PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?country WHERE {
  ?country wdt:P31 wd:Q3624078 .
  ?country wdt:P297 ?isoCode . MINUS {
    ?country wdt:P463 wd:Q1065 .
  }
}

Got 2 rows and 1 column:
| ?country               |
| ---------------------- |
| Palestine (wd:Q219060) |
| Vatican City (wd:Q237) |

2 countries have never been members of the UN.

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

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

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

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

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

[User] How many countries have never been members of the UN?

[Assistant]
To answer this question, we need to identify the countries that have never been members of the United Nations (UN). We can approach this by:

1. Finding all current and former UN member states.
2. Finding all countries.
3. Subtracting the set of UN member states from the set of all countries to get the countries that have never been members of the UN.

Let's start by finding the property that indicates UN membership and then list the UN member states.

[Tool]
Top 10 property alternatives:
1. UN number, also known as UN code (wd:P695 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): four-digit number that identify hazardous substances and articles in the framework of international transport
2. UN/LOCODE, also known as LOCCODE, LOCODE, UNECE location code, UNECE LOCODE, United Nations location code (wd:P1937 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): geographic location code maintained by UNECE
3. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): the political party of which a person is or has been a member or otherwise affiliated, member of
4. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
5. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): some or all members of this group share the occupation
6. UN document symbol, also known as United Nations Document Codes (wd:P3069 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): unique number assigned to United Nations  documents
7. general secretary, also known as secretary general, perpetual secretary, leader (wd:P3975 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): leader of a political or international organization, sometimes below the chairperson (P488), significant person, director / manager
8. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
9. signatory, also known as first signatories, ratified by, signatories, signed by, signer (wd:P1891 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): person, country, or organization that has signed an official document (use P50 for author), significant person
10. UN classification code, also known as UN code classification (wd:P875 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): code for classification of dangerous goods defined by UN

[Assistant]
From the search results, the property `wdt:P463` (member of) seems to be the most relevant for identifying UN member states. Let's list the UN member states using this property.

We will also need to find the property that identifies countries. A common property for this is `wdt:P31` (instance of) with the value `wd:Q6256` (country).

Let's start by listing the UN member states.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that there are no direct results when querying for UN member states using the property `wdt:P463` with the object `wd:Q11138` (United Nations). This might be because the UN member states are not directly linked to the UN in this way. Instead, we can try to find the property that indicates UN membership status and then list the UN member states using that property.

Let's search for a property that specifically indicates UN membership status.

[Tool]
Top 10 property alternatives:
1. UN number, also known as UN code (wd:P695 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): four-digit number that identify hazardous substances and articles in the framework of international transport
2. UN/LOCODE, also known as LOCCODE, LOCODE, UNECE location code, UNECE LOCODE, United Nations location code (wd:P1937 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): geographic location code maintained by UNECE
3. member count, also known as total members, number of members, count of members, amount of members, membership (wd:P2124 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): number of entities that are part of an organization at a particular time
4. United Nations Treaty Series registration number, also known as UNTS Registration Number, UNTSRN (wd:P4231 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): registration number of a treaty within the United Nations Treaty Series
5. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): some or all members of this group share the occupation
6. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): the political party of which a person is or has been a member or otherwise affiliated, member of
7. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
8. start time, also known as start date, since, valid, join time, joined (wd:P580 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): time an entity begins to exist or a statement starts being valid, point in time
9. IAU member ID, also known as IAU member identifier, International Astronomical Union member identifier, International Astronomical Union member ID (wd:P9467 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): identifier for a member of the International Astronomical Union (IAU)
10. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): language status identifier by Ethnologue.com using EGIDS scale

[Assistant]
None of the properties listed seem to directly indicate UN membership status. However, we can try using the property `wdt:P463` (member of) again, but this time we will look for the specific UN member states by searching for the UN as an organization and then finding its members.

Let's search for the UN as an organization and then list its members.

First, let's find the entity for the United Nations.

[Tool]
Top 10 entity alternatives:
1. United Nations, also known as the U.N., the UN, U.N., UN, United Nations Organization (wd:Q1065): global international and intergovernmental organization
2. United Nations (wd:Q7888317): American band
3. United Nations (wd:Q7888316): United Nations album
4. United Nations (wd:Q7888314): Rui En album
5. United Nations, also known as Canadian United, Canada United, Global United Nations Syndicate (wd:Q7888319): criminal gang who started in Vancouver, British Columbia
6. United Nations (wd:Q74063664): print in the National Gallery of Art (NGA 64023)
7. United Nations, also known as q Sm514 United Nations (wd:Q104713070): subject category of the 20th Century Press Archives
8. United Nations, also known as Star Trek UN, Star Trek United Nations, UN (wd:Q111240888): United Nations as depicted in the Star Trek multiverse
9. United Nations (wd:L620589-S1)
10. United Nations (wd:L618606-F1)

[Assistant]
The correct entity for the United Nations is `wd:Q1065`. Now, let's list the UN member states using the property `wdt:P463` (member of) with the object `wd:Q1065`.

This will give us the list of UN member states.

[Tool]
Got 231 rows and 3 columns, showing the first 10 rows below:
| subject                | property             | object                    |
| ---------------------- | -------------------- | ------------------------- |
| United States (wd:Q30) | member of (wdt:P463) | United Nations (wd:Q1065) |
| Turkey (wd:Q43)        | member of (wdt:P463) | United Nations (wd:Q1065) |
| Russia (wd:Q159)       | member of (wdt:P463) | United Nations (wd:Q1065) |
| Japan (wd:Q17)         | member of (wdt:P463) | United Nations (wd:Q1065) |
| Italy (wd:Q38)         | member of (wdt:P463) | United Nations (wd:Q1065) |
| France (wd:Q142)       | member of (wdt:P463) | United Nations (wd:Q1065) |
| Germany (wd:Q183)      | member of (wdt:P463) | United Nations (wd:Q1065) |
| Finland (wd:Q33)       | member of (wdt:P463) | United Nations (wd:Q1065) |
| Mexico (wd:Q96)        | member of (wdt:P463) | United Nations (wd:Q1065) |
| India (wd:Q668)        | member of (wdt:P463) | United Nations (wd:Q1065) |
| ...                    | ...                  | ...                       |

[Assistant]
We have successfully listed the UN member states. Now, we need to find all countries and then subtract the UN member states from this list to get the countries that have never been members of the UN.

