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 ) - IF( MONTH( NOW () ) < MONTH( ?dob ) || ( MONTH( NOW () ) = MONTH( ?dob ) && DAY( NOW () ) < DAY( ?dob ) ) , 1 , 0 ) ) AS ?age ) FILTER ( ?age < 110 )
}
ORDER BY DESC ( ?age )
LIMIT 100

The 100 oldest living tennis players (excluding those 110 or older) are selected by age in descending order, including their IRIs, dates of birth, genders, and ages. For example, Rolf Göpfert (born 1916-02-16, male, age 109), Vera Mattar (born 1916-01-01, female, age 109), and others down to players aged 90. 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-sebastian

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

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

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

[User] 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 living.
2. We want their dates of birth, genders, and ages.
3. We want the 100 oldest, ordered by age descending.
4. We must exclude those who are 110 years old or older.

Step 1: Find the entity for "tennis player" and the properties for "date of birth", "gender", and "date of death" (to ensure they are living).

Step 2: Find the property for "gender".

Step 3: Find the property for "date of birth".

Step 4: Find the property for "date of death".

Step 5: Construct a query to select living tennis players, their date of birth, gender, and calculate their age, filter out those 110 or older, order by age descending, and limit to 100.

Let's 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, let's search for the properties for "date of birth", "gender", and "date of death" to use in our query.

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

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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" entity: wd:Q10833314
- "date of birth" property: wdt:P569
- "date of death" property: wdt:P570
- "sex or gender" property: wdt:P21

Now, we need to:
- Select humans (instance of wd:Q5) who are tennis players (occupation wdt:P106 wd:Q10833314).
- Ensure they are living (no date of death).
- Get their date of birth, gender, and calculate their age.
- Exclude those 110 or older.
- Order by age descending and limit to 100.

Let's check if "occupation" is the correct property for linking a person to "tennis player".

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
3. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): some or all members of this group share the occupation
4. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): type of agents that study this subject or work in this field
5. position held, also known as function, held position, holds position, job, office held (wd:P39 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): subject currently or formerly holds the object position or public office
6. employer, also known as working at, working for, working place, works at, works for (wd:P108 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): person or organization for which the subject works or worked, affiliation
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the object is a country that recognizes the subject as its citizen, country
8. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): person or organization occupying property, used by
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): specialization of a person or organization; see P106 for the occupation, interested in
10. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): location where persons or organisations were actively participating in employment, business or other work, significant place, location

[Assistant]
"Occupation" (wdt:P106) is indeed the correct property to link a person to "tennis player" (wd:Q10833314).

Now, let's construct the SPARQL query:
- Select humans (wd:Q5) with occupation tennis player (wd:Q10833314)
- Must not have a date of death (living)
- Get date of birth (wdt:P569), gender (wdt:P21)
- Calculate age (using NOW() and date of birth)
- Exclude those 110 or older
- Order by age descending
- Limit to 100

Let's write the query.

[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) |
| ...                                | ...                                 | ...                  | ...           |
| Mary Carter Reitano (wd:Q434596)   | 1934-11-29T00:00:00Z (xsd:dateTime) | female (wd:Q6581072) | 90 (xsd:int)  |
| Bill Giles (wd:Q4909141)           | 1934-09-07T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 90 (xsd:int)  |
| Chuck Swindoll (wd:Q5115734)       | 1934-10-18T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 90 (xsd:int)  |
| Tony Pickard (wd:Q3531860)         | 1934-09-13T00:00:00Z (xsd:dateTime) | male (wd:Q6581097)   | 90 (xsd:int)  |
| Janet Hopps Adkisson (wd:Q3161921) | 1934-08-04T00:00:00Z (xsd:dateTime) | female (wd:Q6581072) | 90 (xsd:int)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the 100 oldest living tennis players, excluding those aged 110 or older, and includes their IRIs, dates of birth, genders, and computed ages. The query also orders the results by age in descending order and does not use any non-standard SPARQL features. All requirements from the user question are met, and the answer is complete and accurate.


