PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?sabrina ?email WHERE {
  ?sabrina rdfs:label ?label .
  FILTER ( CONTAINS( LCASE( STR( ?label ) ) , "sabrina" ) ) ?sabrina pv:memberOf ?dept .
  ?dept rdfs:label ?deptLabel .
  FILTER ( LCASE( STR( ?deptLabel ) ) = "marketing" ) ?sabrina pv:email ?email
}

The email of Sabrina from Marketing is Sabrina.Geiger@company.org.

What is the email of Sabrina from Marketing?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the email of Sabrina from Marketing?

[Assistant]
Step 1: Identify entities and properties.
- Entity: "Sabrina" (person)
- Department: "Marketing"
- Property: "email"

Step 2: Search for the entity "Sabrina" in the knowledge graph to find her identifier.

[Tool]
Top 10 entity alternatives:
1. empl Sabrina Geiger@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Geiger%40company.org>): is a Employee
2. empl Sabrina Bayer@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Bayer%40company.org>): is a Employee

[Assistant]
There are two entities named "Sabrina" in the knowledge graph:
1. Sabrina Geiger
2. Sabrina Bayer

Step 3: Determine which one is from the Marketing department. I will check the department or similar property for both entities.

[Tool]
Top 10 property alternatives:
1. area of expertise (pv:areaOfExpertise): The product category agent is expert for., has range Product Category, has domain Agent
2. label (rdfs:label)
3. has manager (pv:hasManager): The manager of the employee., has domain Employee, has range Manager
4. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
5. type (rdf:type)
6. name (pv:name): The name of something.
7. email (pv:email): The e-mail of an agent., has domain Agent
8. phone number (pv:phone): has domain Agent, A phone number.

No other items found

[Tool]
Got 1 row and 3 columns:
| subject                                                                                | property                | object                        |
| ---------------------------------------------------------------------------------------------------------- | ----------------------- | ----------------------------- |
| empl Sabrina Geiger@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Geiger%40company.org>) | member of (pv:memberOf) | dept 85880 (prodi:dept-85880) |

[Tool]
Got 16 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                            | object                                    |
| ----------------------------- | ----------------------------------- | ----------------------------------------- |
| dept 85880 (prodi:dept-85880) | type (rdf:type)                     | Department (pv:Department)                |
| dept 85880 (prodi:dept-85880) | label (rdfs:label)                  | Marketing                                 |
| dept 85880 (prodi:dept-85880) | name (pv:name)                      | Marketing                                 |
| dept 85880 (prodi:dept-85880) | ID (pv:id)                          | 85880                                     |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | srv P516 8211068 (prodi:srv-P516-8211068) |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | srv O662 4012383 (prodi:srv-O662-4012383) |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | srv U360 2815908 (prodi:srv-U360-2815908) |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | hw C831 2580759 (prodi:hw-C831-2580759)   |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | hw D334 6681399 (prodi:hw-D334-6681399)   |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | hw D844 3535311 (prodi:hw-D844-3535311)   |
| ...                           | ...                                 | ...                                       |

[Tool]
Got 1 row and 3 columns:
| subject                                                                                | property         | object                     |
| ---------------------------------------------------------------------------------------------------------- | ---------------- | -------------------------- |
| empl Sabrina Geiger@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Geiger%40company.org>) | email (pv:email) | Sabrina.Geiger@company.org |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is well-constructed and correctly retrieves the email address of Sabrina from the Marketing department. It uses appropriate filters to match the name 'Sabrina' and the department 'Marketing', and returns the actual IRI and email as required. The answer is accurate and complete based on the execution result.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
SELECT ?product ?price ?amount ?currency ?name ?name2 WHERE {
  ?product pv:hasCategory prodi:prod-cat-Oscillator .
  ?product pv:price ?price .
  ?price pv:amount ?amount .
  OPTIONAL {
    ?price pv:currency ?currency
  }
  OPTIONAL {
    ?product foaf:name ?name
  }
  OPTIONAL {
    ?product pv:name ?name2
  }
}
ORDER BY ASC ( xsd:decimal ( ?amount ) )
LIMIT 1

The cheapest Oscillator is prodi:hw-F388-7030185 (Oscillator Transistor Transducer) with a price of 0.1 EUR.

What is the cheapest Oscillator we have?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the cheapest Oscillator we have?

[Assistant]
Step 1: Determine possible entities and properties implied by the user question.

- Entity: Oscillator (likely a product type or class)
- Property: price or cost (to determine the cheapest)
- The question asks for the cheapest Oscillator, so we need to find all Oscillators and their prices, then select the one with the lowest price.

Step 2: Search for the entity "Oscillator" in the knowledge graph to find its identifier.

[Tool]
Top 10 entity alternatives:
1. prod cat Oscillator (prodi:prod-cat-Oscillator): is a Product Category

[Assistant]
The entity "Oscillator" is represented as a product category: prodi:prod-cat-Oscillator.

Step 3: Identify how products are linked to their product category and how price is represented.

- We need to find products that are of category prodi:prod-cat-Oscillator.
- We need to find the property that links a product to its category.
- We also need to find the property that represents the price of a product.

Let's search for properties related to "category" to see how products are linked to categories.

[Tool]
Top 10 property alternatives:
1. has category (pv:hasCategory): The category name of a product., has range Product Category, has domain Product
2. label (rdfs:label)
3. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
4. type (rdf:type)
5. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
6. vocabulary (void:vocabulary)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. sub Class Of (rdfs:subClassOf)
10. is Defined By (rdfs:isDefinedBy)

[Assistant]
The property pv:hasCategory is used to link a product to its category, and its range is Product Category.

Step 4: Search for properties related to "price" to find how the price of a product is represented.