First, let's find all countries by using the property `wdt:P31` (instance of) with the value `wd:Q6256` (country).

Let's list all countries.

[Tool]
Got 197 rows and 3 columns, showing the first 10 rows below:
| subject                | property              | object             |
| ---------------------- | --------------------- | ------------------ |
| United States (wd:Q30) | instance of (wdt:P31) | country (wd:Q6256) |
| Turkey (wd:Q43)        | instance of (wdt:P31) | country (wd:Q6256) |
| Russia (wd:Q159)       | instance of (wdt:P31) | country (wd:Q6256) |
| Japan (wd:Q17)         | instance of (wdt:P31) | country (wd:Q6256) |
| Italy (wd:Q38)         | instance of (wdt:P31) | country (wd:Q6256) |
| France (wd:Q142)       | instance of (wdt:P31) | country (wd:Q6256) |
| Germany (wd:Q183)      | instance of (wdt:P31) | country (wd:Q6256) |
| Finland (wd:Q33)       | instance of (wdt:P31) | country (wd:Q6256) |
| Mexico (wd:Q96)        | instance of (wdt:P31) | country (wd:Q6256) |
| India (wd:Q668)        | instance of (wdt:P31) | country (wd:Q6256) |
| ...                    | ...                   | ...                |

[Assistant]
We have listed all countries. Now, we need to subtract the UN member states from the list of all countries to find the countries that have never been members of the UN.

Let's construct a SPARQL query to achieve this. We will use a `MINUS` clause to exclude the UN member states from the list of all countries.

Here is the SPARQL query:

```sparql
SELECT ?country
WHERE {
  ?country wdt:P31 wd:Q6256.
  MINUS {
    ?country wdt:P463 wd:Q1065.
  }
}
```

Let's execute this query to get the list of countries that have never been members of the UN.

[Tool]
Got 21 rows and 1 column, showing the first 5 and last 5 rows below:
| ?country                     |
| ---------------------------- |
| Chinland (wd:Q124153644)     |
| Ashkenaz (wd:Q124535978)     |
| Havilah (wd:Q124536190)      |
| Kosovo (wd:Q1246)            |
| Persia (wd:Q125422413)       |
| ...                          |
| Denmark (wd:Q35)             |
| Tarshish (wd:Q44826)         |
| Netherlands (wd:Q55)         |
| Mallabhum (wd:Q6744020)      |
| Bharatpur State (wd:Q854850) |

[Assistant]
The SPARQL query has returned a list of 21 countries that have never been members of the UN. However, some of these results seem to be historical or fictional places, which are not actual modern countries. To refine our query, we should filter out these non-current countries.

We can use the property `wdt:P31` (instance of) with the value `wd:Q3624078` (sovereign state) to ensure we only get current sovereign states.

Let's modify the SPARQL query to include this filter:

```sparql
SELECT ?country
WHERE {
  ?country wdt:P31 wd:Q3624078.
  MINUS {
    ?country wdt:P463 wd:Q1065.
  }
}
```

Let's execute this refined query.

[Tool]
Got 6 rows and 1 column:
| ?country                                     |
| -------------------------------------------- |
| First Republic of Seychelles (wd:Q129619467) |
| Lechia (wd:Q17050654)                        |
| French Fifth Republic (wd:Q200686)           |
| Palestine (wd:Q219060)                       |
| Vatican City (wd:Q237)                       |
| Mallabhum (wd:Q6744020)                      |

[Assistant]
The refined SPARQL query has returned 6 results, but some of these are still not current sovereign states. For example, "First Republic of Seychelles" and "French Fifth Republic" are historical entities, and "Mallabhum" is a historical region.

To further refine the query, we should ensure that we are only considering current sovereign states. We can use the property `wdt:P31` (instance of) with the value `wd:Q3624078` (sovereign state) and also check for the property `wdt:P576` (dissolved or abolished) to exclude historical entities.

Here is the updated SPARQL query:

```sparql
SELECT ?country
WHERE {
  ?country wdt:P31 wd:Q3624078.
  MINUS {
    ?country wdt:P463 wd:Q1065.
  }
  MINUS {
    ?country wdt:P576 ?dissolvedDate.
  }
}
```

Let's execute this query to get the final list of current sovereign states that have never been members of the UN.

[Tool]
Got 5 rows and 1 column:
| ?country                                     |
| -------------------------------------------- |
| First Republic of Seychelles (wd:Q129619467) |
| Lechia (wd:Q17050654)                        |
| French Fifth Republic (wd:Q200686)           |
| Palestine (wd:Q219060)                       |
| Vatican City (wd:Q237)                       |

[Assistant]
It seems that the query is still returning historical entities and regions. Let's further refine the query to ensure we only get current sovereign states. We can use the property `wdt:P31` (instance of) with the value `wd:Q3624078` (sovereign state) and also check for the property `wdt:P297` (ISO 3166-1 alpha-2 code) to ensure we are only considering current recognized countries.

Here is the updated SPARQL query:

```sparql
SELECT ?country
WHERE {
  ?country wdt:P31 wd:Q3624078.
  ?country wdt:P297 ?isoCode.
  MINUS {
    ?country wdt:P463 wd:Q1065.
  }
}
```

Let's execute this query to get the final list of current sovereign states that have never been members of the UN.

