PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?coaster ?coasterLabel ?country ?countryLabel WHERE {
  ?coaster wdt:P31 wd:Q204832 .
  OPTIONAL {
    ?coaster wdt:P17 ?country .
    OPTIONAL {
      ?country rdfs:label ?countryLabel FILTER ( lang( ?countryLabel ) = "en" )
    }
  }
  ?coaster rdfs:label ?coasterLabel FILTER ( lang( ?coasterLabel ) = "en" )
}
LIMIT 50

Got 50 rows and 4 columns, showing the first 5 and last 5 rows below:
| coaster                         | coasterLabel           | country                              | countryLabel                    |
| ------------------------------- | ---------------------- | ------------------------------------ | ------------------------------- |
| Bullet (wd:Q1004335)            | Bullet (en)            | United Kingdom (wd:Q145)             | United Kingdom (en)             |
| Windstorm (wd:Q10393876)        | Windstorm (en)         | Brazil (wd:Q155)                     | Brazil (en)                     |
| Circus Express (wd:Q10453412)   | Circus Express (en)    | Sweden (wd:Q34)                      | Sweden (en)                     |
| Gamla bergbanan (wd:Q10502454)  | Gamla bergbanan (en)   | Sweden (wd:Q34)                      | Sweden (en)                     |
| Lisebergsloopen (wd:Q10563200)  | Lisebergsloopen (en)   | Sweden (wd:Q34)                      | Sweden (en)                     |
| ...                             | ...                    | ...                                  | ...                             |
| Extreme Rusher (wd:Q1385492)    | Extreme Rusher (en)    | People's Republic of China (wd:Q148) | People's Republic of China (en) |
| The Dragon (wd:Q1409526)        | The Dragon (en)        | United Kingdom (wd:Q145)             | United Kingdom (en)             |
| The Dragon (wd:Q1409526)        | The Dragon (en)        | Germany (wd:Q183)                    | Germany (en)                    |
| French Revolution (wd:Q1455457) | French Revolution (en) | South Korea (wd:Q884)                | South Korea (en)                |
| Lisebergbanan (wd:Q1502537)     | Lisebergbanan (en)     | Sweden (wd:Q34)                      | Sweden (en)                     |

This query returns a list of roller coasters (with their IRIs and English labels) and their respective countries (with IRIs and English labels, if available).

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

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

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

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

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

[User] Get a list of roller coasters and their respective countries, if available.

[Assistant]
Let's break down the question:

1. We need to find entities that are roller coasters.
2. For each roller coaster, we want to find its country, if available.

Step 1: Find the entity for "roller coaster" in Wikidata.
Step 2: Identify the property that links an instance to its country.
Step 3: Build a query to get all roller coasters and their countries.

Let's start by searching for the entity "roller coaster".

[Tool]
Top 10 entity alternatives:
1. roller coaster, also known as coaster, rollercoaster (wd:Q204832): type of amusement ride found at amusement parks and carnivals
2. steel roller coaster, also known as steel roller coasters, roller coaster (steel), roller coasters (steel), roller coasters made of steel, roller coaster made of steel (wd:Q2389789): type of roller coaster that is defined by having a track made of steel
3. Roller Coaster (wd:Q15630210): single by Justin Bieber
4. Roller Coaster, also known as White Roller Coaster (wd:Q7361012): roller coaster at Lagoon Amusement Park
5. Roller Coaster (wd:Q25394129): single by Toni Braxton and Babyface
6. Roller Coaster (wd:Q120648054): 2023 single by Nmixx
7. 🎢, also known as U+1F3A2, roller coaster ride emoji, ROLLER COASTER, roller coaster emoji (wd:Q87577117): Unicode character
8. Roller Coaster (wd:Q7361018): steel roller coaster at Suối Tiên Amusement Park
9. Roller Coaster (wd:Q7361016): album by Scott Cain
10. Roller Coaster (wd:Q7361015): album by Red Bacteria Vacuum

[Assistant]
The main entity for "roller coaster" as an amusement ride is wd:Q204832.

Next, we need to find the property that links a roller coaster to its country. Typically, this is "country" or "located in the country". Let's search for the relevant property.

[Tool]
Top 10 property alternatives:
1. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): place where a statement is valid, applies to part
2. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): the object is a country that recognizes the subject as its citizen, country
4. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
6. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): most specific known birth location of a person, animal or fictional character, location
7. continent (wd:P30 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): continent of which the subject is a part, located in/on physical feature
8. 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/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
9. place of publication, also known as published in (place), where published, release region, released in, published from (wd:P291 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): geographical place of publication of the edition (use 1st edition when referring to works), significant place
10. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

[Assistant]
The property "country" (wd:P17) is the most appropriate for linking a roller coaster to its country.

Now, let's construct a query to get all entities that are instances of "roller coaster" (wd:Q204832) and, if available, their country (wd:P17). We will also try to get the labels for both the roller coaster and the country, but make them optional.

Let's proceed to build and execute this query.

[Tool]
SPARQL execution failed:
Tried to allocate 6.6 GB, but only 5.2 GB were available. Clear the cache or allow more memory for QLever during startup

[Assistant]
The query failed due to memory constraints, likely because there are a large number of roller coaster entities in Wikidata. To address this, I will refine the query to reduce memory usage:

- I will limit the number of results further (e.g., LIMIT 50).
- I will avoid using OPTIONAL for labels unless necessary, as label retrieval can be expensive.
- I will focus on retrieving just the IRIs for roller coasters and their countries, and only add labels if the query succeeds.

Let's try a simpler version first.

[Tool]
Got 50 rows and 2 columns, showing the first 5 and last 5 rows below:
| coaster                                               | country                  |
| ----------------------------------------------------- | ------------------------ |
| Bullet (wd:Q1004335)                                  | United Kingdom (wd:Q145) |
| wd:Q1028778                                           | Germany (wd:Q183)        |
| Windstorm (wd:Q10393876)                              | Brazil (wd:Q155)         |
| Circus Express (wd:Q10453412)                         | Sweden (wd:Q34)          |
| Gamla bergbanan (wd:Q10502454)                        | Sweden (wd:Q34)          |
| ...                                                   | ...                      |
| Doraemon XR Ride: Nobita's Sky Utopia (wd:Q130297383) |                          |
| Chura Racer (wd:Q130349483)                           | Germany (wd:Q183)        |
| wd:Q130356594                                         | Germany (wd:Q183)        |
| Minifigure Speedway (wd:Q130735411)                   | United Kingdom (wd:Q145) |
| Bowls of Joy (wd:Q131036652)                          |                          |

[Tool]
SPARQL execution failed:
Tried to allocate 6.6 GB, but only 4.7 GB were available. Clear the cache or allow more memory for QLever during startup