[Tool]
Top 10 property alternatives:
1. price (pv:price): The price specification of a product., has domain Product, has range Price
2. currency (pv:currency): has domain Price, The currency.
3. amount (pv:amount): has domain Price, The amount.
4. name (foaf:name):

5. name (pv:name): The name of something.
6. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
7. quantity (pv:quantity): The quantity needed., has domain BOM Part
8. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
9. ID (pv:id): The ID of a thing.
10. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product

[Assistant]
The property pv:price links a product to a Price entity. The Price entity has properties pv:amount (the numeric value) and pv:currency (the currency).

Step 5: Let's check how products are represented and how to get their names or labels. I'll search for properties related to "name" for products.

[Tool]
Top 10 property alternatives:
1. name (foaf:name):

2. name (pv:name): The name of something.
3. ID (pv:id): The ID of a thing.
4. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
5. domain (rdfs:domain)
6. label (rdfs:label)
7. phone number (pv:phone): has domain Agent, A phone number.
8. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
9. price (pv:price): The price specification of a product., has domain Product, has range Price
10. created (dct:created)

[Assistant]
Products may have their names under foaf:name or pv:name, and possibly rdfs:label.

Step 6: Build a SPARQL query to find all products with pv:hasCategory prodi:prod-cat-Oscillator, get their price (pv:price), the amount (pv:amount), and the name (foaf:name or pv:name), and select the one with the lowest price.

I'll use OPTIONAL for the name properties to maximize the chance of getting a label.

Let's write and execute the query.

[Tool]
Got 1 row and 6 columns:
| product                                 | price                                                       | amount            | currency | name | name2                            |
| --------------------------------------- | ----------------------------------------------------------- | ----------------- | -------- | ---- | -------------------------------- |
| hw F388 7030185 (prodi:hw-F388-7030185) | price hw F388 7030185 EUR (prodi:price-hw-F388-7030185-EUR) | 0.1 (xsd:decimal) | EUR      |      | Oscillator Transistor Transducer |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the cheapest Oscillator by ordering the products in the Oscillator category by price amount in ascending order and limiting the result to one. The query returns the product IRI, price, amount, currency, and both possible name properties, all in accordance with the requirements. The answer is accurate and complete based on the execution result.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX dbpedia: <http://dbpedia.org/resource/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
SELECT ?product ?productName ?supplier ?supplierName ?amount WHERE {
  ?product pv:hasCategory prodi:prod-cat-Encoder ; pv:hasSupplier ?supplier ; pv:price ?priceSpec .
  ?priceSpec pv:amount ?amount .
  ?supplier pv:country ?country .
  FILTER ( ?country IN ( dbpedia:France , dbpedia:Germany ) ) OPTIONAL {
    ?product pv:name ?productName
  }
  OPTIONAL {
    ?supplier pv:name ?supplierName
  }
}
ORDER BY ASC ( ?amount )
LIMIT 1

The cheapest Encoder from a French or German supplier is 'Encoder Breaker' (prodi:hw-P453-8155326), supplied by 'Fletcher, Pierce and Navarro' (prodi:suppl-9e95d78d-7f95-4752-9e1f-d522e67e63d7), at a price of 0.39.

What is the cheapest Encoder we can get from a french or german supplier?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the cheapest Encoder we can get from a french or german supplier?

[Assistant]
Let's break down the question:

1. We are looking for "Encoder" products.
2. The supplier must be from France or Germany.
3. We want the cheapest such encoder.

Step 1: Identify the entity for "Encoder".
Step 2: Identify properties for supplier, supplier country, and price.
Step 3: Find suppliers from France or Germany.
Step 4: Find encoders supplied by those suppliers, and their prices.
Step 5: Select the cheapest one.

Let's start by searching for the entity "Encoder".

[Tool]
Top 10 entity alternatives:
1. prod cat Encoder (prodi:prod-cat-Encoder): is a Product Category

[Assistant]
The entity "prod cat Encoder" (prodi:prod-cat-Encoder) is a Product Category for Encoders. We will use this to find products of this category.

Next, let's identify properties related to supplier, supplier country, and price. I'll search for properties related to "supplier" first.

[Tool]
Top 10 property alternatives:
1. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
2. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
3. contributor (dct:contributor)
4. publisher (dct:publisher)
5. quantity (pv:quantity): The quantity needed., has domain BOM Part
6. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
7. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
8. label (rdfs:label)
9. has product manager (pv:hasProductManager): The employee acting as the product manager of the product., has range Employee, has domain Product
10. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent

[Assistant]
We have found relevant properties:
- pv:hasSupplier (supplier of a product)
- pv:country (country of the supplier)

Now, let's search for a property related to "price".

[Tool]
Top 10 property alternatives:
1. price (pv:price): The price specification of a product., has domain Product, has range Price
2. currency (pv:currency): has domain Price, The currency.
3. amount (pv:amount): has domain Price, The amount.
4. name (foaf:name):

5. name (pv:name): The name of something.
6. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
7. quantity (pv:quantity): The quantity needed., has domain BOM Part
8. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
9. ID (pv:id): The ID of a thing.
10. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product

[Assistant]
We have found:
- pv:price (price specification of a product, range: Price)
- pv:amount (amount, domain: Price)
- pv:currency (currency, domain: Price)

So, to get the price value, we need to go from Product → pv:price → Price → pv:amount.

Next, let's search for suppliers from France or Germany. First, let's search for country entities for "France" and "Germany".

[Tool]
Top 10 entity alternatives:
1. France (dbpedia:France)

[Tool]
Top 10 entity alternatives:
1. Germany (dbpedia:Germany)

[Assistant]
We have:
- dbpedia:France
- dbpedia:Germany

Now, let's summarize the plan for the SPARQL query:
- Find products of category prodi:prod-cat-Encoder.
- Get their suppliers (pv:hasSupplier).
- Filter suppliers whose pv:country is dbpedia:France or dbpedia:Germany.
- Get the product's price (pv:price → pv:amount).
- Return the product with the minimum price.

