PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?politician ?spouse WHERE {
  ?politician wdt:P106 wd:Q82955 .
  ?politician wdt:P26 ?spouse .
  ?spouse wdt:P27 wd:Q183 .
}
LIMIT 10

Got 10 rows and 2 columns:
| ?politician                                     | ?spouse                                             |
| ----------------------------------------------- | --------------------------------------------------- |
| Eberhard Gothein (wd:Q100765)                   | Marie-Luise Gothein (wd:Q97309)                     |
| Hans-Peter Bartels (wd:Q101192)                 | Susanne Gaschke (wd:Q104875)                        |
| Karl Trimborn (wd:Q101327)                      | Jeanne Trimborn (wd:Q1686020)                       |
| Siegfried Balleis (wd:Q101881)                  | Angelika Balleis (wd:Q41543230)                     |
| Joachim von Ribbentrop (wd:Q101886)             | Annelies von Ribbentrop (wd:Q15531167)              |
| Joseph-Ernst Graf Fugger von Glött (wd:Q101974) | Stefanie van Hohenzollern-Sigmaringen (wd:Q1936156) |
| Oliver Krischer (wd:Q103710)                    | Sybille Haußmann (wd:Q1684950)                      |
| Gustav Stresemann (wd:Q103955)                  | Käte Stresemann (wd:Q434469)                        |
| Elli Schmidt (wd:Q104088)                       | Anton Ackermann (wd:Q69198)                         |
| Monika Griefahn (wd:Q104150)                    | Michael Braungart (wd:Q69643)                       |

The following politicians are married to Germans:
1. Eberhard Gothein (wd:Q100765) - Married to Marie-Luise Gothein (wd:Q97309)
2. Hans-Peter Bartels (wd:Q101192) - Married to Susanne Gaschke (wd:Q104875)
3. Karl Trimborn (wd:Q101327) - Married to Jeanne Trimborn (wd:Q1686020)
4. Siegfried Balleis (wd:Q101881) - Married to Angelika Balleis (wd:Q41543230)
5. Joachim von Ribbentrop (wd:Q101886) - Married to Annelies von Ribbentrop (wd:Q15531167)
6. Joseph-Ernst Graf Fugger von Glött (wd:Q101974) - Married to Stefanie van Hohenzollern-Sigmaringen (wd:Q1936156)
7. Oliver Krischer (wd:Q103710) - Married to Sybille Haußmann (wd:Q1684950)
8. Gustav Stresemann (wd:Q103955) - Married to Käte Stresemann (wd:Q434469)
9. Elli Schmidt (wd:Q104088) - Married to Anton Ackermann (wd:Q69198)
10. Monika Griefahn (wd:Q104150) - Married to Michael Braungart (wd:Q69643)

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

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

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

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

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

[User] Which politicians were married to a German?

[Assistant]
To answer this question, we need to identify the following elements:

1. Politicians: We can use the occupation or profession property to find people who are politicians.
2. Marriage: We need to find the property that indicates a person's spouse.
3. Germans: We need to find a way to filter out the spouses who are German, which might involve their nationality or country of origin.

Let's start by searching for the relevant properties for occupation and spouse.

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

[Tool]
Top 10 property alternatives:
1. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
2. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
3. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
4. married name, also known as full name (married) (wd:P2562 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): name or surname adopted by a person upon marriage, name
5. place of marriage, also known as marriage location, wedding location, wed at, married in, married at (wd:P2842 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): location where the marriage was celebrated. Use as qualifier for property "spouse" (P26), significant place
6. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): full name of a person at birth, if different from their current, generally used name, name
7. connects with, also known as contacts, couples with, intersects at grade, links to, mates with (wd:P2789 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): item with which the item is physically connected, physically interacts with
8. companion of, also known as has astronomical companion, has companion, companion, astronomic companion of, astronomic companion (wd:P399 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): two or more astronomic bodies of the same type relating to each other
9. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
10. relation (wd:P2309 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): qualifier to define a property constraint in combination with P2...h the property "relative" is "type of kinship" (P1039), not this

[Assistant]
From the search results, we can use the following properties:
- `wdt:P106` for occupation (to find politicians).
- `wdt:P26` for spouse (to find who they are married to).
- `wdt:P27` for country of citizenship (to filter out Germans).

Now, let's construct a SPARQL query to find politicians who are married to a German.

### Step 1: Find politicians
We will first find people who are politicians.

### Step 2: Find their spouses
Next, we will find the spouses of these politicians.

### Step 3: Filter by German citizenship
Finally, we will filter the spouses to only those who are German citizens.

Let's start with the first step and find politicians.

```sparql
SELECT ?politician WHERE {
  ?politician wdt:P106 wd:Q82955.  # Politician (Q82955)
}
```

I will execute this query to see the results.

[Tool]
Got 10 rows and 1 column:
| ?politician                               |
| ----------------------------------------- |
| Joseph C. O'Mahoney (wd:Q1000051)         |
| Vasily Nebenzya (wd:Q1000053)             |
| Valentyn Symonenko (wd:Q1000061)          |
| Myron V. George (wd:Q1000070)             |
| Frank P. Coburn (wd:Q1000085)             |
| Hugh Meade Alcorn, Jr. (wd:Q1000154)      |
| Dietmar Thieser (wd:Q1000195)             |
| James P. Latta (wd:Q1000235)              |
| Wilhelm Rohwedder (wd:Q1000282)           |
| Otto Hermann von Vietinghoff (wd:Q100029) |

[Assistant]
The query successfully returned a list of politicians. Now, let's extend the query to find the spouses of these politicians.