[Tool]
Got 50 rows and 3 columns, showing the first 5 and last 5 rows below:
| coaster                         | coasterLabel           | country                              |
| ------------------------------- | ---------------------- | ------------------------------------ |
| Bullet (wd:Q1004335)            | Bullet (en)            | United Kingdom (wd:Q145)             |
| Windstorm (wd:Q10393876)        | Windstorm (en)         | Brazil (wd:Q155)                     |
| Circus Express (wd:Q10453412)   | Circus Express (en)    | Sweden (wd:Q34)                      |
| Gamla bergbanan (wd:Q10502454)  | Gamla bergbanan (en)   | Sweden (wd:Q34)                      |
| Lisebergsloopen (wd:Q10563200)  | Lisebergsloopen (en)   | Sweden (wd:Q34)                      |
| ...                             | ...                    | ...                                  |
| Extreme Rusher (wd:Q1385492)    | Extreme Rusher (en)    | People's Republic of China (wd:Q148) |
| The Dragon (wd:Q1409526)        | The Dragon (en)        | United Kingdom (wd:Q145)             |
| The Dragon (wd:Q1409526)        | The Dragon (en)        | Germany (wd:Q183)                    |
| French Revolution (wd:Q1455457) | French Revolution (en) | South Korea (wd:Q884)                |
| Lisebergbanan (wd:Q1502537)     | Lisebergbanan (en)     | Sweden (wd:Q34)                      |

[Tool]
Got 50 rows and 4 columns, showing the first 5 and last 5 rows below:
| coaster                         | coasterLabel           | country                              | countryLabel                    |
| ------------------------------- | ---------------------- | ------------------------------------ | ------------------------------- |
| Bullet (wd:Q1004335)            | Bullet (en)            | United Kingdom (wd:Q145)             | United Kingdom (en)             |
| Windstorm (wd:Q10393876)        | Windstorm (en)         | Brazil (wd:Q155)                     | Brazil (en)                     |
| Circus Express (wd:Q10453412)   | Circus Express (en)    | Sweden (wd:Q34)                      | Sweden (en)                     |
| Gamla bergbanan (wd:Q10502454)  | Gamla bergbanan (en)   | Sweden (wd:Q34)                      | Sweden (en)                     |
| Lisebergsloopen (wd:Q10563200)  | Lisebergsloopen (en)   | Sweden (wd:Q34)                      | Sweden (en)                     |
| ...                             | ...                    | ...                                  | ...                             |
| Extreme Rusher (wd:Q1385492)    | Extreme Rusher (en)    | People's Republic of China (wd:Q148) | People's Republic of China (en) |
| The Dragon (wd:Q1409526)        | The Dragon (en)        | United Kingdom (wd:Q145)             | United Kingdom (en)             |
| The Dragon (wd:Q1409526)        | The Dragon (en)        | Germany (wd:Q183)                    | Germany (en)                    |
| French Revolution (wd:Q1455457) | French Revolution (en) | South Korea (wd:Q884)                | South Korea (en)                |
| Lisebergbanan (wd:Q1502537)     | Lisebergbanan (en)     | Sweden (wd:Q34)                      | Sweden (en)                     |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?item ?title WHERE {
  ?item wdt:P356 ?doi .
  FILTER ( ?doi IN ( "10.1126/SCIENCE.156.3775.636" , "10.1145/358027.358042" ) ) OPTIONAL {
    ?item wdt:P1476 ?title
  }
}

The items associated with the DOIs are:
- DOI '10.1126/SCIENCE.156.3775.636': How Long Is the Coast of Britain...ilarity and Fractional Dimension (https://www.wikidata.org/wiki/Q3554851)
- DOI '10.1145/358027.358042': The Complexity of Songs (https://www.wikidata.org/wiki/Q2410432)
Both items have their titles available in Wikidata.

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

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

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

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

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

[User] What are the items associated with the DOIs '10.1126/SCIENCE.156.3775.636' and '10.1145/358027.358042', along with their titles if available?

[Assistant]
Let's break down the question:

1. The user wants to find items (entities) in Wikidata that are associated with two specific DOIs: '10.1126/SCIENCE.156.3775.636' and '10.1145/358027.358042'.
2. For each item, if available, the user wants the title.

Step 1: Find the property for DOI in Wikidata.
Step 2: Find the property for title in Wikidata.
Step 3: Construct a query that finds items with either of the two DOIs and optionally retrieves their titles.

First, let's search for the property "DOI" in Wikidata.

[Tool]
Top 10 property alternatives:
1. DOI, also known as Digital Object Identifier, doi (wd:P356 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): serial code used to uniquely identify digital objects like academic papers (use upper case letters only)
2. DOI prefix, also known as doip, DOIP (wd:P1662 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier specific to a DOI registrant
3. DOI formatter (wd:P8404 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): formatter string where '$1' can be automatically replaced to create a DOI
4. Disease Ontology ID, also known as DOID (wd:P699 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier in the Disease Ontology database
5. Altmetric DOI (wd:P5530 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): DOI of a scientific or academic article at altmetric.com, to track citation metrics
6. Director Identification Number, also known as DIN, DIN number India, India DIN, Indian Director Number (wd:P9706 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier for a person intending to be a director or an existing director of a company, assigned by the Indian central government
7. DIA ID, also known as Detroit Institute of Arts ID (wd:P8916 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier for an artwork on the Detroit Institute of Arts website
8. Playboy Plus ID, also known as PlayboyPlus.com ID, Playmates Playmate ID, PMID (wd:P5346 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier of a profile on the Playboy Plus website
9. PubMed publication ID, also known as PMID, PubMed reference number, PubMed ID (wd:P698 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier for journal articles/abstracts in PubMed
10. Relations Ontology ID, also known as RO ID, Relation Ontology ID (wd:P3590 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): ID in the Relations Ontology

[Assistant]
The property for DOI in Wikidata is wdt:P356.

Next, let's search for the property for "title" in Wikidata, as the user wants the title if available.

[Tool]
Top 10 property alternatives:
1. title, also known as name, titled, page name, original title, known as (wd:P1476 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
2. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): official name of the subject in its official language(s), name
3. title of broader work, also known as container title, website title (wd:P6333 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): title of website, journal or other work in which an article (or ...is published in. Use "published in" (P1433) instead if possible.
4. front and back matter, also known as glossary of this book, postface, introduction in this book, index of this book, preface (wd:P8570 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): front and back matter of a book, has part(s) of the class
5. title page number, also known as cover page number, title djvu page, title file page, title file page number, title page (wd:P4714 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): qualifier to indicate the number of the page of a document in which the title page is located. Don't use for the actual cover page.
6. short name, also known as short title, shortname, abbreviation, shortened name, initialism (wd:P1813 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): short name of a place, organisation, person, journal, wikidata property, etc. Used by some Wikipedia templates., name
7. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): label for the items in their official language  or their original language, name
8. title in LaTeX, also known as LaTeX title, Tex title, title in TeX (wd:P6835 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): (qualifier) for title property (P1476), to write title in LaTeX/...n't render it normally. Enclose normal text with " ext{" and "}"
9. publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): date or point in time when a work was first published or released, point in time
10. review score by, also known as publication, reviewer, score issuer, scorer (wd:P447 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): issuer of a review score

[Assistant]
The property for "title" in Wikidata is wdt:P1476.