Let's check how products are linked to their category. I'll search for properties related to "category" for products.

[Tool]
Top 10 property alternatives:
1. has category (pv:hasCategory): The category name of a product., has range Product Category, has domain Product
2. label (rdfs:label)
3. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
4. type (rdf:type)
5. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
6. vocabulary (void:vocabulary)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. sub Class Of (rdfs:subClassOf)
10. is Defined By (rdfs:isDefinedBy)

[Assistant]
Products are linked to their category via pv:hasCategory.

Now, let's put all the pieces together:
- Product ?product
  - pv:hasCategory prodi:prod-cat-Encoder
  - pv:hasSupplier ?supplier
  - pv:price ?priceSpec
    - pv:amount ?amount
  - pv:name ?productName (optional)
- Supplier ?supplier
  - pv:country dbpedia:France or dbpedia:Germany
  - pv:name ?supplierName (optional)

We want the product with the minimum price (?amount).

Let's write a SPARQL query to get the cheapest encoder from a French or German supplier, including product and supplier IRIs and names, and the price.

[Tool]
Got 1 row and 5 columns:
| product                                 | productName     | supplier                                                                                | supplierName                 | amount             |
| --------------------------------------- | --------------- | --------------------------------------------------------------------------------------------- | ---------------------------- | ------------------ |
| hw P453 8155326 (prodi:hw-P453-8155326) | Encoder Breaker | suppl 9e95d78d 7f95 4752 9e1f d522e67e63d7 (prodi:suppl-9e95d78d-7f95-4752-9e1f-d522e67e63d7) | Fletcher, Pierce and Navarro | 0.39 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly finds the cheapest Encoder from a French or German supplier by filtering suppliers based on country, ordering by price, and limiting the result to one. The query returns the required IRIs and includes optional human-readable names. The answer matches the query result. No further refinement is needed.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
SELECT ?expert ?name WHERE {
  ?expert pv:areaOfExpertise prodi:prod-cat-Sensor .
  OPTIONAL {
    ?expert foaf:name ?name
  }
  OPTIONAL {
    ?expert rdfs:label ?name
  }
}

Got 7 rows and 2 columns:
| expert                                                                                | name                |
| -------------------------------------------------------------------------------------------------------------------- | ------------------- |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | Anamchara Foerstner |
| empl Arendt Beitel@company org (<http://ld.company.org/prod-instances/empl-Arendt.Beitel%40company.org>)             | Arendt Beitel       |
| empl Gretel Roth@company org (<http://ld.company.org/prod-instances/empl-Gretel.Roth%40company.org>)                 | Gretel Roth         |
| empl Liese Adam@company org (<http://ld.company.org/prod-instances/empl-Liese.Adam%40company.org>)                   | Liese Adam          |
| empl Lili Geier@company org (<http://ld.company.org/prod-instances/empl-Lili.Geier%40company.org>)                   | Lili Geier          |
| empl Sylvester Brant@company org (<http://ld.company.org/prod-instances/empl-Sylvester.Brant%40company.org>)         | Sylvester Brant     |
| empl Xochitl Aue@company org (<http://ld.company.org/prod-instances/empl-Xochitl.Aue%40company.org>)                 | Xochitl Aue         |

The Sensor experts are: Anamchara Foerstner, Arendt Beitel, Gretel Roth, Liese Adam, Lili Geier, Sylvester Brant, and Xochitl Aue.

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 our Sensor expert?

[Assistant]
Step 1: Determine possible entities and properties implied by the user question.

The question asks "Who is our Sensor expert?" This suggests:
- There is an entity representing a "Sensor expert" (likely a person with expertise in sensors).
- There may be a property linking people to their area of expertise (e.g., "expertise", "hasExpertise", "field", etc.).
- The term "our" may refer to a specific organization or context, but unless specified, I will assume it means "the Sensor expert in the knowledge graph".

Step 2: Search for the entity "Sensor" and properties related to expertise.

First, I will search for the entity "Sensor" to see how it is represented in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. prod cat Sensor (prodi:prod-cat-Sensor): is a Product Category

[Assistant]
The entity "prod cat Sensor" (prodi:prod-cat-Sensor) is found and is a Product Category. Now, I need to find properties that could link a person (expert) to this product category, such as "expert", "expertise", "hasExpertise", or similar.

I will search for properties related to "expert" in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. area of expertise (pv:areaOfExpertise): The product category agent is expert for., has range Product Category, has domain Agent
2. contributor (dct:contributor)
3. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
4. ID (pv:id): The ID of a thing.
5. creator (dct:creator)
6. created (dct:created)
7. type (rdf:type)
8. name (foaf:name):

9. name (pv:name): The name of something.
10. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product

[Assistant]
The property "area of expertise" (pv:areaOfExpertise) is described as linking an agent (likely a person) to a product category for which they are an expert. This matches our use case.

Step 3: Search for agents (people) who have "Sensor" as their area of expertise.

I will now construct a SPARQL query to find agents with pv:areaOfExpertise prodi:prod-cat-Sensor, and optionally retrieve their labels or names.