### Step 2: Find the spouses of politicians

We will add a clause to find the spouses of the politicians.

```sparql
SELECT ?politician ?spouse WHERE {
  ?politician wdt:P106 wd:Q82955.  # Politician (Q82955)
  ?politician wdt:P26 ?spouse.     # Spouse
}
LIMIT 10
```

I will execute this query to see the results.

[Tool]
Got 10 rows and 2 columns:
| ?politician                               | ?spouse                                                                   |
| ----------------------------------------- | ------------------------------------------------------------------------- |
| Otto Hermann von Vietinghoff (wd:Q100029) | Countess Anna Ulrica of Münnich, Gräfin von Münnich (wd:Q108859253)       |
| Louis d'Eichthal (wd:Q100038758)          | Maria Amy Freeman (wd:Q100037810)                                         |
| Oluf Borch de Schouboe (wd:Q1000637)      | Frederikke Christine Dorothea von Munthe af Morgenstierne (wd:Q113367935) |
| György Festetics (wd:Q1000937)            | Eugénia Erdődy de Monyorókerék et Monoszló (wd:Q1510302)                  |
| Mahatma Gandhi (wd:Q1001)                 | Kasturba Gandhi (wd:Q264908)                                              |
| James Ewing (wd:Q100148045)               | Jane Tucker Crawford (wd:Q119983019)                                      |
| Nicholas Cabell Sr (wd:Q100148299)        | Hannah Carrington Cabell (wd:Q99306322)                                   |
| Mahamadou Diarra (wd:Q100152669)          | Diarra Afoussatou Thiero (wd:Q85984158)                                   |
| Ahmed El Madani Diallo (wd:Q100152865)    | Fatoumata Dialo (wd:Q85985300)                                            |
| József Fischer (wd:Q1001705)              | Eszter Pécsi (wd:Q1242788)                                                |

[Assistant]
The query successfully returned a list of politicians and their spouses. Now, let's filter the results to include only those spouses who are German citizens.

### Step 3: Filter by German citizenship

We will add a clause to filter the spouses to only those who have German citizenship.

```sparql
SELECT ?politician ?spouse WHERE {
  ?politician wdt:P106 wd:Q82955.  # Politician (Q82955)
  ?politician wdt:P26 ?spouse.     # Spouse
  ?spouse wdt:P27 wd:Q183.         # German citizen (Q183)
}
LIMIT 10
```

I will execute this query to see the results.

[Tool]
Got 10 rows and 2 columns:
| ?politician                                     | ?spouse                                             |
| ----------------------------------------------- | --------------------------------------------------- |
| Eberhard Gothein (wd:Q100765)                   | Marie-Luise Gothein (wd:Q97309)                     |
| Hans-Peter Bartels (wd:Q101192)                 | Susanne Gaschke (wd:Q104875)                        |
| Karl Trimborn (wd:Q101327)                      | Jeanne Trimborn (wd:Q1686020)                       |
| Siegfried Balleis (wd:Q101881)                  | Angelika Balleis (wd:Q41543230)                     |
| Joachim von Ribbentrop (wd:Q101886)             | Annelies von Ribbentrop (wd:Q15531167)              |
| Joseph-Ernst Graf Fugger von Glött (wd:Q101974) | Stefanie van Hohenzollern-Sigmaringen (wd:Q1936156) |
| Oliver Krischer (wd:Q103710)                    | Sybille Haußmann (wd:Q1684950)                      |
| Gustav Stresemann (wd:Q103955)                  | Käte Stresemann (wd:Q434469)                        |
| Elli Schmidt (wd:Q104088)                       | Anton Ackermann (wd:Q69198)                         |
| Monika Griefahn (wd:Q104150)                    | Michael Braungart (wd:Q69643)                       |

[Assistant]
The query successfully returned a list of politicians who are married to Germans. Here are the results:

1. **Eberhard Gothein** (wd:Q100765) - Married to **Marie-Luise Gothein** (wd:Q97309)
2. **Hans-Peter Bartels** (wd:Q101192) - Married to **Susanne Gaschke** (wd:Q104875)
3. **Karl Trimborn** (wd:Q101327) - Married to **Jeanne Trimborn** (wd:Q1686020)
4. **Siegfried Balleis** (wd:Q101881) - Married to **Angelika Balleis** (wd:Q41543230)
5. **Joachim von Ribbentrop** (wd:Q101886) - Married to **Annelies von Ribbentrop** (wd:Q15531167)
6. **Joseph-Ernst Graf Fugger von Glött** (wd:Q101974) - Married to **Stefanie van Hohenzollern-Sigmaringen** (wd:Q1936156)
7. **Oliver Krischer** (wd:Q103710) - Married to **Sybille Haußmann** (wd:Q1684950)
8. **Gustav Stresemann** (wd:Q103955) - Married to **Käte Stresemann** (wd:Q434469)
9. **Elli Schmidt** (wd:Q104088) - Married to **Anton Ackermann** (wd:Q69198)
10. **Monika Griefahn** (wd:Q104150) - Married to **Michael Braungart** (wd:Q69643)

These are the politicians who are married to Germans according to the data in Wikidata.

I will now provide the final SPARQL query and the answer to the user's question.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?startDate WHERE {
  wd:Q33132 wdt:P580 ?startDate .
}

July 1, 1863

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

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

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

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

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

[User] When was the Battle of Gettysburg?