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?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 91 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                                | position                                                                          | personLabel                | positionLabel                                                          |
| ------------------------------------- | --------------------------------------------------------------------------------- | -------------------------- | ---------------------------------------------------------------------- |
| Emily Webster Murphy (wd:Q42282721)   | Administrator of General Services (wd:Q102259808)                                 | Emily Webster Murphy (en)  | Administrator of General Services (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)                  |
| Amul Roger Thapar (wd:Q4748925)       | Judge of the United States Court of Appeals for the Sixth Circuit (wd:Q107282720) | Amul Roger Thapar (en)     | Judge of the United States Court of Appeals for the Sixth Circuit (en) |
| Brian Jack (wd:Q86493775)             | White House Political Director (wd:Q108485661)                                    | Brian Jack (en)            | White House Political Director (en)                                    |
| Brett Kavanaugh (wd:Q4962244)         | Associate Justice of the Supreme Court of the United States (wd:Q11144)           | Brett Kavanaugh (en)       | Associate Justice of the Supreme Court of the United States (en)       |
| ...                                   | ...                                                                               | ...                        | ...                                                                    |
| Robert C. O'Brien (wd:Q7342642)       | Special Envoy for Hostage Affairs (wd:Q85802513)                                  | Robert C. O'Brien (en)     | Special Envoy for Hostage Affairs (en)                                 |
| Joseph Otting (wd:Q17306111)          | Comptroller of the Currency (wd:Q89682521)                                        | Joseph Otting (en)         | Comptroller of the Currency (en)                                       |
| Elaine Chao (wd:Q263322)              | United States Secretary of Transportation (wd:Q967737)                            | Elaine Chao (en)           | United States Secretary of Transportation (en)                         |
| Eugene Scalia (wd:Q16875330)          | United States Secretary of Labor (wd:Q967750)                                     | Eugene Scalia (en)         | United States Secretary of Labor (en)                                  |
| Betsy DeVos (wd:Q4898286)             | United States Secretary of Education (wd:Q967762)                                 | Betsy DeVos (en)           | United States Secretary of Education (en)                              |

The people appointed by Donald Trump and the positions they were appointed to can be found by retrieving all individuals with a 'position held' statement where the 'appointed by' qualifier is Donald Trump. The query returns the person and the position for each appointment.

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

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

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

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

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

[User] 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. This likely corresponds to a property such as "appointed by" or "position held with appointer". Let's search for properties related to "appointed by".

[Tool]
Top 10 property alternatives:
1. appointed by, also known as named by (wd:P748 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): 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 pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): 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 pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): 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 pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): 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 pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): 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 pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): person or organization in charge of keeping the subject (for instance an infrastructure) in functioning order
7. academic appointment (wd:P8413 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): 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 pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): entity having executive power on given entity
9. position held, also known as function, held position, holds position, job, office held (wd:P39 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): 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 pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): 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 the most relevant. However, it is often used as a qualifier on "position held" (wd:P39), indicating who appointed a person to a specific position.

So, to answer the question, we need to:
- Find all people (?person) with a "position held" (wd:P39) statement,
- Where the "appointed by" (wd:P748) qualifier is Donald Trump (wd:Q22686),
- And retrieve the position (?position) for each person.

Let's construct a SPARQL query to do this, returning the person and the position they were appointed to, along with optional labels.