[Tool]
Got 7 rows and 2 columns:
| expert                                                                                | name                |
| -------------------------------------------------------------------------------------------------------------------- | ------------------- |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | Anamchara Foerstner |
| empl Arendt Beitel@company org (<http://ld.company.org/prod-instances/empl-Arendt.Beitel%40company.org>)             | Arendt Beitel       |
| empl Gretel Roth@company org (<http://ld.company.org/prod-instances/empl-Gretel.Roth%40company.org>)                 | Gretel Roth         |
| empl Liese Adam@company org (<http://ld.company.org/prod-instances/empl-Liese.Adam%40company.org>)                   | Liese Adam          |
| empl Lili Geier@company org (<http://ld.company.org/prod-instances/empl-Lili.Geier%40company.org>)                   | Lili Geier          |
| empl Sylvester Brant@company org (<http://ld.company.org/prod-instances/empl-Sylvester.Brant%40company.org>)         | Sylvester Brant     |
| empl Xochitl Aue@company org (<http://ld.company.org/prod-instances/empl-Xochitl.Aue%40company.org>)                 | Xochitl Aue         |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and follows all the required rules. It returns the IRIs of the experts as well as their names (optionally via foaf:name or rdfs:label). The answer accurately reflects the query results. No further refinement is necessary.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX prodi: <http://ld.company.org/prod-instances/>
SELECT ?product ?productLabel ?supplier ?supplierLabel WHERE {
  VALUES ?u990 {
    prodi:hw-U990-5234138
  }
  ?u990 pv:compatibleProduct ?product .
  ?product pv:hasSupplier ?supplier .
  OPTIONAL {
    ?product rdfs:label ?productLabel
  }
  OPTIONAL {
    ?supplier rdfs:label ?supplierLabel
  }
  ?supplier pv:addressCountryCode ?countryCode .
  FILTER ( ?countryCode = "US" )
}

You can get the following products from US suppliers that are compatible with the U990 LCD Inductor:

1. A360-3041803 - Inductor Transformer Warp (prodi:hw-A360-3041803) from Fernandez-Roberts (United States)
2. A509-5571891 - Multiplexer Inductor (prodi:hw-A509-5571891) from Collins and Sons (United States)

What products can I get from US suppliers that are compatible with the U990 LCD Inductor?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What products can I get from US suppliers that are compatible with the U990 LCD Inductor?

[Assistant]
Let's break down the question:

1. We need to identify the entity for "U990 LCD Inductor".
2. We need to find products that are compatible with this inductor.
3. These products must be available from US suppliers.

Step 1: Search for the entity "U990 LCD Inductor" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. prod cat LCD (prodi:prod-cat-LCD): is a Product Category
2. prod cat Inductor (prodi:prod-cat-Inductor): is a Product Category
3. hw U990 5234138 (prodi:hw-U990-5234138): is a Hardware
4. bom part 18 U990 5234138 (prodi:bom-part-18-U990-5234138): is a BOM Part
5. bom part 5 U990 5234138 (prodi:bom-part-5-U990-5234138): is a BOM Part
6. price hw U990 5234138 EUR (prodi:price-hw-U990-5234138-EUR): is a Price

[Assistant]
From the search results, "hw U990 5234138" (prodi:hw-U990-5234138) appears to be the hardware entity most closely matching "U990 LCD Inductor". There are also BOM parts related to U990, but for compatibility, the hardware entity is likely the correct reference.

Next, I need to find products that are compatible with this hardware. I will search for properties related to "compatibility" for the entity prodi:hw-U990-5234138.

[Tool]
Top 10 property alternatives:
1. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
2. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
3. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
4. type (rdf:type)
5. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
6. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
7. ID (pv:id): The ID of a thing.
8. label (rdfs:label)
9. name (pv:name): The name of something.
10. has reliability index (pv:reliabilityIndex): A computed KPI to have an reliablity indicator in the context of a supply chain., has domain Hardware

No other items found

[Assistant]
The property pv:compatibleProduct ("compatible product") is likely used to indicate products compatible with a given hardware item.

Next, I will list triples where prodi:hw-U990-5234138 is the subject and pv:compatibleProduct is the property, to find compatible products.

[Tool]
Got 6 rows and 3 columns:
| subject                                 | property                                  | object                                  |
| --------------------------------------- | ----------------------------------------- | --------------------------------------- |
| hw U990 5234138 (prodi:hw-U990-5234138) | compatible product (pv:compatibleProduct) | hw A360 3041803 (prodi:hw-A360-3041803) |
| hw U990 5234138 (prodi:hw-U990-5234138) | compatible product (pv:compatibleProduct) | hw A509 5571891 (prodi:hw-A509-5571891) |
| hw U990 5234138 (prodi:hw-U990-5234138) | compatible product (pv:compatibleProduct) | hw F675 6890144 (prodi:hw-F675-6890144) |
| hw U990 5234138 (prodi:hw-U990-5234138) | compatible product (pv:compatibleProduct) | hw I264 7314323 (prodi:hw-I264-7314323) |
| hw U990 5234138 (prodi:hw-U990-5234138) | compatible product (pv:compatibleProduct) | hw J178 7002767 (prodi:hw-J178-7002767) |
| hw U990 5234138 (prodi:hw-U990-5234138) | compatible product (pv:compatibleProduct) | hw S113 2439377 (prodi:hw-S113-2439377) |

[Assistant]
I have found six products compatible with the U990 LCD Inductor (prodi:hw-U990-5234138):

- prodi:hw-A360-3041803
- prodi:hw-A509-5571891
- prodi:hw-F675-6890144
- prodi:hw-I264-7314323
- prodi:hw-J178-7002767
- prodi:hw-S113-2439377

Now, I need to determine which of these products are available from US suppliers. To do this, I will check for a property like "hasSupplier" or similar for these products, and then filter for suppliers located in the US.

First, I will check the property "hasSupplier" (pv:hasSupplier) for one of these products (e.g., prodi:hw-A360-3041803).

[Tool]
Got 1 row and 3 columns:
| subject                                 | property                  | object                                                                                |
| --------------------------------------- | ------------------------- | --------------------------------------------------------------------------------------------- |
| hw A360 3041803 (prodi:hw-A360-3041803) | supplier (pv:hasSupplier) | suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) |

[Assistant]
The product prodi:hw-A360-3041803 has a supplier linked via the property pv:hasSupplier. The supplier entity is prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491.