[Assistant] To answer the question about when the Battle of Gettysburg took place, we need to identify the entity for the Battle of Gettysburg and then find the date associated with it. Let's start by searching for the entity "Battle of Gettysburg" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Battle of Gettysburg (wd:Q33132): 1863 battle of the American Civil War
2. The Battle of Gettysburg, also known as Battle of Gettysburg (wd:Q3985807): 1913 film by Charles Giblyn, Thomas H. Ince
3. The Battle of Gettysburg, also known as Battle of Gettysburg (wd:Q7715862): 1955 documentary film by Herman Hoffman
4. Battle of Gettysburg order of battle (wd:Q124022501)
5. The battle of Gettysburg (wd:Q74684783): scientific article published on 01 August 1990
6. Gettysburg Confederate order of battle (wd:Q904364): 1863 American order of battle
7. Gettysburg Union order of battle (wd:Q840730)
8. Battle of Gettysburg, First Day (wd:Q841268): first day of the Battle of Gettysburg during the American Civil War
9. Battle of Gettysburg, Second Day (wd:Q905574): battle of the American Civil War
10. Battle of Gettysburg half dollar (wd:Q28104126): Background

[Assistant]
The top result for "Battle of Gettysburg" is `wd:Q33132`, which refers to the 1863 battle of the American Civil War. Now, let's find the date associated with this battle. We will look for properties related to dates, such as "start time" or "end time."

First, let's list the properties of the Battle of Gettysburg to see if we can find the relevant date information.

[Tool]
Got 318 rows and 3 columns, showing the first 10 rows below:
| subject                          | property                        | object                                                                                |
| -------------------------------- | ------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Battle of Gettysburg (wd:Q33132) | instance of (wdt:P31)           | battle (wd:Q178561)                                                                                |
| Battle of Gettysburg (wd:Q33132) | country (wdt:P17)               | United States (wd:Q30)                                                                                |
| Battle of Gettysburg (wd:Q33132) | coordinate location (wdt:P625)  | POINT(-77.225833 39.811389)                                                                                |
| Battle of Gettysburg (wd:Q33132) | Commons category (wdt:P373)     | Battle of Gettysburg                                                                                |
| Battle of Gettysburg (wd:Q33132) | image (wdt:P18)                 | <http://commons.wikimedia.org/wiki/Special:FilePath/Thure%20de%20Thulstrup%20-%20L.%20Prang%20and%20Co.%20-%20Battle%20of%20Gettysburg%20-%20Restoration%20by%20Adam%20Cuerden%20%28cropped%29.jpg> |
| Battle of Gettysburg (wd:Q33132) | part of (wdt:P361)              | Eastern Theater of the American Civil War (wd:Q749397)                                                                                |
| Battle of Gettysburg (wd:Q33132) | location (wdt:P276)             | Adams County (wd:Q351865)                                                                                |
| Battle of Gettysburg (wd:Q33132) | described by source (wdt:P1343) | Brockhaus and Efron Encyclopedic Dictionary (wd:Q602358)                                                                                |
| Battle of Gettysburg (wd:Q33132) | point in time (wdt:P585)        | 1863-07-01T00:00:00Z                                                                                |
| Battle of Gettysburg (wd:Q33132) | start time (wdt:P580)           | 1863-07-01T00:00:00Z                                                                                |
| ...                              | ...                             | ...                                                                                |

[Assistant]
From the list of properties, we can see that the Battle of Gettysburg has a "point in time" (`wdt:P585`) and a "start time" (`wdt:P580`). Both properties indicate the date of the battle as July 1, 1863.

Now, let's construct a SPARQL query to retrieve the start date of the Battle of Gettysburg.

```sparql
SELECT ?startDate
WHERE {
  wd:Q33132 wdt:P580 ?startDate .
}
```

Let's execute this query to confirm the start date.

[Tool]
Got 1 row and 1 column:
| ?startDate           |
| -------------------- |
| 1863-07-01T00:00:00Z |

[Assistant]
The SPARQL query confirms that the start date of the Battle of Gettysburg is July 1, 1863.

Therefore, the answer to the question "When was the Battle of Gettysburg?" is:

**July 1, 1863**

Here is the final SPARQL query:

```sparql
SELECT ?startDate
WHERE {
  wd:Q33132 wdt:P580 ?startDate .
}
```

And the answer:

**July 1, 1863**

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/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?book ?bookLabel WHERE {
  ?book wdt:P50 wd:Q72653 .
  OPTIONAL {
    ?book rdfs:label ?bookLabel .
    FILTER ( LANG( ?bookLabel ) = "en" )
  }
}

Got 211 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?book                                  | ?bookLabel             |
| -------------------------------------- | ---------------------- |
| wd:Q100257629                          |                        |
| Jewels (wd:Q10306884)                  | Jewels                 |
| The Promise (wd:Q10381720)             | The Promise            |
| The Sins of the Mother (wd:Q107074924) | The Sins of the Mother |
| First Sight (wd:Q107074970)            | First Sight            |
| ...                                    | ...                    |
| The Wedding (wd:Q7774042)              | The Wedding            |
| Thurston House (wd:Q7799449)           | Thurston House         |
| Toxic Bachelors (wd:Q7830354)          | Toxic Bachelors        |
| Wanderlust (wd:Q7967238)               | Wanderlust             |
| Sunset in St. Tropez (wd:Q951140)      | Sunset in St. Tropez   |

The query retrieves all books written by Danielle Steel along with their English labels.

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

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

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

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

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

[User] Give me all books written by Danielle Steel.