Now, let's construct a SPARQL query to find items with either of the two DOIs ('10.1126/SCIENCE.156.3775.636' or '10.1145/358027.358042') and optionally retrieve their titles using wdt:P1476.

I'll write the query so that it returns the item IRIs and, if available, their titles.

[Tool]
Got 2 rows and 2 columns:
| item                                                                              | title                                                                    |
| --------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| The Complexity of Songs (wd:Q2410432)                                             | The Complexity of Songs (en)                                             |
| How Long Is the Coast of Britain...ilarity and Fractional Dimension (wd:Q3554851) | How Long Is the Coast of Britain...ilarity and Fractional Dimension (en) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?player ?dob ?gender ?age WHERE {
  ?player wdt:P31 wd:Q5 ; wdt:P106 wd:Q10833314 ; wdt:P569 ?dob ; wdt:P21 ?gender .
  FILTER NOT EXISTS {
    ?player wdt:P570 ?dod
  }
  BIND( ( YEAR( NOW () ) - YEAR( ?dob ) ) AS ?age ) FILTER ( ?age < 110 )
}
ORDER BY DESC ( ?age )
LIMIT 100

The 100 oldest living tennis players (excluding those 110 or older) are listed by age in descending order, with their Wikidata identifiers, dates of birth, genders, and calculated ages. The list starts with those born in 1916 (age 109) and goes down to those born in 1934 (age 91).

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

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

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

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

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

[User] Who are the 100 oldest living tennis players? Include their dates of birth, genders, and ages, and order by age in descending order. Exclude those who are 110 years old or older.

[Assistant]
Let's break down the question:

1. We need to find tennis players who are still alive.
2. We need their dates of birth, genders, and ages.
3. We need to order them by age (descending) and limit to the top 100.
4. Exclude those who are 110 years old or older.

Step 1: Identify the entity for "tennis player" and properties for "date of birth", "gender", and "date of death" (to check if alive).

I'll start by searching for the entity "tennis player".

[Tool]
Top 10 entity alternatives:
1. tennis player (wd:Q10833314): sportsperson who plays tennis
2. Chee-Meng Jimmy Liew, also known as Tennis player (wd:Q27579542): chess player
3. Tennis player (wd:Q50648121): painting by Roy De maistre
4. Tennis Player (wd:Q106776651): painting by James Edward Davis (Princeton y1968-145)
5. Tennis Player (wd:Q106776580): painting by James Edward Davis (Princeton y1968-146)
6. Tennis Player (wd:Q106774483): painting by James Edward Davis (Princeton y1968-147)
7. Tennis Player (wd:Q106767186): painting by James Edward Davis
8. table tennis player, also known as ping-pong player, table tennis athlete (wd:Q13382519): sportsperson taking part in table tennis competitions
9. amateur tennis player, also known as amateur tennis players (wd:Q48995125)
10. beach tennis player (wd:Q30525637)

[Assistant]
The correct entity for "tennis player" is wd:Q10833314.

Next, I need to identify the properties for:
- "date of birth"
- "gender"
- "date of death" (to check if alive)

I'll search for these properties.

[Tool]
Top 10 property alternatives:
1. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): 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 wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): 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 wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): 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 wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): 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 wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): 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 wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): 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 wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): 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 wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): 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 wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): 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 wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): alias used by someone (for nickname use P1449), name

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
3. requires grammatical feature, also known as grammatical feature required, required grammatical feature, requires case, requires mood, uses case (wd:P5713 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): grammatical features required or generally used with lexeme or form of lexeme
4. has grammatical gender, also known as grammatical genders, has genders (wd:P5109 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): specific form of noun class system of a language. Use qualifier ... subject of" (P805) to link to language specific item if present
5. personal pronoun, also known as gender pronoun, personal gender pronoun, personal pronouns, PGP, PGPs (wd:P6553 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): used when a word is only used to refer to people of this gender or to animals of this sex, independent of the grammatical gender
7. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): genders educated at this educational institution
9. male form of label, also known as male form of label (string), male gender sense, masculine form of label (wd:P3321 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): male form of name or title (for female use P2521)
10. given name version for other gender, also known as personal name version for other gender, other genders given name, male version of this female given name, gender inflection of given name, female version of this male given name (wd:P1560 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): equivalent name (with respect to the meaning of the name) in the...n of a female first name. Add primarily the closest matching one

[Tool]
Top 10 property alternatives:
1. mean age, also known as average age (wd:P4442 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): mean age in a given place
2. type of age limit, also known as age limit (wd:P8241 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): qualifier on minimum age (P2899) to describe the type of age limit (Qualifier field only)
3. maximum age, also known as max age (wd:P4135 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): highest age a person is eligible to do something, for example be...or sport teams, some positions like judges, clinical trials, etc
4. longest observed lifespan, also known as maximum age, oldest recorded individual, oldest observed, maximum life span, highest observed lifespan (wd:P4214 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): age of the oldest specimen of a taxon for which the age can be verified
5. generational suffix, also known as age suffix, family suffix, Jr., Junior, Senior (wd:P8017 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): suffix used in name
6. age of subject at event, also known as Aetatis, age at event (wd:P3629 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): the age of the subject according to the cited source at the time of an event. Used as a qualifier of significant event property
7. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): date on which the subject was born, inception
8. App Store age rating, also known as app store age, app rating, age rating (wd:P9897 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): content rating category by Apple for software published at the App Store
9. narrative age, also known as specific age inside fictional universe, years old in-universe, narrative age, age in story, age in fiction (wd:P6249 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): age of a fictional character (use qualifiers like P10663 (applies to work) to restrict the age to a certain work)
10. age of onset (wd:P2841 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): age group in which disease manifestations appear

[Tool]
Top 10 property alternatives:
1. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): dissolved, abolished or demolished date, date on which the subject died, end time
2. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
3. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): date on which the subject was born, inception
4. date of burial or cremation, also known as burial date, cremation date, date of cremation, funeral date (wd:P4602 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): date on which the person was buried or cremated soon after death, point in time
5. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): total (cumulative) number of people who died since start as a direct result of an event or cause
6. birthday, also known as b-day, bday, birth day (wd:P3150 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
7. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): what the place, monument, memorial, or holiday, commemorates, main subject
8. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
9. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): time when an entity begins to exist; for date of official opening use P1619, start time
10. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time

[Assistant]
We have identified the following:
- "tennis player": wd:Q10833314
- "date of birth": wdt:P569
- "sex or gender": wdt:P21
- "date of death": wdt:P570

There is no direct "age" property for people, but we can calculate age in SPARQL using the date of birth and the current date, and filter out those who are 110 or older.