Next, I need to determine if this supplier is a US supplier. I will check what properties are available for this supplier entity, looking for location or country information.

[Tool]
Got 10 rows and 3 columns:
| subject                                                                                | property                                     | object                                |
| --------------------------------------------------------------------------------------------- | -------------------------------------------- | ------------------------------------- |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | type (rdf:type)                              | Supplier (pv:Supplier)                |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | label (rdfs:label)                           | Fernandez-Roberts (United States)     |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | name (pv:name)                               | Fernandez-Roberts                     |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | ID (pv:id)                                   | 29cf8eca-50be-460e-9816-5ae505fc9491  |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | address country (pv:addressCountry)          | United States                         |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | address country code (pv:addressCountryCode) | US                                    |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | address locality (pv:addressLocality)        | Harlingen                             |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | lat (wgs84:lat)                              | 26.1907543                            |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | long (wgs84:long)                            | -97.6960599                           |
| suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | country (pv:country)                         | United States (dbpedia:United_States) |

[Assistant]
The supplier "Fernandez-Roberts" (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) is indeed a US supplier, as indicated by the country properties.

To answer the question, I need to repeat this process for all six compatible products, checking if their suppliers are US-based. To do this efficiently, I will write a SPARQL query that:

- Finds all products compatible with prodi:hw-U990-5234138,
- Gets their suppliers,
- Filters for suppliers with country "United States" or country code "US".

I will include optional labels for products and suppliers for readability.

[Tool]
Got 2 rows and 4 columns:
| product                                 | productLabel                             | supplier                                                                                | supplierLabel                     |
| --------------------------------------- | ---------------------------------------- | --------------------------------------------------------------------------------------------- | --------------------------------- |
| hw A360 3041803 (prodi:hw-A360-3041803) | A360-3041803 - Inductor Transformer Warp | suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | Fernandez-Roberts (United States) |
| hw A509 5571891 (prodi:hw-A509-5571891) | A509-5571891 - Multiplexer Inductor      | suppl afa65b2a f046 47f4 b352 97b579c77c21 (prodi:suppl-afa65b2a-f046-47f4-b352-97b579c77c21) | Collins and Sons (United States)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves products compatible with the U990 LCD Inductor, supplied by US suppliers, and returns their IRIs as required. The answer matches the query results and includes all relevant information. No further refinement is needed.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT ?bom ( AVG( ?amount ) AS ?avgUnitCost ) WHERE {
  ?bom rdf:type pv:BillOfMaterial .
  ?bom pv:hasBomPart ?bomPart .
  ?bomPart pv:hasPart ?product .
  ?product rdf:type pv:Hardware .
  ?product pv:price ?price .
  ?price pv:amount ?amount .
}
GROUP BY ?bom
ORDER BY DESC ( ?avgUnitCost )
LIMIT 1

The Bill-of-Material with the highest average unit cost of its hardware parts is prodi:bom-8 (MotoSync QuantumWave), with an average unit cost of 4.

Which Bill-of-Material has the highest average unit cost of its hardware parts, and what is that average?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 Bill-of-Material has the highest average unit cost of its hardware parts, and what is that average?

[Assistant]
Let's break down the question:

1. We need to identify all Bill-of-Material (BOM) entities.
2. For each BOM, we need to find its hardware parts.
3. For each hardware part, we need to get its unit cost.
4. For each BOM, calculate the average unit cost of its hardware parts.
5. Find the BOM with the highest average unit cost and return that BOM and the average.

First, let's search for the entity and property identifiers for:
- "Bill-of-Material"
- "hardware part"
- "unit cost"

I'll start by searching for "Bill-of-Material".

[Tool] No entity items found

[Assistant] No entity was found for "Bill-of-Material". It's possible the knowledge graph uses a different label or naming convention. Let's try searching for "BOM" as an alternative, since it's a common abbreviation.

[Tool]
Top 10 entity alternatives:
1. BOM Part (pv:BomPart): A (number of) part(s) in a BOM.
2. bom 4 (prodi:bom-4): is a Bill of Material (BOM)
3. bom 19 (prodi:bom-19): is a Bill of Material (BOM)
4. bom 12 (prodi:bom-12): is a Bill of Material (BOM)
5. bom 2 (prodi:bom-2): is a Bill of Material (BOM)
6. bom 11 (prodi:bom-11): is a Bill of Material (BOM)
7. bom 18 (prodi:bom-18): is a Bill of Material (BOM)
8. bom 6 (prodi:bom-6): is a Bill of Material (BOM)
9. bom 15 (prodi:bom-15): is a Bill of Material (BOM)
10. bom 5 (prodi:bom-5): is a Bill of Material (BOM)

[Assistant]
We found several entities for BOMs, such as prodi:bom-4, prodi:bom-19, etc. There is also a class/entity called "BOM Part" (pv:BomPart), which likely represents parts within a BOM.

Next, let's search for properties that link a BOM to its parts. I'll search for properties related to "part" to see how BOMs are connected to their parts.

[Tool]
Top 10 property alternatives:
1. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
2. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
3. contributor (dct:contributor)
4. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
5. has BOM Part (pv:hasBomPart): has domain Bill of Material (BOM), A part(s) used in this BOM., has range BOM Part
6. type (rdf:type)
7. sub Class Of (rdfs:subClassOf)
8. quantity (pv:quantity): The quantity needed., has domain BOM Part
9. label (rdfs:label)
10. modified (dct:modified)

[Assistant]
The property pv:hasBomPart connects a Bill of Material (BOM) to its BOM Parts. The property pv:hasPart connects a BOM Part to a Product.

Now, let's check how to identify "hardware parts." I'll search for entities or classes related to "hardware" to see if there's a specific type or class for hardware parts.