[Assistant] To answer this question, we need to identify the entity for Danielle Steel and then find all the books she has written. Let's start by searching for Danielle Steel in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Danielle Steel, also known as Danielle Fernandes Dominique Schülein-Steel, Danielle Fernandes Dominique Schuelein-Steel (wd:Q72653): children's writer, American writer, novelist, writer
2. Danielle Steel's Star, also known as Star (wd:Q4189382): 1993 film directed by Michael Miller
3. Changes, also known as Danielle Steel's Changes (wd:Q4994471): 1991 television film directed by Charles Jarrott
4. Secrets, also known as Danielle Steel's Secrets (wd:Q2264138): 1992 American television film by Peter H. Hunt
5. Daddy, also known as Danielle Steel's Daddy (wd:Q5207983): 1991 television film
6. Kaleidoscope, also known as Danielle Steel's Kaleidoscope (wd:Q6351961): 1990 film directed by Jud Taylor
7. Danielle Steel's 'Palomino' (wd:Q5219445): 1991 television film
8. Mixed Blessings, also known as Danielle Steel's Mixed Blessings (wd:Q6883881): 1995 American television film directed by Bethany Rooney
9. Danielle Steel's A Perfect Stranger (wd:Q5219446): 1994 TV-film by Michael Miller
10. Message from Nam, also known as Danielle Steel's 'Message from Nam' (wd:Q3492381): 1993 television film

[Assistant] The top result for Danielle Steel is the correct one (wd:Q72653). Now, let's find the property that indicates the author of a book. We can search for properties related to "author" or "written by."

[Tool]
Top 10 property alternatives:
1. theorized by, also known as author, supported by, suggested by, proposer, proposed by (wd:P8403 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): 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 psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): author of song lyrics, author
3. author, also known as writer, written by, poet, playwright, maker (wd:P50 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): 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 psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): 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 psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): 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 psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): 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 psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): 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 psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): 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 psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): 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 psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): use as qualifier to indicate how the object's value was given in the source, name

[Assistant]
The property "author" (wd:P50) seems to be the most relevant for our purpose. Now, let's construct a SPARQL query to find all books written by Danielle Steel (wd:Q72653).

We will start with a simple query to retrieve the books and their IRIs. If necessary, we can add more details later.

Here is the initial SPARQL query:

```sparql
SELECT ?book
WHERE {
  ?book wdt:P50 wd:Q72653 .
}
```

Let's execute this query to see the results.

[Tool]
Got 211 rows and 1 column, showing the first 5 and last 5 rows below:
| ?book                                  |
| -------------------------------------- |
| wd:Q100257629                          |
| Jewels (wd:Q10306884)                  |
| The Promise (wd:Q10381720)             |
| The Sins of the Mother (wd:Q107074924) |
| First Sight (wd:Q107074970)            |
| ...                                    |
| The Wedding (wd:Q7774042)              |
| Thurston House (wd:Q7799449)           |
| Toxic Bachelors (wd:Q7830354)          |
| Wanderlust (wd:Q7967238)               |
| Sunset in St. Tropez (wd:Q951140)      |

[Assistant]
The query returned 211 books written by Danielle Steel. The results include the IRIs of the books, which is what we need. However, to make the results more readable, we can optionally include the labels of the books.

Let's modify the query to include the labels of the books:

```sparql
SELECT ?book ?bookLabel
WHERE {
  ?book wdt:P50 wd:Q72653 .
  OPTIONAL { ?book rdfs:label ?bookLabel . }
}
```

Let's execute this updated query.

[Tool]
Got 891 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?book                             | ?bookLabel                        |
| --------------------------------- | --------------------------------- |
| wd:Q100257629                     | "44 شارع تشارلز"@ar               |
| Jewels (wd:Q10306884)             | Jewels                            |
| Jewels (wd:Q10306884)             | "Jewels"@ga                       |
| Jewels (wd:Q10306884)             | "Jewels"@nl                       |
| Jewels (wd:Q10306884)             | "Jewels"@pt                       |
| ...                               | ...                               |
| Sunset in St. Tropez (wd:Q951140) | "Solnedgång över Saint-Tropez"@sv |
| Sunset in St. Tropez (wd:Q951140) | Sunset in St. Tropez              |
| Sunset in St. Tropez (wd:Q951140) | "Sunset in St. Tropez"@ga         |
| Sunset in St. Tropez (wd:Q951140) | "غروب في الريفيرا الفرنسية"@ar    |
| Sunset in St. Tropez (wd:Q951140) | "सन्सेट इन सेन्ट ट्रोपेज"@ne      |

[Assistant]
The query returned 891 rows, which includes multiple labels for some books in different languages. To simplify the results, we can filter the labels to only include the English labels. This will make the output more concise and easier to read.

Let's update the query to filter for English labels:

```sparql
SELECT ?book ?bookLabel
WHERE {
  ?book wdt:P50 wd:Q72653 .
  OPTIONAL { ?book rdfs:label ?bookLabel . FILTER(LANG(?bookLabel) = "en") }
}
```

Let's execute this updated query.

[Tool]
Got 211 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?book                                  | ?bookLabel             |
| -------------------------------------- | ---------------------- |
| wd:Q100257629                          |                        |
| Jewels (wd:Q10306884)                  | Jewels                 |
| The Promise (wd:Q10381720)             | The Promise            |
| The Sins of the Mother (wd:Q107074924) | The Sins of the Mother |
| First Sight (wd:Q107074970)            | First Sight            |
| ...                                    | ...                    |
| The Wedding (wd:Q7774042)              | The Wedding            |
| Thurston House (wd:Q7799449)           | Thurston House         |
| Toxic Bachelors (wd:Q7830354)          | Toxic Bachelors        |
| Wanderlust (wd:Q7967238)               | Wanderlust             |
| Sunset in St. Tropez (wd:Q951140)      | Sunset in St. Tropez   |

[Assistant]
The query now returns 211 rows with the IRIs and English labels of the books written by Danielle Steel. The results are much more readable and concise.