Next, I'll draft a SPARQL query to:
- Select humans (wd:Q5) who are tennis players (wd:Q10833314) and have no date of death (i.e., still living).
- Retrieve their date of birth, gender, and calculate their age.
- Exclude those who are 110 or older.
- Order by age descending and limit to 100.

I'll write and execute a draft query to check if this approach works.

[Tool]
Got 10 rows and 4 columns:
| player                                | dob                                 | gender               | age           |
| ------------------------------------- | ----------------------------------- | -------------------- | ------------- |
| Rolf Göpfert (wd:Q116256918)          | 1916-02-16T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 109 (xsd:int) |
| Vera Mattar (wd:Q29473999)            | 1916-01-01T00:00:00Z (xsd:dateTime) | female (wd:Q6581072) | 109 (xsd:int) |
| wd:Q27989956                          | 1916-01-01T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 109 (xsd:int) |
| Ronald Sturdy (wd:Q125387626)         | 1917-01-03T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 108 (xsd:int) |
| wd:Q12875993                          | 1917-01-01T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 108 (xsd:int) |
| Blen Franklin (wd:Q125468755)         | 1917-10-01T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 108 (xsd:int) |
| Patricia Henry Yeomans (wd:Q63762498) | 1917-01-01T00:00:00Z (xsd:dateTime) | female (wd:Q6581072) | 108 (xsd:int) |
| Pedro Masip (wd:Q126598001)           | 1918-10-08T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 107 (xsd:int) |
| wd:Q25424566                          | 1918-01-01T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 107 (xsd:int) |
| Edith Niemeyer (wd:Q3052379)          | 1918-01-01T00:00:00Z (xsd:dateTime) | female (wd:Q6581072) | 107 (xsd:int) |

[Tool]
Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| player                             | dob                                 | gender               | age           |
| ---------------------------------- | ----------------------------------- | -------------------- | ------------- |
| Rolf Göpfert (wd:Q116256918)       | 1916-02-16T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 109 (xsd:int) |
| Vera Mattar (wd:Q29473999)         | 1916-01-01T00:00:00Z (xsd:dateTime) | female (wd:Q6581072) | 109 (xsd:int) |
| wd:Q27989956                       | 1916-01-01T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 109 (xsd:int) |
| Ronald Sturdy (wd:Q125387626)      | 1917-01-03T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 108 (xsd:int) |
| wd:Q12875993                       | 1917-01-01T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 108 (xsd:int) |
| ...                                | ...                                 | ...                  | ...           |
| Chuck Swindoll (wd:Q5115734)       | 1934-10-18T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 91 (xsd:int)  |
| Tony Pickard (wd:Q3531860)         | 1934-09-13T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 91 (xsd:int)  |
| Janet Hopps Adkisson (wd:Q3161921) | 1934-08-04T00:00:00Z (xsd:dateTime) | female (wd:Q6581072) | 91 (xsd:int)  |
| Shirley Brasher (wd:Q435255)       | 1934-06-13T00:00:00Z (xsd:dateTime) | female (wd:Q6581072) | 91 (xsd:int)  |
| Mary Carter Reitano (wd:Q434596)   | 1934-11-29T00:00:00Z (xsd:dateTime) | female (wd:Q6581072) | 91 (xsd:int)  |

[Tool] Stopped generation process


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
SELECT DISTINCT ?person ?position ?personLabel ?positionLabel WHERE {
  ?person p:P39 ?statement .
  ?statement ps:P39 ?position ; pq:P748 wd:Q22686 .
  OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( lang( ?personLabel ) = "en" )
  }
  OPTIONAL {
    ?position rdfs:label ?positionLabel FILTER ( lang( ?positionLabel ) = "en" )
  }
}

Got 90 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                                | position                                                           | personLabel                | positionLabel                                           |
| ------------------------------------- | ------------------------------------------------------------------ | -------------------------- | ------------------------------------------------------- |
| Karoline Leavitt (wd:Q100146113)      | White House Press Secretary (wd:Q2306431)                          | Karoline Leavitt (en)      | White House Press Secretary (en)                        |
| Christopher C. Miller (wd:Q101423348) | Director of the National Counterterrorism Center (wd:Q104720749)   | Christopher C. Miller (en) | Director of the National Counterterrorism Center (en)   |
| Christopher C. Miller (wd:Q101423348) | United States Secretary of Defense (wd:Q735015)                    | Christopher C. Miller (en) | United States Secretary of Defense (en)                 |
| Jennifer Homendy (wd:Q106916479)      | Member of the National Transportation Safety Board (wd:Q125195889) | Jennifer Homendy (en)      | Member of the National Transportation Safety Board (en) |
| Anthony M. Ornato (wd:Q112867791)     | White House Deputy Chief of Staff (wd:Q7994871)                    | Anthony M. Ornato (en)     | White House Deputy Chief of Staff (en)                  |
| ...                                   | ...                                                                | ...                        | ...                                                     |
| Alyssa Farah Griffin (wd:Q86419354)   | White House Director of Strategic Communications (wd:Q28450497)    | Alyssa Farah Griffin (en)  | White House Director of Strategic Communications (en)   |
| Brian Jack (wd:Q86493775)             | White House Political Director (wd:Q108485661)                     | Brian Jack (en)            | White House Political Director (en)                     |
| Jeffrey Ross Gunter (wd:Q91601834)    | United States Ambassador to Iceland (wd:Q7889312)                  | Jeffrey Ross Gunter (en)   | United States Ambassador to Iceland (en)                |
| Lydia Tederick (wd:Q96475700)         | White House Office of the Curator (wd:Q2928404)                    | Lydia Tederick (en)        | White House Office of the Curator (en)                  |
| Roger D. Carstens (wd:Q97727835)      | Special Envoy for Hostage Affairs (wd:Q85802513)                   | Roger D. Carstens (en)     | Special Envoy for Hostage Affairs (en)                  |

The people appointed by Donald Trump and the positions they were appointed to can be found in the query result. For example: Karoline Leavitt (White House Press Secretary), Christopher C. Miller (Director of the National Counterterrorism Center and United States Secretary of Defense), Jennifer Homendy (Member of the National Transportation Safety Board), Anthony M. Ornato (White House Deputy Chief of Staff), Alyssa Farah Griffin (White House Director of Strategic Communications), Brian Jack (White House Political Director), Jeffrey Ross Gunter (United States Ambassador to Iceland), Lydia Tederick (White House Office of the Curator), Roger D. Carstens (Special Envoy for Hostage Affairs), and more. The full list is available in the query result.