[Tool]
Top 10 entity alternatives:
1. Hardware (pv:Hardware): The hardware products produced., is subclass of Product
2. hardware chip outline svg?color=#D6AF00&format=svg (<https://api.iconify.design/ion/hardware-chip-outline.svg?color=%23D6AF00&format=svg>)

[Assistant]
There is an entity/class called pv:Hardware, which is a subclass of Product. This likely represents hardware products.

Now, let's search for properties related to "unit cost" to find the cost property for parts or products.

[Tool]
Top 10 property alternatives:
1. price (pv:price): The price specification of a product., has domain Product, has range Price
2. amount (pv:amount): has domain Price, The amount.
3. currency (pv:currency): has domain Price, The currency.
4. quantity (pv:quantity): The quantity needed., has domain BOM Part
5. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
6. lat (wgs84:lat)
7. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware
8. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
9. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
10. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent

[Assistant]
The property pv:price connects a Product to a Price entity, and pv:amount gives the numeric value of the price. So, to get the unit cost, we need to go from Product → pv:price → Price → pv:amount.

Let's summarize the path:
- BOM (e.g., prodi:bom-4) --pv:hasBomPart--> BOM Part --pv:hasPart--> Product
- Product --rdf:type--> pv:Hardware (to filter for hardware parts)
- Product --pv:price--> Price --pv:amount--> (unit cost as a literal)

Now, let's check if BOMs have a type or class, to generalize the query. I'll search for the class of prodi:bom-4.

[Tool]
Got 18 rows and 3 columns, showing the first 10 rows below:
| subject             | property                     | object                                                  |
| ------------------- | ---------------------------- | ------------------------------------------------------- |
| bom 4 (prodi:bom-4) | type (rdf:type)              | Bill of Material (BOM) (pv:BillOfMaterial)              |
| bom 4 (prodi:bom-4) | label (rdfs:label)           | PulseCraft Vertex                                       |
| bom 4 (prodi:bom-4) | name (pv:name)               | PulseCraft Vertex                                       |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 C794 6433363 (prodi:bom-part-4-C794-6433363) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 D605 8095260 (prodi:bom-part-4-D605-8095260) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 F661 8988230 (prodi:bom-part-4-F661-8988230) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 H634 7337115 (prodi:bom-part-4-H634-7337115) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 J859 3337215 (prodi:bom-part-4-J859-3337215) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 K926 9334427 (prodi:bom-part-4-K926-9334427) |
| ...                 | ...                          | ...                                                     |

[Assistant]
prodi:bom-4 is of type pv:BillOfMaterial. So, we can generalize the query to select all BOMs of type pv:BillOfMaterial.

Now, let's check the structure of a BOM Part, specifically how it connects to a Product and if there are any other relevant properties. I'll look at one BOM Part, e.g., prodi:bom-part-4-A750-6901242.

[Tool]
Got 4 rows and 3 columns:
| subject                                                 | property               | object                                  |
| ------------------------------------------------------- | ---------------------- | --------------------------------------- |
| bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) | type (rdf:type)        | BOM Part (pv:BomPart)                   |
| bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) | label (rdfs:label)     | A750-6901242 (44)                       |
| bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) | quantity (pv:quantity) | 44                                      |
| bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) | part (pv:hasPart)      | hw A750 6901242 (prodi:hw-A750-6901242) |

[Tool]
Got 16 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                                   | object                                                                                |
| --------------------------------------- | ------------------------------------------ | ---------------------------------------------------------------------------------------------------------- |
| hw A750 6901242 (prodi:hw-A750-6901242) | type (rdf:type)                            | Hardware (pv:Hardware)                                                                                |
| hw A750 6901242 (prodi:hw-A750-6901242) | label (rdfs:label)                         | A750-6901242 - Film Resistor Memristor Meter                                                               |
| hw A750 6901242 (prodi:hw-A750-6901242) | has category (pv:hasCategory)              | prod cat Memristor (prodi:prod-cat-Memristor)                                                              |
| hw A750 6901242 (prodi:hw-A750-6901242) | compatible product (pv:compatibleProduct)  | hw F574 4728030 (prodi:hw-F574-4728030)                                                                    |
| hw A750 6901242 (prodi:hw-A750-6901242) | name (pv:name)                             | Film Resistor Memristor Meter                                                                              |
| hw A750 6901242 (prodi:hw-A750-6901242) | ID (pv:id)                                 | A750-6901242                                                                                |
| hw A750 6901242 (prodi:hw-A750-6901242) | has product manager (pv:hasProductManager) | empl Kristen Bauers@company org (<http://ld.company.org/prod-instances/empl-Kristen.Bauers%40company.org>) |
| hw A750 6901242 (prodi:hw-A750-6901242) | price (pv:price)                           | price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR)                                                |
| hw A750 6901242 (prodi:hw-A750-6901242) | depth (mm) (pv:depth_mm)                   | 19 (xsd:int)                                                                                |
| hw A750 6901242 (prodi:hw-A750-6901242) | supplier (pv:hasSupplier)                  | suppl 79274f67 b225 49fa ad8c fb20560cb1d5 (prodi:suppl-79274f67-b225-49fa-ad8c-fb20560cb1d5)              |
| ...                                     | ...                                        | ...                                                                                |

[Tool]
Got 4 rows and 3 columns:
| subject                                                     | property               | object             |
| ----------------------------------------------------------- | ---------------------- | ------------------ |
| price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR) | type (rdf:type)        | Price (pv:Price)   |
| price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR) | label (rdfs:label)     | 5,49 EUR           |
| price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR) | amount (pv:amount)     | 5.49 (xsd:decimal) |
| price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR) | currency (pv:currency) | EUR                |

[Assistant]
We have confirmed the full path for retrieving the unit cost of a hardware part:
- BOM (pv:BillOfMaterial) --pv:hasBomPart--> BOM Part --pv:hasPart--> Product (pv:Hardware)
- Product --pv:price--> Price --pv:amount--> (unit cost)

Now, let's construct the SPARQL query:
- For each BOM, get all its BOM Parts.
- For each BOM Part, get the Product (hardware part).
- Filter Products to only those of type pv:Hardware.
- For each Product, get its price amount.
- For each BOM, calculate the average unit cost of its hardware parts.
- Return the BOM with the highest average unit cost and the average.