Here is the final SPARQL query:

```sparql
SELECT ?book ?bookLabel
WHERE {
  ?book wdt:P50 wd:Q72653 .
  OPTIONAL { ?book rdfs:label ?bookLabel . FILTER(LANG(?bookLabel) = "en") }
}
```

This query successfully retrieves all books written by Danielle Steel along with their English labels.

I will now provide the final answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?spouse WHERE {
  wd:Q273833 wdt:P26 ?spouse .
}

Rory Kennedy, the daughter of Robert Kennedy, is married to Mark Bailey.

[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 is the daughter of Robert Kennedy married to?

[Assistant] To answer this question, we need to identify the daughter of Robert Kennedy and then find out who she is married to. Let's start by searching for Robert Kennedy in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Robert F. Kennedy, also known as Robert Kennedy, Robert Francis Kennedy, RFK, Bobby Kennedy (wd:Q25310): United States politician, military officer, politician, lawyer, writer
2. Robert Kennedy, also known as Robert L. Kennnedy (wd:Q59010): Irish field hockey player (1880–1963), field hockey player
3. Bobby Kennedy, also known as Robert Kennedy (wd:Q4935237): Scottish footballer and manager, association football manager, association football player
4. Robert Kennedy, also known as Robert John Kennedy (wd:Q7346314): New Zealand cricketer, cricketer
5. Robert P. Kennedy, also known as Robert Kennedy, Robert Patterson Kennedy (wd:Q7348217): Union Army officer (1840–1918), military officer, politician, lawyer
6. Robert Kennedy (wd:Q7346315): Canadian publisher (1938–2012), publisher
7. Robert B. Kennedy, also known as R. B. Kennedy, Robert Kennedy (wd:Q16105383): American politician, politician
8. Bob Kennedy, also known as Robert Kennedy, Robert Michael Kennedy (wd:Q4933007): American football player (1928–1991), American football player
9. Robert Kennedy, also known as Robert Edward Kennedy (wd:Q7346313): American Jesuit priest, psychoanalyst and Zen rōshi, writer
10. Robert Kennedy (wd:Q125958286): rhodesian rugby player (1925–1979), rugby union player

[Assistant]
The correct entity for Robert Kennedy is the first one listed, Robert F. Kennedy (wd:Q25310). Now, let's find his daughter. We can look for the property that indicates children or family relationships.

Let's search for the property that represents "children" or "daughter".

[Tool]
Top 10 property alternatives:
1. number of children, also known as children, children (number), how many children, issue, kids (wd:P1971 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): number of children of the person, animal, or character
2. child, also known as has son, kids, mother of, kid, issue (wd:P40 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
3. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
4. ASF KID Cave Tag Number, also known as Australian Speleological Federation KID, KID, Karst Index Database (wd:P2792 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): unique identifier for caves within the Karst Index Database of the Australian Speleological Federation
5. Kunstindeks Danmark Artist ID, also known as KID, KID artist ID, KID ID (wd:P1138 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): unique artist identifier used by Kunstindeks Danmark
6. child astronomical body, also known as child body, secondary, satellite, orbited by, has planet (wd:P398 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): minor body that belongs to the item
7. sibling, also known as is sister of, is the brother of, is the sibling of, is the sister of, sib (wd:P3373 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), relative
8. student, also known as teacher to, teacher of, had student, students, pupils (wd:P802 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): notable student(s) of the subject individual, significant person
9. parent, also known as guardian, parents (wd:P8810 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): parent of the subject. Only use if neither father (P22) nor mother (P25) nor stepparent (P3448) is applicable., relative
10. number of out-of-school children (wd:P2573 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): number of out-of-school children reported for a place

[Assistant]
The property "child" (wd:P40) seems to be the most appropriate for finding Robert Kennedy's children. Let's use this property to find his daughter.

We will execute a SPARQL query to find the daughter of Robert Kennedy (wd:Q25310).

[Tool]
Got 11 rows and 1 column, showing the first 5 and last 5 rows below:
| ?daughter                              |
| -------------------------------------- |
| Robert F. Kennedy Jr. (wd:Q1352872)    |
| Joseph P. Kennedy II (wd:Q1386420)     |
| Michael LeMoyne Kennedy (wd:Q1804720)  |
| David A. Kennedy (wd:Q1975383)         |
| Rory Kennedy (wd:Q273833)              |
| ...                                    |
| Kerry Kennedy (wd:Q467912)             |
| Christopher G. Kennedy (wd:Q5112377)   |
| Courtney Kennedy Hill (wd:Q5178632)    |
| Douglas Harriman Kennedy (wd:Q5301573) |
| Max Kennedy (wd:Q6794923)              |

[Assistant]
The query returned several children of Robert Kennedy. Among them, Rory Kennedy (wd:Q273833) is a daughter. Now, let's find out who Rory Kennedy is married to. We will use the property "spouse" (wd:P26) to find this information.

Let's execute a SPARQL query to find the spouse of Rory Kennedy (wd:Q273833).

[Tool]
Got 1 row and 1 column:
| ?spouse                    |
| -------------------------- |
| Mark Bailey (wd:Q29938796) |

[Assistant]
Rory Kennedy (wd:Q273833) is married to Mark Bailey (wd:Q29938796).