[Tool]
Got 2 rows and 1 column:
| ?country               |
| ---------------------- |
| Palestine (wd:Q219060) |
| Vatican City (wd:Q237) |

[Assistant]
The final SPARQL query has returned 2 current sovereign states that have never been members of the UN: Palestine and Vatican City.

Therefore, the answer to the question "How many countries have never been members of the UN?" is 2.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?country
WHERE {
  ?country wdt:P31 wd:Q3624078.
  ?country wdt:P297 ?isoCode.
  MINUS {
    ?country wdt:P463 wd:Q1065.
  }
}
```

Answer: 2 countries have never been members of the UN.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?author WHERE {
  wd:Q76641 wdt:P800 wd:Q315296 .
  BIND( wd:Q76641 AS ?author )
}

Felix Klein

[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 wrote the Erlangen program?

[Assistant] To answer the question "Who wrote the Erlangen program?", we need to identify the entity representing the Erlangen program and then find out who authored it. Let's start by searching for the entity "Erlangen program" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Erlangen program (wd:Q315296): research program on the symmetries of geometry
2. computer program, also known as program, software program (wd:Q40056): sequence of instructions written in programming language to perform a specified task with a computer
3. Erlangen, also known as Medical Valley (wd:Q3126): city in Bavaria, Germany
4. project, also known as effort, program, programme (wd:Q170584): collaborative enterprise, frequently involving research or design, that is carefully planned to achieve a particular aim
5. plan, also known as plans, program, programme (wd:Q1371819): outline of a strategy for achievement of an objective
6. programme, also known as program (wd:Q1508646): informational booklet given out before a live event
7. The Program, also known as Icon, Program (wd:Q15615185): 2015 film
8. educational program, also known as programme, program, educational programme (wd:Q5341296): program written by the institution of education which determines the learning progress of individuals
9. Erlangen, also known as Erlangen station (wd:Q800737): railway halt in the urban district of Erlangen, Middle Franconia, Germany
10. The Program, also known as Program (wd:Q826289): 1993 film by David S. Ward

[Assistant]
The top result for "Erlangen program" is `wd:Q315296`, which describes it as a research program on the symmetries of geometry. This seems to be the correct entity. Next, we need to find the author of this program. We will look for the property that indicates the author or creator of the program.

Let's search for properties related to "author" or "creator" for the entity `wd:Q315296`.

[Tool]
Top 10 property alternatives:
1. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as p/wdtn/wdt): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)
2. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
3. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
4. Treccani's Enciclopedia della Matematica ID, also known as Enciclopedia della Matematica ID (wd:P9621 as p/wdt): identifier for a topic in Treccani's Enciclopedia della Matematica, an Italian encyclopedia regarding mathematics
5. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as p/wdt): identifier for an article in the online version of Encyclopædia Britannica
6. ProofWiki ID, also known as Proof Wiki ID (wd:P6781 as p/wdt): identifier for a ProofWiki article
7. Encyclopedia of China (Third Edition) ID, also known as Encyclopedia of China ID (Third Edition) (wd:P10565 as p/wdt): identifier for an article in the online version of Encyclopedia of China (Third Edition)
8. Lex ID, also known as Den Store Danske ID, DSD ID (wd:P8313 as p/wdt): identifier of an article in the online encyclopedia.lex.dk

No other items found

[Assistant]
It appears that the search for properties related to "author" or "creator" did not yield any relevant results for the entity `wd:Q315296`. Let's try a broader search for properties related to "author" or "creator" in general and see if we can find a suitable property.

We will use the `search_property` function to find properties related to "author" or "creator".

[Tool]
Top 10 property alternatives:
1. theorized by, also known as author, supported by, suggested by, proposer, proposed by (wd:P8403 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): subject who suggested or proposed this concept or immaterial invention
2. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): author of song lyrics, author
3. author, also known as writer, written by, poet, playwright, maker (wd:P50 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
4. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): notable scientific, artistic or literary work, or other work of significance among subject's works
5. author given names, also known as given name, given names, first name, author first names, author first name (wd:P9687 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): qualifier for string representation of given or secondary sortin...presented in a bibliographic reference file (for example BibTeX), given name
6. used by, also known as armiger, user, played by, of (wd:P1535 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): item or concept that makes use of the subject (use sub-properties when appropriate)
7. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): person, profession, organization or entity that operates the equipment, facility, or service, used by
8. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): maker of this creative work or other object (where no more specific property exists)
9. author last names, also known as author last name, surnames, surname, last names, last name (wd:P9688 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): qualifier to provide string representation of family or primary ...presented in a bibliographic reference file (for example BibTeX), family name
10. object named as, also known as original wording, place name string, printed as, reference wording, [sic] (wd:P1932 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): use as qualifier to indicate how the object's value was given in the source, name

[Assistant]
From the search results, the most relevant property for identifying the author of a work is `wd:P50`, which stands for "author" or "writer." Let's use this property to find the author of the Erlangen program.

We will execute a SPARQL query to find the author of the Erlangen program (`wd:Q315296`).

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the property `wd:P50` did not return any results for the Erlangen program. This might mean that the author is not directly linked using this property. Let's try another property that might be more appropriate, such as `wd:P170`, which stands for "creator."

We will execute a SPARQL query to find the creator of the Erlangen program using `wd:P170`.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that the property `wd:P170` also did not return any results for the Erlangen program. This suggests that the author or creator of the Erlangen program might not be directly linked using these common properties.

Let's try a different approach by looking at the statements and qualifiers associated with the Erlangen program to see if we can find any information about its authorship. We will list the triples for the entity `wd:Q315296` to get more context.

[Tool]
Got 123 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                                                | object                                         |
| ----------------------------- | ------------------------------------------------------- | ---------------------------------------------- |
| Erlangen program (wd:Q315296) | instance of (wdt:P31)                                   | research (wd:Q42240)                           |
| Erlangen program (wd:Q315296) | Freebase ID (wdt:P646)                                  | /m/01k8tb                                      |
| Erlangen program (wd:Q315296) | Microsoft Academic ID (wdtn:P6366)                      | <https://makg.org/entity/111593780>            |
| Erlangen program (wd:Q315296) | Encyclopædia Britannica Online ID (wdt:P1417)           | topic/Erlanger-program                         |
| Erlangen program (wd:Q315296) | Lex ID (wdt:P8313)                                      | Erlangen-programmet                            |
| Erlangen program (wd:Q315296) | Encyclopedia of China (Third Edition) ID (wdt:P10565)   | 318393                                         |
| Erlangen program (wd:Q315296) | nLab ID (wdt:P4215)                                     | Erlangen program                               |
| Erlangen program (wd:Q315296) | ProofWiki ID (wdt:P6781)                                | Definition:Erlangen_Program                    |
| Erlangen program (wd:Q315296) | Treccani's Enciclopedia della Matematica ID (wdt:P9621) | programma-di-erlangen                          |
| Erlangen program (wd:Q315296) | schema:description                                      | research program on the symmetries of geometry |
| ...                           | ...                                                     | ...                                            |

[Assistant]
The list of triples for the Erlangen program does not include any direct information about its author or creator. However, we can see that it is described as a research program on the symmetries of geometry. Given the nature of the program, it is likely that the author is a well-known mathematician.

Let's try a more targeted search by looking for the author of the Erlangen program in the context of mathematical works. We will search for the author of the Erlangen program using the property `wd:P50` (author) and see if we can find any related entities.

We will execute a SPARQL query to find the author of the Erlangen program, including any related works or publications.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the Erlangen program is not directly linked to any works or publications that have an author listed. This suggests that the authorship information might be stored differently or might not be directly linked to the program itself.

Given the historical context, the Erlangen program is a well-known mathematical work, and it is often attributed to Felix Klein. Let's search for Felix Klein and see if he is linked to the Erlangen program.

We will search for the entity "Felix Klein" in Wikidata and then check if he is associated with the Erlangen program.

[Tool]
Top 10 entity alternatives:
1. Felix Klein, also known as Felix Christian Klein, F. Klein, Christian Felix Klein (wd:Q76641): German mathematician, author of the Erlangen Program (1849-1925), historian of mathematics, university teacher, mathematician, politician, publisher
2. Félix Klein (wd:Q16750728): Catholic priest, French priest
3. Felix Klein (wd:Q52062894): diplomat, jurist
4. Felix Klein (wd:Q106618632): photograph by Georg Brokesch
5. Felix Klein (wd:Q120614781): German film producer, film producer
6. Felix Klein (wd:Q27526592): chess player
7. Felix Klein (wd:Q95319364)
8. Felix Klein, also known as F. Klein (wd:Q58181951): researcher, ORCID id # 0000-0002-3680-4735, researcher
9. Félix Klein (wd:Q133262954): Holocaust victim
10. Felix Klein Prize (wd:Q1403571)

[Assistant]
The top result for "Felix Klein" is `wd:Q76641`, which describes him as a German mathematician and the author of the Erlangen Program. This seems to be the correct entity.

Next, we will verify if Felix Klein is indeed associated with the Erlangen program by checking if there is a direct link between `wd:Q315296` (Erlangen program) and `wd:Q76641` (Felix Klein).

We will execute a SPARQL query to confirm this association.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that there is no direct link between the Erlangen program (`wd:Q315296`) and Felix Klein (`wd:Q76641`) using the `wd:P50` (author) property. However, given the historical context and the well-known fact that Felix Klein is the author of the Erlangen program, it is likely that this information is stored in a different way.

Let's try a more general approach by looking for any statements that link Felix Klein to the Erlangen program. We will execute a SPARQL query to find any relationships between Felix Klein and the Erlangen program.

[Tool]
Got 1 row and 2 columns:
| ?property               | ?value                        |
| ----------------------- | ----------------------------- |
| notable work (wdt:P800) | Erlangen program (wd:Q315296) |

[Assistant]
The SPARQL query returned a result indicating that Felix Klein (`wd:Q76641`) has the Erlangen program (`wd:Q315296`) as a notable work (`wdt:P800`). This confirms that Felix Klein is indeed the author of the Erlangen program.

Therefore, the answer to the question "Who wrote the Erlangen program?" is Felix Klein.

Here is the final SPARQL query and answer:

```sparql
SELECT ?author WHERE {
  wd:Q76641 wdt:P800 wd:Q315296 .
  BIND(wd:Q76641 AS ?author)
}
```

Answer: Felix Klein

Let's finalize this with the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?character ) AS ?count ) WHERE {
  ?character wdt:P1080 [] ; wdt:P21 wd:Q6581072 ; wdt:P520 wd:Q12791 .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 16     |

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

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

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

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

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

[User] How many fictional female swordfighters are there?

[Assistant]
To answer this question, we need to identify the relevant entities and properties in the knowledge graph. We are looking for fictional characters who are female and are swordfighters. Let's start by searching for the relevant properties and entities:

1. Search for the property that indicates a character is fictional.
2. Search for the property that indicates the gender of a character.
3. Search for the property that indicates a character is a swordfighter.
4. Combine these properties to form a SPARQL query to count the number of fictional female swordfighters.

Let's begin with the first step.

[Tool]
Top 10 property alternatives:
1. fictional or mythical analog of, also known as fictionalisation of, mythical analog of, fictional version of, fictionalization of, fictional analog of (wd:P1074 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): used to link an entity or class of entities appearing in a creat...with the analogous entity or class of entities in the real world, inspired by
2. from narrative universe, also known as from narrative, in continuity, from universe, in cycle, in world of (wd:P1080 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): subject's fictional entity is in the object narrative. See also P1441 (present in work) and P1445 (fictional universe described in), part of
3. fictional universe described in (wd:P1445 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): to link a fictional universe with a work that describes it: <universe> "described in the work:" <work>
4. personality trait of fictional character, also known as personality trait, personality trait of fictitious character, personal quality of fictional character, fictitious character personality trait, personal quality of fictitious character (wd:P9652 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): particular personality trait which applies to this fictional character
5. takes place in fictional universe, also known as universe featured, described fictional universe, universe described, set in fictional universe, fictional universe described (wd:P1434 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): the subject is a work describing a fictional universe, i.e. whose plot occurs in this universe
6. Fantastic Fiction author ID, also known as Fantastic Fiction ID (wd:P5408 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): identifier for an author on the Fantastic Fiction website
7. simulates, also known as imitates, simulated, simulate, imitated, imitate (wd:P12328 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): item simulated, imitated, or made to appear real by this item
8. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
9. form of creative work, also known as work type, work form, type of work, artform, type of reference work (wd:P7937 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): structure of a creative work
10. uses, also known as uses trope, used, using, wielded, wields (wd:P2283 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): item or concept used by the subject or in the operation (see also instrument [P1303] and armament [P520])

[Assistant]
From the search results, the property `wdt:P1080` (from narrative universe) seems to be the most relevant for indicating that a character is fictional. However, it might not be the only property used to indicate this. Let's also consider `wdt:P1445` (fictional universe described in) and `wdt:P1074` (fictional or mythical analog of).

Next, let's search for the property that indicates the gender of a character.

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): 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 pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): 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 pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): 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 pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): 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 pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): 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 pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): 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 pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): equivalent name (with respect to the meaning of the name) in the...n of a female first name. Add primarily the closest matching one

[Assistant]
The property `wdt:P21` (sex or gender) is the most relevant for indicating the gender of a character.

Next, let's search for the property that indicates a character is a swordfighter.

[Tool]
Top 10 property alternatives:
1. International Fencing Federation fencer ID, also known as Fédération Internationale d'Escrime ID, FIE fencer ID, FIE ID, FIE identifier (wd:P2423 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): Identifier in the database of all fencers holding an internation...al Fencing Federation (FIE: Fédération Internationale d'Escrime)
2. Russian Fencing Federation fencer ID, also known as FFR fencer ID, Rusfencing.ru (wd:P7092 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): Russian Fencing Federation identifier
3. conflict, also known as war, theatre (military), theater (military), participated in conflict, military conflict (wd:P607 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): battles, wars or other military engagements in which the person or item participated, participant in
4. European Fencing Confederation fencer ID, also known as EFC fencer ID, Eurofencing fencer ID (wd:P4475 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): identifier on the European Fencing Confederation website
5. armament, also known as armed with, ship armament, weapon, wields (wd:P520 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): equippable weapon item for the subject, has facility
6. dan/kyu rank, also known as go rank, wushu rank, shogi rank, renju rank, kendo rank (wd:P468 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): rank system used in several board games (e.g. go, shogi, renju), martial arts (e.g. judo, kendo, wushu) and some other games
7. inverse property, also known as property opposite of, property inverse, opposite property, opponent, inverse of (wd:P1696 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): links a property to its inverse property (which relates the subject and object in reverse order)
8. enemy, also known as opponent, rival, archvillain, archrival, archnemesis (wd:P7047 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): opponent character or group of this fictive character or group, significant person
9. perpetrator, also known as robber, perpetrators, perpetrated by, perp, offender (wd:P8031 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): person or organization who carried out this harmful, illegal, or immoral act, participant
10. name of the character role, also known as character named as, role named as, role name, name of the role, name of the character (wd:P4633 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): name by which a character role is recorded in a database or ment...ably a specific performance of a theatrical production of a play, name

[Assistant]
The property `wdt:P520` (armament) is the most relevant for indicating that a character wields a sword. However, this property is more general and can include other weapons as well. To specifically identify swordfighters, we can look for the object "sword" or "swordfighter" in the context of this property.

Let's search for the object "sword" to see if it is used in the context of the `wdt:P520` property.

[Tool]
Top 10 entity alternatives:
1. sword, also known as Swords (wd:Q12791): bladed weapon longer than a knife or dagger
2. Double-edged sword, also known as Jian, sword (wd:Q11396047): sword with double sharp sides
3. sword, also known as one-handed sword (wd:Q107263658): fictional weapon type in Genshin Impact
4. katana, also known as Nihonto, samurai sword, single-edged sword (wd:Q172736): Japanese sword, that was used by samurai
5. lightsaber, also known as laser sword, lightsabers, lightsabre (wd:Q19873): type of fictional weapon in the Star Wars franchise
6. Fairey Swordfish, also known as Swordfish (wd:Q674079): 1934 carrier-based torpedo bomber family by Fairey Aviation
7. two-handed sword, also known as Zweihänder (wd:Q64894): weapon
8. Japanese sword, also known as Nihontō (wd:Q1768697): traditionally made sword from Japan
9. small sword, also known as court sword, dress sword, épée de cour, smallsword (wd:Q23954892): light one-handed sword designed for thrusting
10. short sword, also known as long dagger (wd:Q18204139): sword with blade between 40 and 80 centimetres

No other items found

No literal items found

[Assistant]
The search results show that "sword" (wd:Q12791) is the most relevant object for the `wdt:P520` property. Now we can construct a SPARQL query to count the number of fictional female characters who wield a sword.

We will use the properties `wdt:P1080` (from narrative universe) to ensure the character is fictional, `wdt:P21` (sex or gender) to ensure the character is female, and `wdt:P520` (armament) to ensure the character wields a sword.

Let's write and execute the SPARQL query.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 16     |

[Assistant]
The SPARQL query returned a count of 16 fictional female swordfighters.

Here is the final SPARQL query and the answer:

```sparql
SELECT (COUNT(?character) AS ?count)
WHERE {
  ?character wdt:P1080 [] ;
             wdt:P21 wd:Q6581072 ;
             wdt:P520 wd:Q12791 .
}
```

The answer to the question "How many fictional female swordfighters are there?" is 16.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?openingDate WHERE {
  wd:Q71719 wdt:P1619 ?openingDate .
}

The Hollywood Walk of Fame opened in the year 1960.

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

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

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

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

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

[User] In what year did the Hollywood Walk of Fame open?

[Assistant]
To find out when the Hollywood Walk of Fame opened, we need to identify the entity representing the Hollywood Walk of Fame and then look for a property that indicates its opening date or establishment year.

First, let's search for the entity "Hollywood Walk of Fame" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Hollywood Walk of Fame, also known as Walk of Fame (wd:Q71719): more than 2,700 five-pointed terrazzo and brass stars embedded i...ulevard and three blocks of Vine Street in Hollywood, California
2. star on Hollywood Walk of Fame, also known as Hollywood Walk of Fame star (wd:Q17985761): award in the Hollywood Walk of Fame, Hollywood, California, United States
3. Hollywood's Rock Walk of Fame (wd:Q3139400)
4. Walk of Fame (wd:Q48673901): 2017 film by Jesse Thomas
5. Walk of Fame (wd:Q51084447): street in Saint Petersburg, Russia
6. Starr gets star; Ringo added to Hollywood Walk of Fame (wd:Q18021457): Wikinews article
7. Walk of Fame (wd:Q7962075): memorial for famous dogs in Battersea Park, London, England, UK
8. walk of fame (wd:Q47502370): sidewalk or similar construction that commemorates outstanding individuals in a particular group
9. Walk of Fame (wd:Q114476628): episode of Cupcake Wars (S2 E11)
10. Walk of Fame, also known as Wigan's Walk of Fame, Believe Square (wd:Q121879112): public walkway in Wigan, England

[Assistant]
The top result is the entity for the Hollywood Walk of Fame, which has the identifier `wd:Q71719`. Next, we need to find a property that indicates the opening date or establishment year of the Hollywood Walk of Fame. We can search for properties related to "opening" or "establishment" for this entity.

Let's search for properties related to "opening" for the entity `wd:Q71719`.

[Tool]
Top 10 property alternatives:
1. date of official opening, also known as launch date, launched, officially opened on, official opening, official opening time (wd:P1619 as p/wdt): date or point in time a place, organization, or event officially opened, start time, inception
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
3. located on street, also known as on street, street address, street, square, road (wd:P669 as p/wdt): street, road, or square, where the item is located. To add the n...perty P6375 "street address", if there is no item for the street, location, part of
4. title, also known as name, titled, page name, original title, known as (wd:P1476 as p/wdt): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
5. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
6. 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 p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
7. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p): label for the items in their official language  or their original language, name
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
9. ground level 360 degree view URL, also known as Mapillary, virtual tour URL, tour URL, street view URL, Mapy.CZ (wd:P5282 as p/wdt): URL to access a service that allows to visually navigate through images at ground level in the proximity of the item, URL
10. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL

No other items found

[Assistant]
The property `wd:P1619` (date of official opening) seems to be the most relevant for finding the opening date of the Hollywood Walk of Fame. Let's construct a SPARQL query to retrieve this information.

We will query for the date of official opening of the Hollywood Walk of Fame (`wd:Q71719`) using the property `wdt:P1619`.

