` to find the individuals who held the position of mayor in Hamburg.

Let's refine the query to use only `wdt:P39` and filter for the position of mayor.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that the query is still not returning any results. This suggests that the way we are querying the data might not be correct. Let's try a different approach by directly linking the mayor position to the city of Hamburg.

We will use the property `wdt:P39` to find individuals who held the position of mayor and then filter for those who are associated with Hamburg. Additionally, we will check if the individuals are female using the property `wdt:P21` (sex or gender).

Let's construct the query again.

[Tool]
Got 2 rows and 1 column:
| mayor                       |
| --------------------------- |
| Lisa Albrecht (wd:Q1394531) |
| Maren Kruse (wd:Q1432484)   |

[Assistant]
The query returned two distinct female mayors of Hamburg: Lisa Albrecht and Maren Kruse. Therefore, the number of different female mayors Hamburg has had is 2.

Here is the final SPARQL query and the answer:

```sparql
SELECT (COUNT(DISTINCT ?mayor) AS ?count) WHERE {
  ?mayor wdt:P39 wd:Q30185 .
  ?mayor wdt:P19 wd:Q1055 .
  ?mayor wdt:P21 wd:Q6581072 .
}
```

Answer: Hamburg has had 2 different female mayors.

Now, let's provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the accurate count of distinct female mayors who have held the position in Hamburg. The query correctly uses the relevant entities and properties to filter the results. Well done!


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?dateOfBirth WHERE {
  wd:Q43347 wdt:P569 ?dateOfBirth
}

Rumi was born on September 30, 1207.

[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] When was Rumi born?

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

[Tool]
Example 1:
Question:
Who painted The Storm on the Sea of Galilee?

SPARQL:
SELECT ?uri WHERE {
  wd:Q2246489 wdt:P170 ?uri
}

Using entities:
The Storm on the Sea of Galilee, also known as Christ in the Storm on the Sea of Galilee, St. Pieters scheepje, Storm on the Sea of Galilee (wd:Q2246489): stolen painting by Rembrandt

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)

Example 2:
Question:
Give me the birthdays of all actors of the television show Charmed.

SPARQL:
SELECT DISTINCT ?date WHERE {
  wd:Q162371 wdt:P161 / wdt:P569 ?date .
}

Using entities:
Charmed (wd:Q162371): American supernatural drama / fantasy television series (1998–2006)

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
date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt): date on which the subject was born, inception

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

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

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

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

[Assistant] Based on the examples, we need to identify the entity for Rumi and the property for date of birth. Let's start by searching for the entity Rumi.

[Tool]
Top 10 entity alternatives:
1. Rumi, also known as Mawlana, Mawlana Rumi, Mawlawi, Jallal ed-Din Muhammad Balkhy, Jelaluddin Rumi (wd:Q43347): Sufi and Persian poet, philosopher, literary, writer, mystic, ʿālim, poet
2. Rum, also known as Arwām, Rūm, Rūmī (wd:Q3943294): autonym
3. Rūmī (wd:Q25908371): crater on planet Mercury
4. POGLUT1, also known as MDSRP, Rumi, protein O-glucosyltransferase 1, MDS010, LGMDR21 (wd:Q18042749): protein-coding gene in the species Homo sapiens
5. Lanmewko, also known as Rumi (wd:Q109342876): Taiwanese Virtual YouTuber, Twitch streamer, VTuber
6. Rumi Rumiyuq (wd:Q25104391): mountain in Bolivia
7. Rumi, also known as るみ (wd:Q97655647): Japanese female given name (るみ)
8. Rumi (wd:Q11241326): Japanese master of ceremonies, rapper
9. Rumi (wd:Q11578550): Japanese actress, actor
10. Rumi (wd:Q19949377)

[Assistant] The first result is the correct entity for Rumi. Now let's search for the property for date of birth.

[Tool]
Top 10 property alternatives:
1. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): date on which the subject was born, inception
2. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): most specific known birth location of a person, animal or fictional character, location
3. birthday, also known as b-day, bday, birth day (wd:P3150 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
4. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): the object is a country that recognizes the subject as its citizen, country
5. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): what the place, monument, memorial, or holiday, commemorates, main subject
6. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): full name of a person at birth, if different from their current, generally used name, name
7. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): dissolved, abolished or demolished date, date on which the subject died, end time
8. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): time when an entity begins to exist; for date of official opening use P1619, start time
9. website username or ID, also known as user name, website username, website ID, username in social media, username (wd:P554 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): username or identifier on a website that the person or movement ... account on, for use as qualifier of "website account on" (P553)
10. pseudonym, also known as nom de plume, nom-de-plume, nome de guerre, pen name, ring name (wd:P742 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): alias used by someone (for nickname use P1449), name

[Assistant] The first result is the correct property for date of birth. Now we can construct a simple SPARQL query to find out when Rumi was born.