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

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

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

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

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

[User] Who were the people appointed by Donald Trump, and which position was this for each person?

[Assistant]
Let's break down the question:

1. We need to identify "Donald Trump" as an entity.
2. We need to find people who were "appointed by" Donald Trump.
3. For each person, we need to find the "position" they were appointed to.

First, let's search for the entity "Donald Trump" in Wikidata to get his identifier.

[Tool]
Top 10 entity alternatives:
1. Donald Trump, also known as President Donald Trump, President Donald J. Trump, President Trump, President Donald J Trump, Trump (wd:Q22686): president of the United States (2017–2021, 2025–present), real estate entrepreneur, chief executive officer, television producer, business magnate, businessperson, game show host, film producer, entrepreneur, politician, merchant, investor, writer, actor
2. Donald Trump, also known as Donald L. Trump, the other Donald Trump, Skip Trump, Dr. Donald L. Trump, Donald Lynn "Skip" Trump (wd:Q27947481): American physician, oncologist, physician, executive
3. Donald Trump (wd:Q5295230): 2011 song by Mac Miller
4. Donald Trump (wd:Q23001025): segment of an episode of Last Week Tonight
5. Donald Trump III, also known as Donald J. Trump III, Donald Trump, Donald J. Trump, Donald John Trump, Donald John Trump III (wd:Q23000825): son of Donald Trump Jr. (born 2009)
6. Donald Trump (wd:Q104421475): character Donald Trump in Anthony Davis's opera The Central Park Five
7. Donald Trump Jr., also known as Donald Trump, Jr., Donald Trump Junior, Don Jr, Don Jr., Don Trump Jr (wd:Q3713655): American businessman and reality television personality (born 1977), television presenter, businessperson, entrepreneur
8. second impeachment of Donald Trump, also known as 2021 efforts to remove Donald Trump from office, 2021 impeachment of Donald Trump, 2nd impeachment of Donald Trump, Donald J. Trump Impeachment, Donald Trump Impeachment (wd:Q104713215): 2021 United States presidential impeachment
9. second inauguration of Donald Trump, also known as Trump inauguration 2025, the 60th Presidential Inauguration, second Trump inauguration, second inauguration of Trump, inauguration of Donald Trump (wd:Q126616223): 2025 United States presidential inauguration
10. first presidency of Donald Trump, also known as Donald Trump I, First Donald Trump Administration, First Donald Trump presidency, First presidency of Donald Trump, First Trump presidency (wd:Q27809653): U.S. presidential administration from 2017 to 2021

[Assistant]
The correct entity for Donald Trump (the U.S. president) is wd:Q22686.

Next, we need to find people who were "appointed by" Donald Trump and the positions they were appointed to. This likely involves a property related to "appointed by" or "position held" with a qualifier indicating the appointer.

Let's search for properties related to "appointed by" in Wikidata.

[Tool]
Top 10 property alternatives:
1. appointed by, also known as named by (wd:P748 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): who appointed the person to the office, can be used as a qualifier
2. consecrator, also known as has consecrator, ordainer, ordained by, has ordainer, consecrated by (wd:P1598 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): bishop who presided as consecrator or co-consecrator of this bishop, significant person
3. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
4. issued by, also known as issuing body, issuing agent, issuer, identifier issuing body, identifier issued by (wd:P2378 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): organisation or other agent that issues or allocates an identifier, code, classification number, etc.
5. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): founder or co-founder of this organization, religion, place or entity, creator
6. maintained by, also known as custodian, maintenance, maintainer, held by, administrator (wd:P126 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): person or organization in charge of keeping the subject (for instance an infrastructure) in functioning order
7. academic appointment (wd:P8413 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): this person has been appointed to a role within the given higher...stitution or department; distinct from employment or affiliation
8. authority, also known as executive authority, governed by, governing authority, governing body, has authority (wd:P797 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): entity having executive power on given entity
9. position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): subject currently or formerly holds the object position or public office
10. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant

[Assistant]
The property "appointed by" (wd:P748) is exactly what we need. It is typically used as a qualifier on "position held" (wd:P39), indicating who appointed the person to the office.

So, the structure is:
- ?person wdt:P39 ?position .
- The statement has a qualifier: pq:P748 wd:Q22686 (Donald Trump).

Let's list some example triples using "appointed by" (wd:P748) as a qualifier to confirm this structure.

[Tool]
Got 5,433 rows and 3 columns, showing the first 10 rows below:
| subject                                           | property               | object                    |
| ------------------------------------------------- | ---------------------- | ------------------------- |
| s:Q3431395-4c83ea20-b27b-496f-aa6a-81ce519697cd   | appointed by (pq:P748) | United Kingdom (wd:Q145)  |
| s:Q114322-a000a496-465f-bf1c-3a03-6933bcb50e17    | appointed by (pq:P748) | Barack Obama (wd:Q76)     |
| s:Q100146113-d0b07846-46cd-6d79-6c88-1dc3e8df9079 | appointed by (pq:P748) | Donald Trump (wd:Q22686)  |
| s:Q18620776-779e44a6-4c39-56ba-51f0-9e1aa82304f0  | appointed by (pq:P748) | Adolf Hitler (wd:Q352)    |
| s:Q60090110-14D37617-1F07-4346-ABC6-2FAE76C9F999  | appointed by (pq:P748) | Somalia (wd:Q1045)        |
| s:Q11147-E4DB3B65-0D49-4009-A7DE-A970B556FC4E     | appointed by (pq:P748) | Ronald Reagan (wd:Q9960)  |
| s:Q32024-7e2f0499-4502-7870-c8c9-f4bd5e9843d5     | appointed by (pq:P748) | Vladimir Putin (wd:Q7747) |
| s:Q16069838-79701039-40d6-14fb-a06b-f8f29487f190  | appointed by (pq:P748) | Helsinki (wd:Q1757)       |
| s:Q1234235-417ADF8B-FED5-4B81-AF91-9E7437D8D1D1   | appointed by (pq:P748) | Abraham Lincoln (wd:Q91)  |
| s:Q3093556-51dc088a-4af4-6ed8-901b-8126daa2e479   | appointed by (pq:P748) | Napoleon (wd:Q517)        |
| ...                                               | ...                    | ...                       |

[Assistant]
The structure is confirmed: "appointed by" (pq:P748) is used as a qualifier on a statement, typically on "position held" (P39).