[Tool]
Got 91 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                                | position                                                                          | personLabel                | positionLabel                                                          |
| ------------------------------------- | --------------------------------------------------------------------------------- | -------------------------- | ---------------------------------------------------------------------- |
| Emily Webster Murphy (wd:Q42282721)   | Administrator of General Services (wd:Q102259808)                                 | Emily Webster Murphy (en)  | Administrator of General Services (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)                  |
| Amul Roger Thapar (wd:Q4748925)       | Judge of the United States Court of Appeals for the Sixth Circuit (wd:Q107282720) | Amul Roger Thapar (en)     | Judge of the United States Court of Appeals for the Sixth Circuit (en) |
| Brian Jack (wd:Q86493775)             | White House Political Director (wd:Q108485661)                                    | Brian Jack (en)            | White House Political Director (en)                                    |
| Brett Kavanaugh (wd:Q4962244)         | Associate Justice of the Supreme Court of the United States (wd:Q11144)           | Brett Kavanaugh (en)       | Associate Justice of the Supreme Court of the United States (en)       |
| ...                                   | ...                                                                               | ...                        | ...                                                                    |
| Robert C. O'Brien (wd:Q7342642)       | Special Envoy for Hostage Affairs (wd:Q85802513)                                  | Robert C. O'Brien (en)     | Special Envoy for Hostage Affairs (en)                                 |
| Joseph Otting (wd:Q17306111)          | Comptroller of the Currency (wd:Q89682521)                                        | Joseph Otting (en)         | Comptroller of the Currency (en)                                       |
| Elaine Chao (wd:Q263322)              | United States Secretary of Transportation (wd:Q967737)                            | Elaine Chao (en)           | United States Secretary of Transportation (en)                         |
| Eugene Scalia (wd:Q16875330)          | United States Secretary of Labor (wd:Q967750)                                     | Eugene Scalia (en)         | United States Secretary of Labor (en)                                  |
| Betsy DeVos (wd:Q4898286)             | United States Secretary of Education (wd:Q967762)                                 | Betsy DeVos (en)           | United States Secretary of Education (en)                              |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves people appointed by Donald Trump and the positions they were appointed to, using the appropriate properties and qualifiers. The query returns the IRIs for both the person and the position, and includes optional labels for readability. The answer is complete and follows all specified rules.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?person ?elo ?date ?personLabel WHERE {
  ?person wdt:P31 wd:Q5 .
  ?person p:P1087 ?statement .
  ?statement ps:P1087 ?elo ; pq:P585 ?date .
  FILTER ( STRSTARTS( STR( ?date ) , "2023-01" ) ) OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( LANG( ?personLabel ) = "en" )
  }
}
ORDER BY DESC ( ?elo )
LIMIT 100

Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                              | elo                | date                                | personLabel                 |
| ----------------------------------- | ------------------ | ----------------------------------- | --------------------------- |
| Yu Yangyi (wd:Q377866)              | 2729 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Yu Yangyi (en)              |
| Francisco Vallejo Pons (wd:Q543256) | 2710 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Francisco Vallejo Pons (en) |
| Hans Niemann (wd:Q59137809)         | 2706 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Hans Niemann (en)           |
| Kirill Alekseenko (wd:Q18923582)    | 2686 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Kirill Alekseenko (en)      |
| Amin Tabatabaei (wd:Q23710569)      | 2686 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Amin Tabatabaei (en)        |
| ...                                 | ...                | ...                                 | ...                         |
| Nikolas Theodorou (wd:Q27533120)    | 2590 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Nikolas Theodorou (en)      |
| Shamsiddin Vokhidov (wd:Q27533974)  | 2589 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Shamsiddin Vokhidov (en)    |
| Viktor Erdős (wd:Q2524265)          | 2588 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Viktor Erdős (en)           |
| Ivan Sokolov (wd:Q709548)           | 2588 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Ivan Sokolov (en)           |
| Peter Michalík (wd:Q539326)         | 2588 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Peter Michalík (en)         |

This query returns the top 100 humans with the highest Elo ratings in January 2023, including their Elo rating, the date of the rating, and their label (if available), 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-sebastian

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

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

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

[User] 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 their Elo ratings as of January 2023.
3. We want the top 100, ordered by Elo rating descending.
4. We need to include their Elo rating in the result.

First, I need to identify:
- The property for Elo rating in Wikidata.
- How Elo ratings are represented with time qualifiers (e.g., January 2023).
- The entity for January 2023, if needed.

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

[Tool]
Top 10 property alternatives:
1. Elo rating (wd:P1087 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): review score received by a creative work or other entity
3. rating (wd:P4271 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): qualifier of "points/goal scored by (P1363)"
8. league level above, also known as level above (league), promotion to (wd:P2499 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 in Wikidata is wd:P1087 ("Elo rating"). Next, I need to determine how Elo ratings are represented with time qualifiers, specifically for January 2023.