[Tool]
Got 1 row and 1 column:
| dateOfBirth                         |
| ----------------------------------- |
| 1207-09-30T00:00:00Z (xsd:dateTime) |

[Assistant] The result shows that Rumi was born on September 30, 1207. We can now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected result. The date of birth for Rumi is accurately retrieved from Wikidata.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?deaths WHERE {
  wd:Q815436 wdt:P1120 ?deaths .
}

[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 casualties were a result of the Troubles?

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

[Tool]
Example 1:
Question:
How many programming languages are there?

SPARQL:
SELECT ( COUNT( DISTINCT ?sub ) AS ?count ) WHERE {
  ?sub wdt:P31 / wdt:P279 * wd:Q9143 .
}

Using entities:
programming language, also known as coding language, computer language, computer programming, computer programming language (wd:Q9143): language for communicating instructions to a machine

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:
Who is the author of WikiLeaks?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q359 wdt:P50 ?o1 .
}

Using entities:
WikiLeaks, also known as wikileaks.org (wd:Q359): NGO owned by Icelandic company Sunshine Press Productions ehf that has published news leaks provided by anonymous sources

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

Example 3:
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

[Assistant]
None of these examples directly relate to the Troubles or casualties, but we can use them as a reference for structuring our query.

To answer the question "How many casualties were a result of the Troubles?", we need to identify the entity representing "the Troubles" and the property that links it to the number of casualties. Let's start by searching for the entity "Troubles".

[Tool]
Top 10 entity alternatives:
1. The Troubles, also known as Troubles, Northern Irish Troubles, Northern Ireland Troubles, Northern Ireland conflict, Conflict in Northern Ireland (wd:Q815436): 1960s–1990s conflict in Northern Ireland
2. Troubles (wd:Q4000425): novel by James Gordon Farrell
3. Troubles (wd:Q7846501): album by Steve Lacy
4. Troubles (wd:Q7846503): UK musical group
5. Troubles (wd:Q109812273): Movie directed by Érik Papatie
6. Troubles (wd:Q129262318): 2022 track by Denzel Curry
7. Troubles (wd:Q131565207): hardback edition (en)
8. Troubles (wd:Q42196874)
9. Troubles (wd:Q7846502): album by Troubles
10. troubles (wd:L1330100-S1)

[Assistant]
The first result, "The Troubles" (wd:Q815436), is the entity we are looking for. Now, let's find out what properties are associated with this entity, particularly those that might indicate the number of casualties.

I will list the properties of "The Troubles" to see if there is a property that indicates the number of casualties.

[Tool]
Got 357 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                                       | object                                                              |
| ------------------------- | ---------------------------------------------- | ------------------------------------------------------------------- |
| The Troubles (wd:Q815436) | instance of (wdt:P31)                          | ethnic conflict (wd:Q766875)                                        |
| The Troubles (wd:Q815436) | country (wdt:P17)                              | United Kingdom (wd:Q145)                                            |
| The Troubles (wd:Q815436) | Commons category (wdt:P373)                    | Northern Ireland Troubles                                           |
| The Troubles (wd:Q815436) | image (wdt:P18)                                | <http://commons.wikimedia.org/wiki/Special:FilePath/Dsc1877ne2.jpg> |
| The Troubles (wd:Q815436) | location (wdt:P276)                            | Northern Ireland (wd:Q26)                                           |
| The Troubles (wd:Q815436) | on focus list of Wikimedia project (wdt:P5008) | WikiProject Human Rights (wd:Q13382529)                             |
| The Troubles (wd:Q815436) | point in time (wdt:P585)                       | 1998-01-01T00:00:00Z (xsd:dateTime)                                 |
| The Troubles (wd:Q815436) | start time (wdt:P580)                          | 1960-01-01T00:00:00Z (xsd:dateTime)                                 |
| The Troubles (wd:Q815436) | topic's main category (wdt:P910)               | wd:Q8850177                                                         |
| The Troubles (wd:Q815436) | end time (wdt:P582)                            | 1998-01-01T00:00:00Z (xsd:dateTime)                                 |
| ...                       | ...                                            | ...                                                                 |

[Assistant]
From the list of properties, there doesn't seem to be a direct property indicating the number of casualties. However, we can try searching for properties related to "casualties" or "deaths" to see if there is a relevant property that might link to the number of casualties.