Let's write the SPARQL query accordingly.

[Tool]
Got 1 row and 2 columns:
| bom                 | avgUnitCost     |
| ------------------- | --------------- |
| bom 8 (prodi:bom-8) | 4 (xsd:decimal) |

[Tool]
Got 8 rows and 3 columns:
| subject             | property                     | object                                                  |
| ------------------- | ---------------------------- | ------------------------------------------------------- |
| bom 8 (prodi:bom-8) | type (rdf:type)              | Bill of Material (BOM) (pv:BillOfMaterial)              |
| bom 8 (prodi:bom-8) | label (rdfs:label)           | MotoSync QuantumWave                                    |
| bom 8 (prodi:bom-8) | name (pv:name)               | MotoSync QuantumWave                                    |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 G625 4620445 (prodi:bom-part-8-G625-4620445) |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 L275 4377274 (prodi:bom-part-8-L275-4377274) |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 L781 7008508 (prodi:bom-part-8-L781-7008508) |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 W232 7656495 (prodi:bom-part-8-W232-7656495) |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 Z322 3336300 (prodi:bom-part-8-Z322-3336300) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly calculates the average unit cost of hardware parts for each Bill-of-Material, orders the results in descending order, and returns the BOM with the highest average. The query uses the appropriate classes and properties, and the answer matches the query result. All requirements are met, and the output is correct and complete.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX prodi: <http://ld.company.org/prod-instances/>
SELECT ?dept ?deptLabel WHERE {
  ?dept pv:responsibleFor prodi:hw-M558-2275045 .
  OPTIONAL {
    ?dept rdfs:label ?deptLabel
  }
}

The department responsible for the Sensor Switch M558-2275045 is Data Services (IRI: prodi:dept-41622).

Which department is responsible for the Sensor Switch M558-2275045?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 department is responsible for the Sensor Switch M558-2275045?

[Assistant]
Let's break down the question:

1. The entity is "Sensor Switch M558-2275045" (likely a product or part).
2. The property is "responsible department" (which department is responsible for this item).

First, I will search for the entity "Sensor Switch M558-2275045" in the knowledge graph to find its IRI.

[Tool]
Top 10 entity alternatives:
1. prod cat Sensor (prodi:prod-cat-Sensor): is a Product Category
2. prod cat Switch (prodi:prod-cat-Switch): is a Product Category

[Assistant]
The search for "Sensor Switch M558-2275045" did not return an exact match for the product, but only for broader product categories: "prod cat Sensor" and "prod cat Switch".

Next, I will try searching for just "M558-2275045" to see if the product is listed under a different or shorter name.

[Tool] No entity items found

[Assistant]
The search for "M558-2275045" did not return any entity either. It's possible that the product is listed under a slightly different name or code, or that the knowledge graph does not contain this specific product.

As a next step, I will search for "Sensor Switch" to see if there are any entities that match this combination, which might help identify the correct product or a close match.

[Tool]
Top 10 entity alternatives:
1. prod cat Sensor (prodi:prod-cat-Sensor): is a Product Category
2. prod cat Switch (prodi:prod-cat-Switch): is a Product Category

[Assistant]
The search for "Sensor Switch" also only returns product categories, not a specific product or part with the code "M558-2275045".

Since the specific product entity cannot be found in the knowledge graph, I am unable to construct a SPARQL query to determine which department is responsible for it.

I will now stop and explain that the entity could not be found, and thus the question cannot be answered with the current data.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The explanation correctly identifies that the specific entity 'Sensor Switch M558-2275045' was not found in the knowledge graph, which is a valid reason for not being able to answer the question. However, the SPARQL query could be improved by considering alternative labels, partial matches, or similar products (e.g., using FILTER or regex to match substrings), as the product might be listed under a slightly different label. Additionally, the query should attempt to identify the property that links products to departments (the current variable '?responsibleProperty' is too generic and may not match any actual property in the graph). Refining the query to search for similar labels and investigating the correct property for department responsibility could yield better results.

[Assistant]
Thank you for the feedback. I agree that the approach can be improved by:

1. Searching for entities with labels that partially match "M558-2275045" or "Sensor Switch" using regex or substring matching.
2. Investigating which property in the knowledge graph links products to departments (e.g., "responsible department", "managed by", etc.), rather than using a generic variable.

Step 1: I will list entities with labels containing "M558" or "2275045" to find possible matches.

[Tool]
Got 1 row and 2 columns:
| product                                 | label                        |
| --------------------------------------- | ---------------------------- |
| hw M558 2275045 (prodi:hw-M558-2275045) | M558-2275045 - Sensor Switch |

[Assistant]
I found an entity with the label "M558-2275045 - Sensor Switch" and the IRI prodi:hw-M558-2275045. This matches the product in question.

Step 2: Next, I need to determine which property links this product to a department. I will list all properties for this entity to identify the relevant one.