Typically, qualifiers like "point in time" (likely wd:P585) are used to specify the date for a given value. I'll confirm the property for "point in time" and check how Elo ratings are qualified with dates.

[Tool]
Top 10 property alternatives:
1. point in time, also known as at time, as of, year, when, time of event (wd:P585 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the date when a recording was made, inception

[Assistant]
The property for "point in time" is wd:P585. This is likely used as a qualifier on Elo rating statements to specify the date.

Now, I need to check how Elo ratings are represented for people, and how the "point in time" qualifier is used. I'll list some triples where the property is Elo rating (wdt:P1087), to see the structure and confirm the use of qualifiers.

[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) |
| ...                               | ...                    | ...                |

[Assistant]
The direct property wdt:P1087 gives the Elo rating, but does not include qualifiers such as the date. To get Elo ratings as of a specific date (January 2023), I need to use the full statement path (p:P1087), which allows access to qualifiers like "point in time" (pq:P585).

Next, I need to confirm the value for January 2023. Usually, the "point in time" qualifier is a date literal (e.g., "2023-01-01"^^xsd:date). I'll check some Elo rating statements with their qualifiers to confirm this.

[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 7 rows and 3 columns:
| subject                                        | property                 | object                                       |
| ---------------------------------------------- | ------------------------ | -------------------------------------------- |
| s:Q106807-011A7F8B-2AAE-4C51-B47F-9ACD6F9C315B | Elo rating (ps:P1087)    | 2882 (xsd:decimal)                           |
| s:Q106807-011A7F8B-2AAE-4C51-B47F-9ACD6F9C315B | point in time (pq:P585)  | 2014-05-01T00:00:00Z (xsd:dateTime)          |
| s:Q106807-011A7F8B-2AAE-4C51-B47F-9ACD6F9C315B | wikibase:rank            | wikibase:NormalRank                          |
| s:Q106807-011A7F8B-2AAE-4C51-B47F-9ACD6F9C315B | rdf:type                 | wikibase:Statement                           |
| s:Q106807-011A7F8B-2AAE-4C51-B47F-9ACD6F9C315B | prov:wasDerivedFrom      | ref:a13cb5b476f8dd365e5c22a686a3ad7791ac569f |
| s:Q106807-011A7F8B-2AAE-4C51-B47F-9ACD6F9C315B | Elo rating (psv:P1087)   | v:7eb179c14755792dee594f7aebfaf7a7           |
| s:Q106807-011A7F8B-2AAE-4C51-B47F-9ACD6F9C315B | point in time (pqv:P585) | v:e0e14f5714aca22bfe702639db968957           |

[Tool] Got no rows and 3 columns

[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 no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[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 no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Assistant]
It appears that there are no Elo rating statements in Wikidata that are specifically qualified with the exact date "2023-01-01T00:00:00Z" or similar for January 2023. However, there are Elo ratings with various "point in time" qualifiers, some of which are close to January 2023 (e.g., February 2023, or late 2022).

Given this, the best approach is to:
- Retrieve all Elo rating statements with a "point in time" qualifier in 2023.
- Filter for those where the date is in January 2023, or as close as possible.
- Order by Elo rating descending and limit to the top 100.

I'll write a SPARQL query that:
- Finds people (?person) with an Elo rating statement (?statement).
- Gets the Elo rating value (?elo) and the "point in time" (?date).
- Filters for dates in January 2023.
- Orders by Elo rating descending.
- Limits to 100 results.
- Optionally includes the label for the person.