Let's search for properties related to "casualties" or "deaths".

[Tool]
Top 10 property alternatives:
1. number of casualties, also known as casualities, number of deaths and injuries (wd:P1590 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of people dead or injured because of this event.  Used wh...e data on number of deaths and number of injured is unavailable.
2. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): total (cumulative) number of people who died since start as a direct result of an event or cause
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 pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): people killed by the subject, both legal and illegal
4. military casualty classification, also known as casualty classification, casualty type (wd:P1347 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): allowed values:  killed in action (Q210392), missing in action (...ent (Q16861407), others used in military casualty classification
5. number of injured, also known as injured, injuries, injury toll, non-fatal injuries, number injured (wd:P1339 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of people with non-fatal injuries in an event
6. number of losses, also known as defeats, games lost, L, losses, lost (wd:P1356 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of sporting matches, games or events lost
7. category for people who died here, also known as category for place of death, category of people who died here (wd:P1465 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): category item for people who died in this location, related category
8. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
9. case fatality rate, also known as fatality rate, CFR, case fatality ratio, case fatality, case fatality risk (wd:P3457 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): proportion of patients who die of a particular medical condition out of all who have this condition within a given time frame
10. victim(s), also known as sexual abuse victim, terrorist victim, shooting victim, torture victim, victims (wd:P8032 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): person(s) who were harmed from an act or event, object of occurrence, participant

[Assistant]
The property "number of casualties" (wd:P1590) seems to be the most relevant for our query. Let's check if this property is used with the entity "The Troubles" (wd:Q815436).

I will execute a SPARQL query to see if there is a value for the "number of casualties" property for "The Troubles".

```sparql
SELECT ?casualties WHERE {
  wd:Q815436 wdt:P1590 ?casualties .
}
```

Let's run this query.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that the property "number of casualties" (wd:P1590) is not directly linked to the entity "The Troubles" (wd:Q815436).

Next, let's try the property "number of deaths" (wd:P1120) to see if it provides the information we need.

I will execute a SPARQL query to check if there is a value for the "number of deaths" property for "The Troubles".

```sparql
SELECT ?deaths WHERE {
  wd:Q815436 wdt:P1120 ?deaths .
}
```

Let's run this query.

[Tool]
Got 1 row and 1 column:
| deaths             |
| ------------------ |
| 3532 (xsd:decimal) |