Here is the final SPARQL query and answer:

```sparql
SELECT ?spouse WHERE {
  wd:Q273833 wdt:P26 ?spouse .
}
```

The daughter of Robert Kennedy, Rory Kennedy, is married to Mark Bailey.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?lyricist WHERE {
  wd:Q482988 wdt:P676 ?lyricist .
}

Józef Wybicki

[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 lyrics for the Polish national anthem?

[Assistant] To find out who wrote the lyrics for the Polish national anthem, we need to identify the entity representing the Polish national anthem and then look for the property that indicates the author of the lyrics. Let's start by searching for the Polish national anthem in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Poland Is Not Yet Lost, also known as Dąbrowski's Mazurka, Polish national anthem, Song of the Polish Legions in Italy (wd:Q482988): national anthem of Poland
2. national anthem, also known as national hymn, state anthem (wd:Q23691): song that represents a country or sovereign state
3. National Anthem of Chile, also known as Canción Nacional, National Anthem (wd:Q484161): National Anthem of Chile
4. National Anthem (wd:Q2697331): Lana Del Rey song
5. National Anthem (wd:Q116945688): 2023 film directed by Luke Gilford
6. The National Anthem, also known as National Anthem (wd:Q19573235): 1999 film by Wu Ziniu
7. National Anthem (wd:Q16955069): album by The Away Team
8. National Anthem (wd:Q39078564): 2003 film
9. America, also known as National Anthem, National Hymn (wd:Q109781686): melody often used for national anthems; first published in 1744
10. National Anthem (wd:Q110059383): sketch from Saturday Night Live

[Assistant] The top result is "Poland Is Not Yet Lost, also known as Dąbrowski's Mazurka, Polish national anthem, Song of the Polish Legions in Italy" (wd:Q482988), which seems to be the correct entity for the Polish national anthem. Now, let's find the property that indicates the author of the lyrics. We can search for properties related to "lyrics" or "author".

[Tool]
Top 10 property alternatives:
1. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): author of song lyrics, author
2. has lyrics, also known as has text, has verses, lyrics that this work has, text, text that this work has (wd:P6439 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): work whose text is used as the lyrics of this work, references work, tradition or theory
3. composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator
4. Lyrics007 artist ID (wd:P7206 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): identifier for an artist on Lyrics007 site
5. LyricsTranslate ID, also known as LyricsTranslate, LyricsTranslate identifier (wd:P7212 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): identifier on LyricsTranslate
6. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
7. first line, also known as incipit, opening line, fl, first verse, first sentence (wd:P1922 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): first line (incipit) of a poem, first sentence of a novel, speech, etc.
8. developer, also known as written by, video game developer, video game dev, game developer, game dev (wd:P178 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): organization or person that developed the item, creator
9. screenwriter, also known as story by, teleplay by, video game writer, writer (of screenplays), writing credits (wd:P58 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): person(s) who wrote the script for subject item, film crew member, author
10. author, also known as writer, written by, poet, playwright, maker (wd:P50 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

[Assistant]
The property "lyricist" (wd:P676) seems to be the most appropriate for finding the author of the lyrics. Let's use this property to query the knowledge graph and find out who wrote the lyrics for the Polish national anthem.

I will now construct a SPARQL query to retrieve this information.

```sparql
SELECT ?lyricist WHERE {
  wd:Q482988 wdt:P676 ?lyricist .
}
```

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| ?lyricist                  |
| -------------------------- |
| Józef Wybicki (wd:Q370069) |

[Assistant]
The SPARQL query returned the result that Józef Wybicki (wd:Q370069) wrote the lyrics for the Polish national anthem.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?lyricist WHERE {
  wd:Q482988 wdt:P676 ?lyricist .
}
```

The lyrics for the Polish national anthem were written by Józef Wybicki.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q810986 wdt:P31 wd:Q7889 .
}

True

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

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

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

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

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

[User] Is there a video game called Battle Chess?

[Assistant] To determine if there is a video game called Battle Chess, we need to search for an entity with this name in the knowledge graph. Let's start by searching for the entity "Battle Chess" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Battle Chess (wd:Q810986): 1988 chess-playing video game
2. Battle Chess (wd:Q108370586): video game series
3. Check vs. Mate, also known as Battle vs. Chess (wd:Q3636865): 2011 video game
4. Battle Chess 4000, also known as BC 4000, BC4000 (wd:Q111966835): 1992 video game developed by Interplay
5. Eonica Chess Battle (wd:Q122824456): 2020 early access video game
6. Battle Chess II: Chinese Chess (wd:Q3636840): 1990 video game
7. Battle Chess: Game of Kings (wd:Q4869999): 2014 video game remake
8. Battle Chess Enhanced CD Rom (wd:Q124877749): 1992 video game
9. chess, also known as chess game, Western chess, modern European chess, international chess (wd:Q718): strategy board game
10. battle, also known as ⚔, combat (wd:Q178561): part of a war which is well defined in duration, area and force commitment

[Assistant]
The search has returned several entities related to "Battle Chess." The first result, `wd:Q810986`, is described as a 1988 chess-playing video game, which seems to be what we are looking for. To confirm, let's check the details of this entity to ensure it is indeed a video game.

We can use the `list` function to get more information about this entity, specifically focusing on properties that indicate it is a video game.

[Tool]
Got 293 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                            | object                               |
| ------------------------- | ----------------------------------- | ------------------------------------ |
| Battle Chess (wd:Q810986) | instance of (wdt:P31)               | video game (wd:Q7889)                |
| Battle Chess (wd:Q810986) | publication date (wdt:P577)         | 1988-01-01T00:00:00Z                 |
| Battle Chess (wd:Q810986) | language of work or name (wdt:P407) | English (wd:Q1860)                   |
| Battle Chess (wd:Q810986) | Commons category (wdt:P373)         | Battle Chess                         |
| Battle Chess (wd:Q810986) | country of origin (wdt:P495)        | United States (wd:Q30)               |
| Battle Chess (wd:Q810986) | official website (wdt:P856)         | <https://www.interplay.com>          |
| Battle Chess (wd:Q810986) | genre (wdt:P136)                    | chess video game (wd:Q71679871)      |
| Battle Chess (wd:Q810986) | publisher (wdt:P123)                | Interplay Entertainment (wd:Q628249) |
| Battle Chess (wd:Q810986) | distribution format (wdt:P437)      | digital distribution (wd:Q269415)    |
| Battle Chess (wd:Q810986) | distributed by (wdt:P750)           | Steam (wd:Q337535)                   |
| ...                       | ...                                 | ...                                  |

[Assistant]
The list of triples confirms that `wd:Q810986` is indeed a video game. Specifically, it is an instance of a video game (`wd:Q7889`), published in 1988, and is a chess video game (`wd:Q71679871`).

Since we have verified that there is a video game called Battle Chess, we can now formulate an ASK query to provide a definitive "True" or "False" answer to the user's question.

Let's construct and execute the ASK query:

```sparql
ASK WHERE {
  wd:Q810986 wdt:P31 wd:Q7889 .
}
```

This query checks if `wd:Q810986` is an instance of a video game (`wd:Q7889`).

[Tool] True

[Assistant]
The ASK query has returned `True`, confirming that there is indeed a video game called Battle Chess.

Therefore, the answer to the user's question is:

**Yes, there is a video game called Battle Chess.**

Here is the final SPARQL query and answer:

```sparql
ASK WHERE {
  wd:Q810986 wdt:P31 wd:Q7889 .
}
```

Answer: **True**

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q5513 wdt:P2046 ?baikalArea .
  wd:Q5525 wdt:P2046 ?greatBearArea .
  FILTER ( ?baikalArea > ?greatBearArea )
}

True

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

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

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

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

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

[User] Is Lake Baikal bigger than the Great Bear Lake?

[Assistant]
To answer this question, we need to compare the sizes of Lake Baikal and the Great Bear Lake. We will first identify the entities for both lakes and then find their respective areas. Finally, we will compare these areas to determine which lake is larger.

Step 1: Identify the entities for Lake Baikal and the Great Bear Lake.

[Tool]
Top 10 entity alternatives:
1. Lake Baikal, also known as Baikal, Baikal Sea, Baykal (wd:Q5513): freshwater rift lake in southern Siberia, Russia
2. Lake Baikal (wd:Q123738053): Canadian animated short film, directed by Alisi Telengut and released in 2023
3. Lake Baikal (wd:L300494-S1)
4. Baikal Seal, also known as Pusa sibirica, Phoca sibirica, Nerpa, Lake baikal seal (wd:Q4535): species of seal
5. Lake Baikal mountain vole, also known as Alticola olchonensis (wd:Q1768026): species of mammal
6. Battle of Lake Baikal (wd:Q11153274): 1918 battle of the Russian Civil War
7. 1862 lake Baikal earthquake (wd:Q4191068)
8. Ambitions for Lake Baikal (wd:Q58990558): scientific article published in Nature
9. Ice cave on Olkhon island, also known as Lake Baikal Ice Cave (wd:Q123524221): ice cave on Lake Baikal, Siberia, Russia
10. Lake Baikal in Crisis (wd:Q116758151): scientific article published in 2022

[Assistant] The top result for "Lake Baikal" is the correct entity (wd:Q5513). Now let's find the entity for the Great Bear Lake.

[Tool]
Top 10 entity alternatives:
1. Great Bear Lake, also known as Sahtú (wd:Q5525): large glacial lake in the Northwest Territories, Canada
2. Great Bear Lake (wd:Q33257595): lake in Van Buren County, Michigan, USA
3. Great Bear Lake (wd:Q39073453): 2009 novel by Erin Hunter
4. Great Bear Lake Airport, also known as DAS (wd:Q3913216): airport in Northwest Territories, Canada
5. Great Bear Lake Drain (wd:Q33194757): canal in Van Buren County, Michigan, United States of America
6. Great Bear Lake Dam (wd:Q34818758): dam in Webster County, Missouri, United States of America
7. Great Bear Lake 16 (wd:Q22424486): First Nation reserve in British Columbia, Canada
8. Great Bear Lake Water Aerodrome (wd:Q3913618): airport in Northwest Territories, Canada
9. Radium Mine, Great Bear Lake (wd:Q59504373): painting by A.Y. Jackson
10. Radium Mine, Great Bear Lake (wd:Q59552554): painting by A.Y. Jackson (NGA Canada 4542r)

[Assistant]
The top result for "Great Bear Lake" is the correct entity (wd:Q5525). Now that we have the entities for both lakes, we need to find the property that represents the area of a lake.

Step 2: Find the property for the area of a lake.

[Tool]
Top 10 property alternatives:
1. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): area occupied by an object
2. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): specialization of a person or organization; see P106 for the occupation, interested in
3. applies to part, also known as when viewed as, valid for part, section, region, per (wd:P518 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): part, aspect, or form of the item to which the claim applies
4. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
5. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
6. water area (wd:P8887 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): area/surface of a geographical entity that is covered by water, area
7. interested in, also known as area of interest, area of research, field of interest, field of research, field of study (wd:P2650 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): item of special or vested interest to this person or organisation
8. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
9. 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 psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
10. electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

[Assistant]
The property for the area of a lake is `wd:P2046`. Now we can construct a SPARQL query to retrieve the areas of both Lake Baikal and the Great Bear Lake and compare them.

Step 3: Construct and execute the SPARQL query to compare the areas of the two lakes.

[Tool]
Got 2 rows and 2 columns:
| ?lake                      | ?area |
| -------------------------- | ----- |
| Lake Baikal (wd:Q5513)     | 31722 |
| Great Bear Lake (wd:Q5525) | 31153 |

[Assistant]
The results show that the area of Lake Baikal is 31,722 square kilometers, and the area of the Great Bear Lake is 31,153 square kilometers. Therefore, Lake Baikal is indeed larger than the Great Bear Lake.

To provide a clear answer, we can use an ASK query to confirm this comparison.

Step 4: Construct and execute the ASK query to confirm the comparison.

[Tool] True

[Assistant]
The ASK query confirms that Lake Baikal is indeed larger than the Great Bear Lake.

Therefore, the answer to the question is:

**True**

Lake Baikal is bigger than the Great Bear Lake.

Now, I will provide the final SPARQL query and answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?country ) AS ?count ) WHERE {
  ?country wdt:P31 wd:Q3624078 .
  ?country wdt:P30 wd:Q46 .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 46     |

There are 46 countries in Europe.

[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 are there in Europe?

[Assistant]
To answer the question "How many countries are there in Europe?", we need to identify the entities and properties that will help us count the number of countries in Europe. Here's the step-by-step approach:

1. **Identify the continent of Europe**: We need to find the entity for Europe.
2. **Find the property for "country"**: We need to find the property that indicates a country.
3. **Count the number of countries in Europe**: We will use the identified entities and properties to construct a SPARQL query to count the number of countries in Europe.

Let's start by searching for the entity for Europe.

### Step 1: Search for the entity for Europe
I will use the `search_entity` function to find the entity for Europe.