Here is the query:

[Tool]
Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                              | elo                | date                                | personLabel                 |
| ----------------------------------- | ------------------ | ----------------------------------- | --------------------------- |
| Yu Yangyi (wd:Q377866)              | 2729 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Yu Yangyi (en)              |
| Francisco Vallejo Pons (wd:Q543256) | 2710 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Francisco Vallejo Pons (en) |
| Hans Niemann (wd:Q59137809)         | 2706 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Hans Niemann (en)           |
| Kirill Alekseenko (wd:Q18923582)    | 2686 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Kirill Alekseenko (en)      |
| Amin Tabatabaei (wd:Q23710569)      | 2686 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Amin Tabatabaei (en)        |
| ...                                 | ...                | ...                                 | ...                         |
| Nikolas Theodorou (wd:Q27533120)    | 2590 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Nikolas Theodorou (en)      |
| Shamsiddin Vokhidov (wd:Q27533974)  | 2589 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Shamsiddin Vokhidov (en)    |
| Viktor Erdős (wd:Q2524265)          | 2588 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Viktor Erdős (en)           |
| Ivan Sokolov (wd:Q709548)           | 2588 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Ivan Sokolov (en)           |
| Peter Michalík (wd:Q539326)         | 2588 (xsd:decimal) | 2023-01-01T00:00:00Z (xsd:dateTime) | Peter Michalík (en)         |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query is mostly correct, but it is missing an important filter: it should restrict the results to humans (wd:Q5) to ensure that only people are included. Currently, the query could potentially return organizations or other entities with Elo ratings. Please add a triple like '?person wdt:P31 wd:Q5 .' to ensure only humans are included in the result. Otherwise, the structure and ordering of the query are correct.

[Assistant]
Thank you for your feedback. You are correct: to ensure that only people (humans) are included in the results, I should add a triple restricting ?person to instances of human (wd:Q5) using ?person wdt:P31 wd:Q5. I will update the query accordingly.

Here is the refined SPARQL query:

SELECT ?person ?elo ?date ?personLabel WHERE {
  ?person wdt:P31 wd:Q5 .
  ?person p:P1087 ?statement .
  ?statement ps:P1087 ?elo ;
             pq:P585 ?date .
  FILTER (STRSTARTS(STR(?date), "2023-01"))
  OPTIONAL { ?person rdfs:label ?personLabel FILTER (LANG(?personLabel) = "en") }
}
ORDER BY DESC(?elo)
LIMIT 100

This query now ensures that only humans are included in the result. I will submit this as the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the top 100 humans with the highest Elo ratings in January 2023, including their Elo rating, the date, and optionally their English label. The query uses the correct properties and filters, orders by Elo rating in descending order, and limits the result to 100. All requirements are met, and the query follows the specified rules for SPARQL queries.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
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 (wdt:P2093). The results include the item IRIs and, if available, their labels.

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

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

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

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

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

[User] Which 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. First, I need to identify the property in Wikidata that corresponds to "author name string".
3. Then, I 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): 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 pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for an author on the LibraryThing website
8. Databazeknih.cz author ID, also known as Databáze knih author ID (wd:P10387 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): numeric ID of author in Databáze knih
9. Online Books Page author ID, also known as OnlineBooks author ID (wd:P4629 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for an author, at the Online Books Page website
10. Arnet Miner author ID, also known as AMiner author ID (wd:P5776 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): author identifier from the Arnet Miner research database

[Assistant]
The property "author name string" in Wikidata is wdt:P2093. Now, I will construct a SPARQL query to find all items where the property wdt:P2093 has the exact value "Fred Smith".

I will also include optional labels for the items for better readability, but the main result will be the item IRIs.

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 final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all items that have exactly the string "Fred Smith" as their author name string (wdt:P2093). The query returns the required IRIs and optionally includes labels, as per best practices. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
SELECT ?person ?date ?personLabel WHERE {
  ?person p:P166 ?statement .
  ?statement ps:P166 wd:Q55455135 .
  OPTIONAL {
    ?statement pq:P585 ?date .
  }
  OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( lang( ?personLabel ) = "en" )
  }
}
ORDER BY ?date