[Assistant]
The query returned a value for the "number of deaths" property (wd:P1120) for "The Troubles" (wd:Q815436). The number of deaths is 3,532.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?deaths WHERE {
  wd:Q815436 wdt:P1120 ?deaths .
}
```

The number of casualties resulting from the Troubles is 3,532.

Let's provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly retrieves the number of deaths resulting from the Troubles using the appropriate entity and property. The result matches the expected number of 3,532 casualties.


Failed to generate SPARQL query

[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 of Reinhold Messner's brothers still live?

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

[Tool]
Example 1:
Question:
How often did Jane Fonda marry?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) as ?c ) WHERE {
  wd:Q41142 wdt:P26 ?uri .
}

Using entities:
Jane Fonda, also known as Jane Seymour Fonda, Jayne Seymour Fonda, Hanoi Jane (wd:Q41142): American actress and activist, television actor, autobiographer, film producer, voice actor, stage actor, film actor, writer, model, actor

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

Example 2:
Question:
Give me all professional skateboarders from Sweden.

SPARQL:
SELECT ?s1 WHERE {
  ?s1 wdt:P641 wd:Q842284 .
  ?s1 wdt:P19 ?o1 .
  ?o1 wdt:P131 * wd:Q34 .
}

Using entities:
Sweden, also known as Swedish Kingdom, Konungariket Sverige, SWE, se, Kingdom of Sweden (wd:Q34): country in Northern Europe
skateboarding, also known as skateboard sport (wd:Q842284): action sport on skateboards

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
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location
sport, also known as play, plays, sport played, sports (wd:P641 as wdt): sport that the subject participates or participated in or is associated with

Example 3:
Question:
What is the last work of Dan Brown?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P50 wd:Q7345 ; wdt:P577 ?date .
}
ORDER BY DESC ( ?date )
LIMIT 1

Using entities:
Dan Brown, also known as Daniel Gerhard Brown, Dan Gerhard Brown (wd:Q7345): American novelist, prose writer, researcher, journalist, musician, novelist, teacher, writer

Using properties:
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

[Assistant] Based on the examples, we need to identify the entity for Reinhold Messner and the relevant properties to find his brothers and their current status. Let's start by searching for Reinhold Messner in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Reinhold Messner (wd:Q189307): Italian mountaineer, adventurer and explorer, film director, mountaineer, politician, explorer, writer
2. Reinhold Messner, also known as Reinhold Meßner, Reinhold Oswald Messner (wd:Q121337911): Austrian Franciscan priest and philosopher, regular priest, philosopher
3. Markus Lanz und Reinhold Messner (wd:Q55978741): episode of Reinhold Beckmann trifft … (S1 E2)
4. The Unauthorized Biography of Reinhold Messner (wd:Q3989773): album by Ben Folds Five
5. 18092 Reinhold, also known as Reinhold (wd:Q2618622): asteroid
6. Reinhold (wd:Q2141320): lunar impact crater
7. Messner (wd:Q28812178): family name
8. Reinhold, also known as Reinhold (first name), Reinhold (given name) (wd:Q18091397): male given name
9. Bernhard Reinhold, also known as B. Reinhold, Reinhold (wd:Q16761534): German painter, painter
10. Messner (wd:Q1777589): 2012 film directed by Andreas Nickel

[Assistant] The correct entity for Reinhold Messner is `wd:Q189307`. Now, let's find out the properties related to siblings and living status. We'll start by searching for properties related to siblings.

[Tool]
Top 10 property alternatives:
1. sibling, also known as is sister of, is the brother of, is the sibling of, is the sister of, sib (wd:P3373 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), relative
2. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
3. number of children, also known as children, children (number), how many children, issue, kids (wd:P1971 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of children of the person, animal, or character
4. child, also known as has son, kids, mother of, kid, issue (wd:P40 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
5. family, also known as royal house, noble family, member of family, house, dynasty (wd:P53 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): family, including dynasty and nobility houses. Not family name (use P734 for family name)., member of
6. family name identical to this given name, also known as surname identical to this given name, surname identical to this first name, related surname, related family name, last name identical to this first name (wd:P1533 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): last name that is the same as a given first name. Use on items for given names, different from
7. generational suffix, also known as age suffix, family suffix, Jr., Junior, Senior (wd:P8017 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): suffix used in name
8. twinning, also known as crystal twinning (wd:P537 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): type of twins a crystal forms
9. kinship to subject, also known as type of relationship, type of kinship, relation to, relationship (kinship), nature of kinship (wd:P1039 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): qualifier of "relative" (P1038) to indicate less usual family re...; indicate how the qualificator item is related to the main item, object of statement has role

[Assistant] The property for siblings is `wdt:P3373`. Next, we need to find the property for living status. Let's search for properties related to living status.

[Tool]
Top 10 property alternatives:
1. floruit, also known as work period, living, known alive in, flourished, fl. (wd:P1317 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): date when the person was known to be active or alive, when birth or death not documented
2. state of transmission, also known as state of preservation, survival status (wd:P12020 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): state in which a work is transmitted or its existence; for the state of its material witnesses, use P5816
3. life expectancy, also known as life span, lifespan (wd:P2250 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): average life expectancy for this group or species, duration
4. state of conservation, also known as conservation status, condition (wd:P5816 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): to indicate state of conservation of a building, monument, artif...t state of conservation. Ex.: ruinous, demolished, correct, etc.
5. nature of statement, also known as validity of statement, status of statement, refine statement, precisely, modality of statement (wd:P5102 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): (qualifier only) the underlying circumstances of this statement
6. medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): any state relevant to the health of an organism, including diseases and positive conditions
7. official residence, also known as resides at, lives in, palace, presidential mansion, presidential palace (wd:P263 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): the residence at which heads of government and other senior figures officially reside, residence
8. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): the place where the person is or has been, resident, location
9. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): person or organization occupying property, used by
10. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): language status identifier by Ethnologue.com using EGIDS scale

[Assistant]
The property for living status is `wdt:P1317` (floruit), which indicates when a person was known to be active or alive. However, it might not directly indicate the current living status. Another property that might be useful is `wdt:P570` (date of death), which can help us determine if someone is still alive.

Let's check if Reinhold Messner has any siblings and if we can find their living status using these properties.

First, let's find Reinhold Messner's siblings.