So, to answer the question, we need to:
- Find all people (?person) with a "position held" (P39) statement that has a qualifier "appointed by" (P748) with value Donald Trump (wd:Q22686).
- For each, return the person and the position.

Now, I'll write a SPARQL query to retrieve:
- The person (?person)
- The position (?position)
- Optionally, their labels for readability

Let's proceed to construct and execute this query.

[Tool]
Got 90 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                                | position                                                           | personLabel                | positionLabel                                           |
| ------------------------------------- | ------------------------------------------------------------------ | -------------------------- | ------------------------------------------------------- |
| Karoline Leavitt (wd:Q100146113)      | White House Press Secretary (wd:Q2306431)                          | Karoline Leavitt (en)      | White House Press Secretary (en)                        |
| Christopher C. Miller (wd:Q101423348) | Director of the National Counterterrorism Center (wd:Q104720749)   | Christopher C. Miller (en) | Director of the National Counterterrorism Center (en)   |
| Christopher C. Miller (wd:Q101423348) | United States Secretary of Defense (wd:Q735015)                    | Christopher C. Miller (en) | United States Secretary of Defense (en)                 |
| Jennifer Homendy (wd:Q106916479)      | Member of the National Transportation Safety Board (wd:Q125195889) | Jennifer Homendy (en)      | Member of the National Transportation Safety Board (en) |
| Anthony M. Ornato (wd:Q112867791)     | White House Deputy Chief of Staff (wd:Q7994871)                    | Anthony M. Ornato (en)     | White House Deputy Chief of Staff (en)                  |
| ...                                   | ...                                                                | ...                        | ...                                                     |
| Alyssa Farah Griffin (wd:Q86419354)   | White House Director of Strategic Communications (wd:Q28450497)    | Alyssa Farah Griffin (en)  | White House Director of Strategic Communications (en)   |
| Brian Jack (wd:Q86493775)             | White House Political Director (wd:Q108485661)                     | Brian Jack (en)            | White House Political Director (en)                     |
| Jeffrey Ross Gunter (wd:Q91601834)    | United States Ambassador to Iceland (wd:Q7889312)                  | Jeffrey Ross Gunter (en)   | United States Ambassador to Iceland (en)                |
| Lydia Tederick (wd:Q96475700)         | White House Office of the Curator (wd:Q2928404)                    | Lydia Tederick (en)        | White House Office of the Curator (en)                  |
| Roger D. Carstens (wd:Q97727835)      | Special Envoy for Hostage Affairs (wd:Q85802513)                   | Roger D. Carstens (en)     | Special Envoy for Hostage Affairs (en)                  |

[Tool] Stopped generation process


PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
SELECT ?person ?elo ?date WHERE {
  ?person p:P1087 ?statement .
  ?statement ps:P1087 ?elo .
  ?statement pq:P585 ?date .
  FILTER ( ?date >= "2023-01-01T00:00:00Z" ^^ xsd:dateTime && ?date < "2023-02-01T00:00:00Z" ^^ xsd:dateTime )
}
ORDER BY DESC ( ?elo )
LIMIT 100

The top 100 people with the highest Elo ratings in January 2023 can be found by the query above. Each result includes the person's Wikidata identifier, their Elo rating, and the date (within January 2023). The results are ordered by Elo rating in descending order.

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

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

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

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

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

[User] Who were the top 100 people with the highest Elo ratings in January 2023? Please include their Elo rating, and order by their Elo rating in descending order.

[Assistant]
Let's break down the question:

1. We are looking for people (likely chess players) with Elo ratings.
2. We want the top 100 by Elo rating, specifically for January 2023.
3. We need to include their Elo rating and order the results by rating descending.

First, let's check if there is an entity or property for "Elo rating" in Wikidata, and if there is a way to specify the date (January 2023).

I'll start by searching for the "Elo rating" property in Wikidata.

[Tool]
Top 10 property alternatives:
1. Elo rating (wd:P1087 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): quantitative measure of one's game-playing ability, particularly in classical chess
2. review score, also known as rating (score), review rating (wd:P444 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): review score received by a creative work or other entity
3. rating (wd:P4271 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): qualifier to indicate a score given by the referenced source indicating the quality or completeness of the statement
4. number of reviews/ratings, also known as number of reviews, ratings, reviews, number of ratings (wd:P7887 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): qualifier on review score to state the number of user reviews, user ratings or critic reviews
5. dan/kyu rank, also known as go rank, wushu rank, shogi rank, renju rank, kendo rank (wd:P468 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): rank system used in several board games (e.g. go, shogi, renju), martial arts (e.g. judo, kendo, wushu) and some other games
6. ranking, also known as peak position, place, placing, position, rank (wd:P1352 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): subject's ordinal position as qualitatively evaluated relative to other members of a group
7. score method, also known as scoring system, score type, scoring metric, scoring method, score system (wd:P1443 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): qualifier of "points/goal scored by (P1363)"
8. league level above, also known as level above (league), promotion to (wd:P2499 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): the league above this sports league, next higher rank
9. series ordinal, also known as ordinal, unit number, sort order, sorting order, series number (wd:P1545 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): position of an item in its parent series (most frequently a 1-ba...d from "ranking" defined as a property for evaluating a quality)
10. military or police rank, also known as military rank, naval rank, police rank, rank (wd:P410 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): military or police rank achieved by a person (should usually hav...ualifier), or military or police rank associated with a position

[Assistant]
The property for "Elo rating" is wd:P1087. This property is used for the quantitative measure of one's game-playing ability, particularly in classical chess.

Next, we need to check if this property can be qualified with a date, so we can filter for January 2023. I'll search for qualifiers related to "point in time" or "date" for this property.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. property proposal discussion, also known as proposal, Wikidata property proposal, proposal URL, property discussion URL, property discussion (wd:P3254 as wdt/p): URL of the page (or page section) on which the creation of the property was discussed, Wikimedia community discussion URL
3. Wikidata item of this property, also known as associated item, Wikidata property subject item, Wikidata item for this property, subject of this property, subject of property (wd:P1629 as wdt/p): item corresponding to the concept represented by the property
4. Wikidata property example, also known as e.g., Wikidata property sample, property sample, property example, for example (wd:P1855 as wdt/p): example where this Wikidata property is used; target item is one...ualifier the property being described given the associated value
5. property constraint, also known as rdfs:range, constraint, rdfs:domain (wd:P2302 as wdt/p): constraint applicable to a Wikidata property
6. stability of property value, also known as variability of value, variability of property, stability of value, stability of property value, stability of property (wd:P2668 as wdt/p): likelihood that statements with this property will change