```json
{
  "name": "search_entity",
  "arguments": {
    "kg": "wikidata",
    "query": "Europe"
  }
}
```

[Tool]
Top 10 entity alternatives:
1. Europe, also known as European continent, The Old Continent, Old Continent, European Continent, European Peninsula (wd:Q46): continent in the Northern Hemisphere
2. European Union, also known as E.U., Europe, eu (wd:Q458): political and economic union of 27 European states
3. Europa, also known as Europe, Evropa (wd:Q165170): Phoenician character in Greek mythology, daughter of Agenor
4. Europe (wd:Q185144): Swedish rock band
5. Europe (wd:Q579160): National anthem of Kosovo
6. Europe (wd:Q766618): Paris Métro station
7. Europe (wd:Q1163173): international racing sailing class
8. Europe (wd:Q198697): 1983 debut studio album by Europe
9. James Reese Europe, also known as Jim Europe, James R. Europe, James R. Europe, Sr., Lieut. Jim Europe, James Europe (wd:Q1280917): American jazz musician and United States Army officer (1880-1919), jazz musician, mandolinist, bandleader, conductor, composer, pianist
10. Europe (wd:Q612228): French magazine

[Assistant]
From the search results, the entity for Europe as a continent is `wd:Q46`.

### Step 2: Find the property for "country"
Next, we need to find the property that indicates a country. We can search for properties related to "country" or "nation".

```json
{
  "name": "search_property",
  "arguments": {
    "kg": "wikidata",
    "query": "country"
  }
}
```

[Tool]
Top 10 property alternatives:
1. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): place where a statement is valid, applies to part
2. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): the object is a country that recognizes the subject as its citizen, country
4. country, also known as sovereign state, state, land, host country (wd:P17 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
6. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): most specific known birth location of a person, animal or fictional character, location
7. continent (wd:P30 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): continent of which the subject is a part, located in/on physical feature
8. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
9. place of publication, also known as published in (place), where published, release region, released in, published from (wd:P291 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): geographical place of publication of the edition (use 1st edition when referring to works), significant place
10. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as psv/pqn/prn/pr/wdtn/p/pqv/prv/pq/wdt/ps/psn): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

[Assistant]
From the search results, the property that indicates a country is `wd:P17` (country).

### Step 3: Construct the SPARQL query to count the number of countries in Europe
We will use the identified entities and properties to construct a SPARQL query to count the number of countries in Europe. We will filter the results to include only those entities that are countries and are located in Europe.

Here is the initial SPARQL query:

```sparql
SELECT (COUNT(?country) AS ?count)
WHERE {
  ?country wdt:P31 wd:Q3624078 .  # ?country is an instance of a country
  ?country wdt:P30 wd:Q46 .       # ?country is located in Europe
}
```

Let's execute this query to get the count of countries in Europe.

```json
{
  "name": "execute",
  "arguments": {
    "kg": "wikidata",
    "sparql": "SELECT (COUNT(?country) AS ?count) WHERE { ?country wdt:P31 wd:Q3624078 . ?country wdt:P30 wd:Q46 . }"
  }
}
```

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 46     |

[Assistant]
The SPARQL query returned a count of 46 countries in Europe.

### Final Answer
There are 46 countries in Europe.

```json
{
  "name": "answer",
  "arguments": {
    "kg": "wikidata",
    "sparql": "SELECT (COUNT(?country) AS ?count) WHERE { ?country wdt:P31 wd:Q3624078 . ?country wdt:P30 wd:Q46 . }",
    "answer": "There are 46 countries in Europe."
  }
}
```

[Tool] Stopped generation process