Got 60 rows and 3 columns, showing the first 5 and last 5 rows below:
| person                                   | date                                | personLabel                    |
| ---------------------------------------- | ----------------------------------- | ------------------------------ |
| Manuel Alvar (wd:Q1891429)               | 1974-01-01T00:00:00Z (xsd:dateTime) | Manuel Alvar (en)              |
| Ludwig Buisson (wd:Q1563209)             | 1974-01-01T00:00:00Z (xsd:dateTime) | Ludwig Buisson (en)            |
| Christian Adolf Isermeyer (wd:Q15226554) | 1974-01-01T00:00:00Z (xsd:dateTime) | Christian Adolf Isermeyer (en) |
| Richard Hoggart (wd:Q1534871)            | 1974-01-01T00:00:00Z (xsd:dateTime) | Richard Hoggart (en)           |
| Nicolás Guillén (wd:Q334118)             | 1976-01-01T00:00:00Z (xsd:dateTime) | Nicolás Guillén (en)           |
| ...                                      | ...                                 | ...                            |
| Kaija Saariaho (wd:Q241432)              | 2015-01-01T00:00:00Z (xsd:dateTime) | Kaija Saariaho (en)            |
| Richard Dyer (wd:Q7325332)               | 2018-12-06T00:00:00Z (xsd:dateTime) | Richard Dyer (en)              |
| Patricio Guzmán (wd:Q2057315)            | 2019-03-12T00:00:00Z (xsd:dateTime) | Patricio Guzmán (en)           |
| Ibrahima Thioub (wd:Q1656025)            | 2020-01-20T00:00:00Z (xsd:dateTime) | Ibrahima Thioub (en)           |
| Trina Robbins (wd:Q458714)               | 2023-11-30T00:00:00Z (xsd:dateTime) | Trina Robbins (en)             |

The people who have received an honorary doctorate from Bordeaux Montaigne University (wd:Q13342) are listed in the query result. The results include the recipient's Wikidata IRI, the year (if available), and their English label, ordered by year of award.

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

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

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

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

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

[User] Who has received an honorary doctorate from Bordeaux Montaigne University? Please also include the year they received the doctorate and order results by year

[Assistant]
Let's break down the question:

1. We need to identify the entity for "Bordeaux Montaigne University".
2. We need to find the property for "honorary doctorate received from" or similar.
3. We need to retrieve people who received an honorary doctorate from this university, along with the year.
4. We need to order the results by year.

Let's start by searching for the entity "Bordeaux Montaigne University".

[Tool]
Top 10 entity alternatives:
1. Bordeaux Montaigne University, also known as University of Bordeaux 3, Michel de Montaigne University (wd:Q13342): French university founded in 1971
2. honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135)
3. University of Bordeaux, also known as UB, u-bordeaux.fr (wd:Q13344): university in France
4. Bordeaux Segalen University, also known as University of Bordeaux 2 (wd:Q13340): former French university abolished and replaced in 2014
5. IUT Bordeaux Montaigne, also known as University Institute of Journalism Technology of Bordeaux, IUT Michel de Montaigne (wd:Q3152663)
6. Bordeaux University Foundation (wd:Q117197454)
7. University of Bordeaux (wd:Q20791505): French university from 1896 to 1971
8. University of Bordeaux 1 (wd:Q13338): former French university founded in 1971, replaced and abolished in 2014
9. prix Montaigne de Bordeaux (wd:Q16671140): French literary prize
10. Bordeaux University Law Library (wd:Q97667454): University law and economics library

[Assistant]
The main entity for Bordeaux Montaigne University is wd:Q13342. There is also a specific entity for "honorary doctorate of the Bordeaux Montaigne University" (wd:Q55455135), which might be useful.

Next, I need to find the property for "received honorary doctorate from" or similar, to link people to the university as recipients. I'll search for properties related to "honorary doctorate".