No other items found

[Tool]
Top 10 property alternatives:
1. point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
2. valid in period, also known as valid in season, valid for season, valid for period, valid for, time period (wd:P1264 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): time period when a statement is valid
3. set in period, also known as time period set in, time period of setting, time period, takes place in time, takes place during (wd:P2408 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): historical, contemporary, or future period, year, century or day...rk or genre is set in or event featured in the story of the work
4. time period, also known as oge (oge akụkọ ihe mere eme ma ọ...ụ mere ma ọ bụ nke ejikọtara ya. (wd:P2348 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): time period (historic period or era, sports season, theatre seas...c.) in which the subject occurred or with which it is associated
5. start time, also known as start date, since, valid, join time, joined (wd:P580 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): time an entity begins to exist or a statement starts being valid, point in time
6. date depicted, also known as depicted date, temporal coverage, shown as at date, depicts date, depicted time (wd:P2913 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): date represented in a work (for narrative works use P2408)
7. term length of position, also known as term length, time in position, term of position, position term, length of term (wd:P2097 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): length of time in years (unit: Q577) a person (usually a politician) is to serve in a particular position. Do not add bounds., duration
8. history of topic, also known as history of the topic, timeline of subject, timeline of the subject, timeline of the topic, timeline of topic (wd:P2184 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): item about the historical development of a subject's topic, exam... To list key events of the topic, use "significant event" (P793), studied in
9. latest date, also known as terminus ante quem, prior to, on or before this date, no later than, max date (wd:P1326 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): latest possible time that something could have occurred. Use as qualifier for other date properties
10. recording date, also known as recorded date, record date, recdate, rec. date, date of recording (wd:P10135 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): the date when a recording was made, inception

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                           | property               | object             |
| --------------------------------- | ---------------------- | ------------------ |
| Magnus Carlsen (wd:Q106807)       | Elo rating (wdt:P1087) | 2832 (xsd:decimal) |
| Mikhail Tal (wd:Q102664)          | Elo rating (wdt:P1087) | 2525 (xsd:decimal) |
| Vasily Smyslov (wd:Q104148)       | Elo rating (wdt:P1087) | 2480 (xsd:decimal) |
| Bent Larsen (wd:Q108807)          | Elo rating (wdt:P1087) | 2415 (xsd:decimal) |
| Harika Dronavalli (wd:Q109147059) | Elo rating (wdt:P1087) | 2502 (xsd:decimal) |
| Jan-Krzysztof Duda (wd:Q10860652) | Elo rating (wdt:P1087) | 1834 (xsd:decimal) |
| Andor Lilienthal (wd:Q113167)     | Elo rating (wdt:P1087) | 2385 (xsd:decimal) |
| Anna Cramling (wd:Q104539456)     | Elo rating (wdt:P1087) | 2045 (xsd:decimal) |
| Jon Ludvig Hammer (wd:Q1152824)   | Elo rating (wdt:P1087) | 2596 (xsd:decimal) |
| Carlos Guimard (wd:Q1042965)      | Elo rating (wdt:P1087) | 2325 (xsd:decimal) |
| ...                               | ...                    | ...                |

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                          | property             | object                                            |
| -------------------------------- | -------------------- | ------------------------------------------------- |
| Magnus Carlsen (wd:Q106807)      | Elo rating (p:P1087) | s:Q106807-011A7F8B-2AAE-4C51-B47F-9ACD6F9C315B    |
| Mikhail Tal (wd:Q102664)         | Elo rating (p:P1087) | s:Q102664-0c4cfe4f-2e37-4bf1-99a4-7a07e179f1eb    |
| Vasily Smyslov (wd:Q104148)      | Elo rating (p:P1087) | s:Q104148-070A06C1-065A-4527-AFD7-AB41436E5928    |
| Alexander Khalifman (wd:Q106374) | Elo rating (p:P1087) | s:Q106374-046A1CED-407D-4168-9185-9ADD5FA760C4    |
| Anna Cramling (wd:Q104539456)    | Elo rating (p:P1087) | s:Q104539456-003C73F1-1B0B-44E4-A4B2-E44EAF76493B |
| Carlos Guimard (wd:Q1042965)     | Elo rating (p:P1087) | s:Q1042965-02949667-e10c-41b2-8281-7081a816ec87   |
| Christian Bauer (wd:Q1078924)    | Elo rating (p:P1087) | s:Q1078924-03CCEC79-FDB8-4119-A2B8-A6B91CFDB78D   |
| Carlos Bielicki (wd:Q1042752)    | Elo rating (p:P1087) | s:Q1042752-02045444-A46C-4F1A-A500-9B762CB65E5E   |
| Tatiana Melamed (wd:Q108199)     | Elo rating (p:P1087) | s:Q108199-01CD75D5-EAA6-4173-9FC5-9DF57EF266D9    |
| Camila Colombo (wd:Q1028926)     | Elo rating (p:P1087) | s:Q1028926-049DA126-1CCA-4323-AACF-66AE0F8B4E9E   |
| ...                              | ...                  | ...                                               |

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                         | property                | object                              |
| ----------------------------------------------- | ----------------------- | ----------------------------------- |
| s:L1001895-c4a16b6f-4a7c-974c-3abd-376ece81edfb | point in time (pq:P585) | 2023-09-07T00:00:00Z (xsd:dateTime) |
| s:L1003898-8e8a6772-461a-6c4b-d5a4-f5b6f42358d3 | point in time (pq:P585) | 2024-08-02T00:00:00Z (xsd:dateTime) |
| s:L1006394-bc0eb96a-4c0f-9363-4453-77062c39c498 | point in time (pq:P585) | 2025-01-04T00:00:00Z (xsd:dateTime) |
| s:L1007058-44797370-42bd-9083-fcc4-dc2fa42017c4 | point in time (pq:P585) | 2024-08-01T00:00:00Z (xsd:dateTime) |
| s:L1011418-525c6808-4c83-0b81-923f-7311d79fa5f9 | point in time (pq:P585) | 1900-01-01T00:00:00Z (xsd:dateTime) |
| s:L1011441-776c2c8a-42e6-ea66-95e0-226df3322b59 | point in time (pq:P585) | 2023-02-02T00:00:00Z (xsd:dateTime) |
| s:L1012744-6bb047fb-4341-e6fd-eb5a-fb669f9dbcac | point in time (pq:P585) | 1600-01-01T00:00:00Z (xsd:dateTime) |
| s:L1016914-b69e1e80-4313-7306-346f-3ae2243f6281 | point in time (pq:P585) | 2023-09-14T00:00:00Z (xsd:dateTime) |
| s:L1018273-910e54b5-4dc0-dc0d-2dcb-45d33fc7c365 | point in time (pq:P585) | 2023-02-14T00:00:00Z (xsd:dateTime) |
| s:L1018302-0A585CBC-BC7A-4257-9B00-3E159D6E1832 | point in time (pq:P585) | 2024-02-11T00:00:00Z (xsd:dateTime) |
| ...                                             | ...                     | ...                                 |