```sparql
SELECT ?openingDate
WHERE {
  wd:Q71719 wdt:P1619 ?openingDate .
}
```

Let's execute this query to get the opening date.

[Tool]
Got 1 row and 1 column:
| ?openingDate         |
| -------------------- |
| 1960-01-01T00:00:00Z |

[Assistant]
The Hollywood Walk of Fame opened on January 1, 1960.

Here is the final SPARQL query and answer:

```sparql
SELECT ?openingDate
WHERE {
  wd:Q71719 wdt:P1619 ?openingDate .
}
```

Answer: The Hollywood Walk of Fame opened in the year 1960.

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

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?language ) AS ?numberOfLanguages ) WHERE {
  wd:Q843 wdt:P37 ?language .
}

Got 1 row and 1 column:
| ?numberOfLanguages |
| ------------------ |
| 2                  |

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

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

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

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

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

[User] How many official languages has Pakistan ?

[Assistant]
To answer the question about the number of official languages in Pakistan, we need to identify the relevant entities and properties in the knowledge graph. Let's start by searching for the entity representing Pakistan and then look for properties related to official languages.

First, I will search for the entity "Pakistan" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Pakistan, also known as Islamic Republic of Pakistan, PAK, pk, Republic of Pakistan (wd:Q843): sovereign state in South Asia
2. Dominion of Pakistan, also known as Pakistan (wd:Q2006542): period of Pakistani history between 1947 to 1956
3. West Pakistan, also known as Pakistan (wd:Q2342822): Western Wing of Pakistan between 1947–1970
4. Pakistan (wd:Q4121082): village in Purnia district, Bihar, India
5. Urdu 1, also known as Pakistan (wd:Q2786023): Pakistani Urdu-language television network
6. Pakistan (wd:Q57206806): village in Cameroon
7. Pakistan (wd:Q122963846): 2023 single by D-Block Europe and Clavish
8. Khan Bela, also known as Liaqatpur, Pakistan, Rahim Yar Khan (wd:Q31308479): Khan Bela is a city in Rahim Yar Khan District, Punjab, Pakistan...is {{cvt|90|km|mile}} from Khan Bela and Bahawalpur is {{cvt|105
9. Pakistan (wd:Q87704056): scientific article published on 01 November 1987
10. Pakistan (wd:Q99573810): scientific article published on 01 October 2020

[Assistant]
The top result for "Pakistan" is the entity representing the Islamic Republic of Pakistan (wd:Q843). Now, I will search for properties related to official languages to find out how many official languages Pakistan has.

I will search for properties related to "official language" for the entity "Pakistan".

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as p/wdt): language designated as official by this item, language used
2. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
3. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as p/wdt): language widely used (spoken or written) in this place or at this event or organisation
4. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as p/wdt): official name of the subject in its official language(s), name
5. official religion, also known as established religion, state religion (wd:P3075 as p/wdt): official religion in this administrative entity
6. basic form of government, also known as form of government, government, type of government (wd:P122 as p/wdt): subject's government
7. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity
8. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
9. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as p/wdt): political office that is fulfilled by the head of the government of this item
10. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as p/wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

No other items found

[Assistant]
The top result for the property related to "official language" is `wd:P37`. This property indicates the language designated as official by the entity.

Now, I will construct a SPARQL query to find the number of official languages for Pakistan (wd:Q843) using the property `wdt:P37`.

Let's execute the query:

```sparql
SELECT (COUNT(?language) AS ?numberOfLanguages)
WHERE {
  wd:Q843 wdt:P37 ?language .
}
```

This query will count the number of official languages associated with Pakistan.

Executing the query now:

[Tool]
Got 1 row and 1 column:
| ?numberOfLanguages |
| ------------------ |
| 2                  |

[Assistant]
The SPARQL query returned that Pakistan has 2 official languages.

Therefore, the answer to the question "How many official languages has Pakistan?" is:

**2**

Final SPARQL query:
```sparql
SELECT (COUNT(?language) AS ?numberOfLanguages)
WHERE {
  wd:Q843 wdt:P37 ?language .
}
```

Final answer:
2

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?creator ?creatorLabel WHERE {
  wd:Q16889037 wdt:P170 ?creator .
  OPTIONAL {
    ?creator rdfs:label ?creatorLabel .
    FILTER ( LANG( ?creatorLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| ?creator                     | ?creatorLabel  |
| ---------------------------- | -------------- |
| Tina Fey (wd:Q14540)         | Tina Fey       |
| Robert Carlock (wd:Q7342763) | Robert Carlock |

The creators of Unbreakable Kimmy Schmidt are Tina Fey and Robert Carlock.

[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 was the creator of Unbreakable Kimmy Schmidt ?

[Assistant] To find the creator of Unbreakable Kimmy Schmidt, we need to identify the entity for the TV show and then look for the property that indicates the creator(s). Let's start by searching for the entity "Unbreakable Kimmy Schmidt" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Unbreakable Kimmy Schmidt (wd:Q16889037): American comedy streaming television series
2. Unbreakable Kimmy Schmidt, season 1 (wd:Q21186375): season of television series
3. Unbreakable Kimmy Schmidt, season 4 (wd:Q54847377): season of television series
4. Unbreakable Kimmy Schmidt, season 3 (wd:Q30158232): season of television series
5. Unbreakable Kimmy Schmidt, season 2 (wd:Q25093973): season of television series
6. Unbreakable Kimmy Schmidt theme song (wd:Q28787990): song
7. Unbreakable Kimmy Schmidt: Kimmy vs. the Reverend, also known as Kimmy vs. the Reverend, Unbreakable Kimmy Schmidt: Kimmy vs the Reverend (wd:Q98708760): 2020 interactive film directed by Claire Scanlon
8. Kimmy Schmidt, also known as Kimberly Cougar Schmidt, Kimberly Schmidt (wd:Q23017207): fictional Protagonist of Unbreakable Kimmy Schmidt
9. Käthe Kollwitz, also known as Kėte Kolʹvit︠s︡, Käthe Schmidt Kollwitz, Kʻo-le-hui-chih, Kathe Schmidt, Käthe Schmidt (wd:Q142472): German printmaker and sculptor (1867–1945), architectural draftsperson, graphic artist, autobiographer, poster artist, draftsperson, lithographer, illustrator, printmaker, sculptor, designer, painter, artist
10. Unbreakable (wd:Q650613): 2000 film directed by M. Night Shyamalan

[Assistant] The top result is the entity for the TV show "Unbreakable Kimmy Schmidt" (wd:Q16889037). Now, let's find the property that indicates the creator(s) of the TV show. We can search for properties related to "creator" for this specific entity.

[Tool]
Top 10 property alternatives:
1. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as p/wdt): maker of this creative work or other object (where no more specific property exists)
2. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
3. composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as p/wdt): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator
4. original language of film or TV show, also known as media language, original language, language of the original work, created on language (wd:P364 as p/wdt): language in which a film or a performance work was originally cr... works and songs; use P407 ("language of work or name") instead., language of work or name
5. producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as p/wdt): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. title, also known as name, titled, page name, original title, known as (wd:P1476 as p/wdt): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
8. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
9. start time, also known as start date, since, valid, join time, joined (wd:P580 as p/wdt): time an entity begins to exist or a statement starts being valid, point in time
10. MusicBrainz artist ID, also known as MB artist ID, MBID artist (wd:P434 as p/wdtn/wdt): identifier for an artist in the MusicBrainz open music encyclopedia

No other items found

[Assistant]
The property "creator" (wd:P170) seems to be the most relevant for identifying the creator(s) of the TV show. Let's construct a SPARQL query to retrieve the creator(s) of "Unbreakable Kimmy Schmidt" (wd:Q16889037).

Here is the initial SPARQL query:

```sparql
SELECT ?creator WHERE {
  wd:Q16889037 wdt:P170 ?creator .
}
```

Let's execute this query to see the results.

[Tool]
Got 2 rows and 1 column:
| ?creator                     |
| ---------------------------- |
| Tina Fey (wd:Q14540)         |
| Robert Carlock (wd:Q7342763) |

[Assistant]
The creators of "Unbreakable Kimmy Schmidt" are Tina Fey (wd:Q14540) and Robert Carlock (wd:Q7342763).

To provide a more complete answer, we can include the labels of the creators in the SPARQL query. Here is the refined query:

```sparql
SELECT ?creator ?creatorLabel WHERE {
  wd:Q16889037 wdt:P170 ?creator .
  OPTIONAL { ?creator rdfs:label ?creatorLabel . FILTER(LANG(?creatorLabel) = "en") }
}
```

Let's execute this refined query to get the labels as well.

[Tool]
Got 2 rows and 2 columns:
| ?creator                     | ?creatorLabel  |
| ---------------------------- | -------------- |
| Tina Fey (wd:Q14540)         | Tina Fey       |
| Robert Carlock (wd:Q7342763) | Robert Carlock |

[Assistant]
The creators of "Unbreakable Kimmy Schmidt" are Tina Fey and Robert Carlock.

Here is the final SPARQL query and answer:

```sparql
SELECT ?creator ?creatorLabel WHERE {
  wd:Q16889037 wdt:P170 ?creator .
  OPTIONAL { ?creator rdfs:label ?creatorLabel . FILTER(LANG(?creatorLabel) = "en") }
}
```

Answer: The creators of "Unbreakable Kimmy Schmidt" are Tina Fey and Robert Carlock.

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

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?movie ) AS ?count ) WHERE {
  ?movie wdt:P57 wd:Q8006 .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 32     |

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

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

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

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

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

[User] How many movies were directed by Akira Kurosawa ?

[Assistant]
To answer the question "How many movies were directed by Akira Kurosawa?", we need to:

1. Identify the entity for Akira Kurosawa.
2. Identify the property for "directed by".
3. Count the number of movies that Akira Kurosawa directed.

Let's start by searching for the entity for Akira Kurosawa.

[Tool]
Top 10 entity alternatives:
1. Akira Kurosawa, also known as Kurosawa Akira, Kurosawa (wd:Q8006): Japanese filmmaker (1910–1998), film producer, film director, screenwriter, film editor, producer, director, painter, writer
2. Akira Kurosawa (wd:Q95472952): former JGSDF officer, military officer
3. Akira Kurosawa (wd:Q110408919): fictional character from the television series The Simpsons, waiter, sensei
4. Akira Kurosawa bibliography (wd:Q17003557)
5. Ak: Akira Kurosawa (wd:Q123305558): 1985 film by Chris Marke
6. Dreams, also known as Akira Kurosawa's Dreams (wd:Q418809): 1990 film by Akira Kurosawa, Ishirō Honda
7. Criticism of Akira Kurosawa (wd:Q5186786): negative criticisms of the Japanese film director
8. filmmaking technique of Akira Kurosawa (wd:Q30154500)
9. The Films of Akira Kurosawa (wd:Q124077496)
10. Akira Kurosawa’s Natural Story (wd:Q119422666)

[Assistant] The top result for Akira Kurosawa is `wd:Q8006`, which is the correct entity for the Japanese filmmaker. Next, we need to identify the property for "directed by". Let's search for this property.

[Tool]
Top 10 property alternatives:
1. editor-in-chief, also known as lead editor, managing editor, executive editor, editor in chief, directed by (wd:P5769 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): a publication's editorial leader who has final responsibility fo...publishing articles or books in collections or periodical papers
2. director, also known as film director, movie director, game director, directed by (wd:P57 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator
3. position held by head of the organization, also known as position held by head of the organisation, secretary's position, president's position, position held by head of the organization, office held by head of the organisation (wd:P2388 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): position of the head of this item
4. director / manager, also known as leader, manager, manager/director, managing director, Officer-in-Charge (wd:P1037 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): person who manages any kind of group, significant person
5. director of photography, also known as cinematographer, DOP (wd:P344 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): person responsible for the framing, lighting, and filtration of the subject work, film crew member
6. screenwriter, also known as story by, teleplay by, video game writer, writer (of screenplays), writing credits (wd:P58 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): person(s) who wrote the script for subject item, film crew member, author
7. produced by, also known as secreted by (wd:P2849 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): links a class of biological features (such as a biochemical compound) with another class of biological entities known to produce it, has immediate cause
8. manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): (main or final) manufacturer or producer of this product
9. fabrication method, also known as process used, method of cooking, preparation method, obtained by, method used (wd:P2079 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): method, process or technique used to grow, cook, weave, build, assemble, manufacture the item, uses
10. producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as pr/pqn/prn/pqv/prv/p/psv/wdtn/ps/wdt/psn/pq): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]

[Assistant]
The property for "directed by" is `wd:P57`. Now, we can construct a SPARQL query to count the number of movies directed by Akira Kurosawa (`wd:Q8006`).

Let's write and execute the SPARQL query to get the count.

```sparql
SELECT (COUNT(?movie) AS ?count)
WHERE {
  ?movie wdt:P57 wd:Q8006 .
}
```

This query will count the number of movies where Akira Kurosawa is listed as the director.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 32     |

[Assistant]
The SPARQL query returned a count of 32 movies directed by Akira Kurosawa.

Therefore, the answer to the question "How many movies were directed by Akira Kurosawa?" is 32.

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(?movie) AS ?count)
WHERE {
  ?movie wdt:P57 wd:Q8006 .
}
```

Answer: 32

[Tool] Stopped generation process