[Tool]
Top 10 property alternatives:
1. conferred by, also known as presented by, officiated by, issued by, granted by, given by (wd:P1027 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): person or organization who grants an award, certification, grant, or role
2. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): award or recognition received by a person, organization or creative work
3. professorship, also known as professorship position, named professorship, named chair, endowed professorship, chair (wd:P803 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): professorship position held by this academic person, position held
4. student of, also known as professor, studied under, pupil of, tutor, mentor (wd:P1066 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): person who has taught this person, significant person
5. category for employees of the organization, also known as Academic staff, category for employees of the organisation, Professor (wd:P4195 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): Wikimedia category for people who work or worked at this organization
6. UGentMemorialis professor ID, also known as UGent Memorialis ID, UGentMemorialis ID (wd:P3159 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for a professor at the Ghent University
7. doctoral advisor, also known as PhD supervisor, promotor, supervisor, thesis advisor, advisor (wd:P184 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): person who supervised the doctorate or PhD thesis of the subject, supervised by, student of
8. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): what the place, monument, memorial, or holiday, commemorates, main subject
9. doctoral student, also known as Ph.D. student, supervisee, supervised doctoral student, doctoral candidate (wd:P185 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): doctoral student(s) of a professor, student
10. rector, also known as chancellor, university president, Rector (academia), president (wd:P1075 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): senior official in an educational institution., director / manager, chairperson

[Assistant]
The most relevant properties are:
- "award received" (wd:P166), which can be used to indicate someone received an honorary doctorate.
- "conferred by" (wd:P1027), which can be used as a qualifier to specify the awarding institution.

Given that there is a specific entity for "honorary doctorate of the Bordeaux Montaigne University" (wd:Q55455135), the best approach is to find people who have "award received" (wd:P166) this specific award, and then retrieve the year (likely as a qualifier).

Next, I'll check what qualifiers are typically used with "award received" for honorary doctorates, especially for the year.

[Tool]
Got 57 rows and 3 columns, showing the first 10 rows below:
| subject                            | property                  | object                                                                 |
| ---------------------------------- | ------------------------- | ---------------------------------------------------------------------- |
| José Saramago (wd:Q37060)          | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| Mario Vargas Llosa (wd:Q39803)     | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| Elie Wiesel (wd:Q18391)            | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| Judith Butler (wd:Q219368)         | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| Carlos Fuentes (wd:Q154691)        | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| Vigdís Finnbogadóttir (wd:Q189797) | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| Krzysztof Penderecki (wd:Q153469)  | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| Mário Soares (wd:Q156781)          | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| Rafael Alberti (wd:Q118936)        | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| Abdou Diouf (wd:Q219728)           | award received (wdt:P166) | honorary doctorate of the Bordeaux Montaigne University (wd:Q55455135) |
| ...                                | ...                       | ...                                                                    |

[Assistant]
We have a list of people who received the honorary doctorate from Bordeaux Montaigne University using "award received" (wd:P166) with the object wd:Q55455135.

Now, to get the year, I need to check what qualifiers are used with these award statements. I'll look at the statement for one recipient, e.g., José Saramago (wd:Q37060), to see what qualifiers are available.

[Tool]
Got 21 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                | object                                        |
| ------------------------- | ----------------------- | --------------------------------------------- |
| José Saramago (wd:Q37060) | award received (p:P166) | s:Q37060-10db109c-4f25-fb70-3be3-ac38bb5b5776 |
| José Saramago (wd:Q37060) | award received (p:P166) | s:Q37060-183ce62a-4343-7833-9390-0148c0ce223b |
| José Saramago (wd:Q37060) | award received (p:P166) | s:Q37060-1d012fb0-47e1-b057-bd31-2b64999030c3 |
| José Saramago (wd:Q37060) | award received (p:P166) | s:Q37060-2095894f-494f-b7a5-87ab-e15d1428f542 |
| José Saramago (wd:Q37060) | award received (p:P166) | s:Q37060-29e8b566-438c-aebe-94d7-72864c6f9cde |
| José Saramago (wd:Q37060) | award received (p:P166) | s:q37060-2DB864D5-93CE-49DC-96B2-9146014CDEE2 |
| José Saramago (wd:Q37060) | award received (p:P166) | s:Q37060-35c89357-4b2a-28a6-2321-84b3c172b4ad |
| José Saramago (wd:Q37060) | award received (p:P166) | s:Q37060-46ccbd62-4841-26be-7971-dc564f8bc16b |
| José Saramago (wd:Q37060) | award received (p:P166) | s:Q37060-4a18a67f-4c01-864b-2f71-76430defff17 |
| José Saramago (wd:Q37060) | award received (p:P166) | s:Q37060-5a9d190b-4885-18b0-3a3e-44ea122d380a |
| ...                       | ...                     | ...                                           |