[Tool]
Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                              | statement                                        | elo                | date                                |
| ----------------------------------- | ------------------------------------------------ | ------------------ | ----------------------------------- |
| Yu Yangyi (wd:Q377866)              | s:Q377866-16356490-A268-4D75-9033-952C84FFE33F   | 2729 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Francisco Vallejo Pons (wd:Q543256) | s:Q543256-EDEB0850-80FF-4C61-A7DD-979E4406040E   | 2710 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Hans Niemann (wd:Q59137809)         | s:Q59137809-C821182C-36CE-4C79-A585-EC0FC2D7BB82 | 2706 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Kirill Alekseenko (wd:Q18923582)    | s:Q18923582-8D47BAD0-E18B-4034-9FAE-9A528B0AD703 | 2686 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Amin Tabatabaei (wd:Q23710569)      | s:Q23710569-89BF84ED-B692-41BB-8180-7AFE704D4DB9 | 2686 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| ...                                 | ...                                              | ...                | ...                                 |
| Nikolas Theodorou (wd:Q27533120)    | s:Q27533120-E63ECB17-68E7-4999-9B58-BB624E72D716 | 2590 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Shamsiddin Vokhidov (wd:Q27533974)  | s:Q27533974-4A5F368D-08B1-49AE-B6DF-AE84828B34F3 | 2589 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Viktor Erdős (wd:Q2524265)          | s:Q2524265-91A7A704-0EC4-4D46-A06D-FF84B2239568  | 2588 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Ivan Sokolov (wd:Q709548)           | s:Q709548-6CB5002F-4C8D-4F9C-8FB4-41347B704B67   | 2588 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Peter Michalík (wd:Q539326)         | s:Q539326-7FB9B563-32A5-4DA7-BF4E-A05FB2FCFC66   | 2588 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?item ?itemLabel WHERE {
  ?item wdt:P2093 "Fred Smith" .
  OPTIONAL {
    ?item rdfs:label ?itemLabel .
  }
}

Got 15 rows and 2 columns, showing the first 5 and last 5 rows below:
| item                                                                                | itemLabel                                                                |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| Can Unions Be Sued for Following the Law? (wd:Q128767199)                           | Can Unions Be Sued for Following the Law? (en)                           |
| A Better Hope: Resources for a C...sm, Democracy, and Postmodernity (wd:Q128929105) | A Better Hope: Resources for a C...sm, Democracy, and Postmodernity (en) |
| Computerized Deep Structure Indexing System – A critical appraisal (wd:Q129292383)  | Computerized Deep Structure Indexing System – A critical appraisal (en)  |
| Term and cross reference structu...d Deep Structure Indexing System (wd:Q129294127) | Term and cross reference structu...d Deep Structure Indexing System (en) |
| FORTRAN programming standards (wd:Q130959327)                                       | FORTRAN programming standards (en)                                       |
| ...                                                                                | ...                                                                      |
| FOR THE PERIOD JANUARY-SEPTEMBER, 2003 (wd:Q58549138)                               | FOR THE PERIOD JANUARY-SEPTEMBER, 2003 (nl)                              |
| 24 Hour Service at Georgia Southern University: 1989–2007 (wd:Q58602086)            | 24 Hour Service at Georgia Southern University: 1989–2007 (en)           |
| 24 Hour Service at Georgia Southern University: 1989–2007 (wd:Q58602086)            | 24 Hour Service at Georgia Southern University: 1989–2007 (nl)           |
| Cardiac epithelioid hemangioendothelioma with 8-year follow-up (wd:Q80335651)       | Cardiac epithelioid hemangioendothelioma with 8-year follow-up (en)      |
| Cardiac epithelioid hemangioendothelioma with 8-year follow-up (wd:Q80335651)       | Cardiac epithelioid hemangioendothelioma with 8-year follow-up (nl)      |

This query returns all items that have exactly the string "Fred Smith" listed under their author name string (P2093), along with optional labels for those items.

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

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

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

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

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

[User] Which items have exactly the string "Fred Smith" listed under its author name string?

[Assistant]
Let's break down the question:

1. We are looking for items (entities) that have an "author name string" property with the exact value "Fred Smith".
2. We need to identify the property in Wikidata that corresponds to "author name string".
3. Then, we will construct a query to find all items where this property has the value "Fred Smith".

First, I will search for the property "author name string" in Wikidata.

[Tool]
Top 10 property alternatives:
1. author name string, also known as short author name, writer named as, writer name, writer indicated as, songwriting credits string (wd:P2093 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): stores unspecified author or editor name for publications; use i...or editor (P98) does not exist or is not known. Do not use both.
2. author last names, also known as author last name, surnames, surname, last names, last name (wd:P9688 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): qualifier to provide string representation of family or primary ...presented in a bibliographic reference file (for example BibTeX), family name
3. EXQUIRITE author ID, also known as EXQUIRITE author identifier, IRIS UNISTRAPG author ID, IRIS UNISTRAPG author identifier (wd:P10071 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier for an author in EXQUIRITE, the open-access repository of the Università per Stranieri di Perugia
4. BioNames author ID, also known as BioNames author identifier (wd:P11029 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier for an author in the BioNames database
5. SEARCH on line catalogue ID, also known as SEARCH author ID, SEARCH ID (wd:P9081 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier for an authority in the SEARCH on line catalogue (union-catalog of four libraries in Rome)
6. author given names, also known as given name, given names, first name, author first names, author first name (wd:P9687 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): qualifier for string representation of given or secondary sortin...presented in a bibliographic reference file (for example BibTeX), given name
7. LibraryThing author ID, also known as Library Thing author ID, LT author ID (wd:P7400 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier for an author on the LibraryThing website
8. Databazeknih.cz author ID, also known as Databáze knih author ID (wd:P10387 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): numeric ID of author in Databáze knih
9. Online Books Page author ID, also known as OnlineBooks author ID (wd:P4629 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): identifier for an author, at the Online Books Page website
10. Arnet Miner author ID, also known as AMiner author ID (wd:P5776 as wdt/psv/psn/prn/pqv/ps/p/prv/pr/wdtn/pq/pqn): author identifier from the Arnet Miner research database

[Assistant]
The property "author name string" corresponds to Wikidata property P2093. Now, I will construct a SPARQL query to find all items where the property P2093 has the exact value "Fred Smith". I will also try to include optional labels for easier interpretation.

Here is the SPARQL query I will use:

```sparql
SELECT ?item ?itemLabel WHERE {
  ?item wdt:P2093 "Fred Smith".
  OPTIONAL { ?item rdfs:label ?itemLabel. }
}
```

Now, I will provide this as the answer.

[Tool] Stopped generation process