[Tool]
Got 7 rows and 3 columns:
| subject                                       | property                 | object                                                                    |
| --------------------------------------------- | ------------------------ | ------------------------------------------------------------------------- |
| s:Q37060-10db109c-4f25-fb70-3be3-ac38bb5b5776 | award received (ps:P166) | honorary doctorate of the University of Castille-La Mancha (wd:Q35803330) |
| s:Q37060-10db109c-4f25-fb70-3be3-ac38bb5b5776 | point in time (pq:P585)  | 1997-01-01T00:00:00Z (xsd:dateTime)                                       |
| s:Q37060-10db109c-4f25-fb70-3be3-ac38bb5b5776 | wikibase:rank            | wikibase:NormalRank                                                       |
| s:Q37060-10db109c-4f25-fb70-3be3-ac38bb5b5776 | rdf:type                 | wikibase:BestRank                                                         |
| s:Q37060-10db109c-4f25-fb70-3be3-ac38bb5b5776 | prov:wasDerivedFrom      | ref:074a3d21de71f8e3ca47be13c9d1a5cbdf5df0e7                              |
| s:Q37060-10db109c-4f25-fb70-3be3-ac38bb5b5776 | point in time (pqv:P585) | v:7eca85bb7139467b8a00957d652cc79c                                        |
| s:Q37060-10db109c-4f25-fb70-3be3-ac38bb5b5776 | rdf:type                 | wikibase:Statement                                                        |

[Assistant]
The qualifier "point in time" (pq:P585) is used to indicate the year the honorary doctorate was received.

Now, I will construct a SPARQL query to:
- Find all people (?person) who received the honorary doctorate of Bordeaux Montaigne University (wd:Q55455135) via "award received" (wd:P166)
- Retrieve the year (using pq:P585 as a qualifier)
- Optionally include the person's label
- Order the results by year

Let's write the query.

[Tool]
Got 60 rows and 3 columns, showing the first 5 and last 5 rows below:
| person                                   | date                                | personLabel                    |
| ---------------------------------------- | ----------------------------------- | ------------------------------ |
| Manuel Alvar (wd:Q1891429)               | 1974-01-01T00:00:00Z (xsd:dateTime) | Manuel Alvar (en)              |
| Ludwig Buisson (wd:Q1563209)             | 1974-01-01T00:00:00Z (xsd:dateTime) | Ludwig Buisson (en)            |
| Christian Adolf Isermeyer (wd:Q15226554) | 1974-01-01T00:00:00Z (xsd:dateTime) | Christian Adolf Isermeyer (en) |
| Richard Hoggart (wd:Q1534871)            | 1974-01-01T00:00:00Z (xsd:dateTime) | Richard Hoggart (en)           |
| Nicolás Guillén (wd:Q334118)             | 1976-01-01T00:00:00Z (xsd:dateTime) | Nicolás Guillén (en)           |
| ...                                      | ...                                 | ...                            |
| Kaija Saariaho (wd:Q241432)              | 2015-01-01T00:00:00Z (xsd:dateTime) | Kaija Saariaho (en)            |
| Richard Dyer (wd:Q7325332)               | 2018-12-06T00:00:00Z (xsd:dateTime) | Richard Dyer (en)              |
| Patricio Guzmán (wd:Q2057315)            | 2019-03-12T00:00:00Z (xsd:dateTime) | Patricio Guzmán (en)           |
| Ibrahima Thioub (wd:Q1656025)            | 2020-01-20T00:00:00Z (xsd:dateTime) | Ibrahima Thioub (en)           |
| Trina Robbins (wd:Q458714)               | 2023-11-30T00:00:00Z (xsd:dateTime) | Trina Robbins (en)             |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all recipients of an honorary doctorate from Bordeaux Montaigne University, includes the year (if available), and orders the results by year. It also returns the required IRIs and optionally includes English labels. The query follows all specified rules and meets the user's requirements.