[Tool]
Got 14 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                                   | object                                                                                |
| --------------------------------------- | ------------------------------------------ | -------------------------------------------------------------------------------------------------------------------- |
| hw M558 2275045 (prodi:hw-M558-2275045) | type (rdf:type)                            | Hardware (pv:Hardware)                                                                                |
| hw M558 2275045 (prodi:hw-M558-2275045) | label (rdfs:label)                         | M558-2275045 - Sensor Switch                                                                                |
| hw M558 2275045 (prodi:hw-M558-2275045) | has category (pv:hasCategory)              | prod cat Sensor (prodi:prod-cat-Sensor)                                                                              |
| hw M558 2275045 (prodi:hw-M558-2275045) | compatible product (pv:compatibleProduct)  | hw A181 1118563 (prodi:hw-A181-1118563)                                                                              |
| hw M558 2275045 (prodi:hw-M558-2275045) | name (pv:name)                             | Sensor Switch                                                                                |
| hw M558 2275045 (prodi:hw-M558-2275045) | ID (pv:id)                                 | M558-2275045                                                                                |
| hw M558 2275045 (prodi:hw-M558-2275045) | has product manager (pv:hasProductManager) | empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) |
| hw M558 2275045 (prodi:hw-M558-2275045) | price (pv:price)                           | price hw M558 2275045 EUR (prodi:price-hw-M558-2275045-EUR)                                                          |
| hw M558 2275045 (prodi:hw-M558-2275045) | depth (mm) (pv:depth_mm)                   | 16 (xsd:int)                                                                                |
| hw M558 2275045 (prodi:hw-M558-2275045) | supplier (pv:hasSupplier)                  | suppl e157b0e5 1085 4999 83a0 02a46d7a8994 (prodi:suppl-e157b0e5-1085-4999-83a0-02a46d7a8994)                        |
| ...                                     | ...                                        | ...                                                                                |

[Assistant]
From the listed properties, there is no direct property like "responsible department", but there is a property called pv:hasProductManager, which links to an employee. The department might be linked via the product manager or there could be another property.

To check further, I will look at all properties related to "department" in the knowledge graph to see if there is a direct link from the product or via the product manager.

[Tool]
Top 10 property alternatives:
1. area of expertise (pv:areaOfExpertise): The product category agent is expert for., has range Product Category, has domain Agent
2. label (rdfs:label)
3. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
4. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
5. has manager (pv:hasManager): The manager of the employee., has domain Employee, has range Manager
6. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product
7. sub Class Of (rdfs:subClassOf)
8. quantity (pv:quantity): The quantity needed., has domain BOM Part
9. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
10. type (rdf:type)

[Assistant]
The property pv:responsibleFor is described as "The product for which a department is responsible" and has domain Department and range Product. This means the relationship is from Department to Product.

To find the responsible department for "Sensor Switch M558-2275045", I need to query for departments (?dept) such that ?dept pv:responsibleFor prodi:hw-M558-2275045.

I will now construct and execute the SPARQL query to find the responsible department, including optional labels for readability.

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 14 for token OPTIONAL with content 'OPTIONAL' (the input most likely does not follow the grammar)

[Assistant]
There was a syntax error in my previous query because OPTIONAL cannot be used in the SELECT clause. I will correct the query by moving the OPTIONAL clause into the WHERE block and selecting the department and its label.

Here is the corrected query:

[Tool]
Got 1 row and 2 columns:
| dept                          | deptLabel     |
| ----------------------------- | ------------- |
| dept 41622 (prodi:dept-41622) | Data Services |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and follows all the required rules. It returns the IRI of the responsible department and optionally its label. The answer matches the query result, and the query is executed against the correct knowledge graph. No further refinement is needed.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX prodi: <http://ld.company.org/prod-instances/>
SELECT DISTINCT ?supplier ?label WHERE {
  ?product pv:hasCategory prodi:prod-cat-Compensator .
  ?product pv:hasSupplier ?supplier .
  OPTIONAL {
    ?supplier rdfs:label ?label
  }
}

Got 90 rows and 2 columns, showing the first 5 and last 5 rows below:
| supplier                                                                                | label                                      |
| --------------------------------------------------------------------------------------------- | ------------------------------------------ |
| suppl 034022f5 5327 45c2 aaff 524b1be2fbd5 (prodi:suppl-034022f5-5327-45c2-aaff-524b1be2fbd5) | Drake Ltd (Honduras)                       |
| suppl 06034b22 8e1b 435f 902e 88739f77d86a (prodi:suppl-06034b22-8e1b-435f-902e-88739f77d86a) | Lee and Sons (Brazil)                      |
| suppl 06d152e4 f062 46da b6be 750b192a5a4b (prodi:suppl-06d152e4-f062-46da-b6be-750b192a5a4b) | Barnes LLC (Pakistan)                      |
| suppl 07335cfb 9bbc 4be5 b546 bdd8af104e7e (prodi:suppl-07335cfb-9bbc-4be5-b546-bdd8af104e7e) | Guerrero, Sutton and Lucas (United States) |
| suppl 0817f6f5 8011 4c46 aeab ba89def6df14 (prodi:suppl-0817f6f5-8011-4c46-aeab-ba89def6df14) | Daniels Group (Antigua and Barbuda)        |
| ...                                                                                | ...                                        |
| suppl f78ea3cf fe86 4b17 ba41 96dd934e043e (prodi:suppl-f78ea3cf-fe86-4b17-ba41-96dd934e043e) | Powell-Nguyen (United Kingdom)             |
| suppl f8337d39 2d97 423a 9f94 35a45ee9ade6 (prodi:suppl-f8337d39-2d97-423a-9f94-35a45ee9ade6) | May, Ruiz and Butler (Turkey)              |
| suppl f9bfd642 7152 407c 8158 d53fbc55f45b (prodi:suppl-f9bfd642-7152-407c-8158-d53fbc55f45b) | Harris, Graves and Gonzalez (Turkey)       |
| suppl fbc53ab7 1c1e 41c8 afe2 44b405858cda (prodi:suppl-fbc53ab7-1c1e-41c8-afe2-44b405858cda) | Harris, Wright and Morales (Japan)         |
| suppl fdd83431 425f 4291 b8e4 f08805b6b89d (prodi:suppl-fdd83431-425f-4291-b8e4-f08805b6b89d) | Thomas-Jenkins (Bangladesh)                |

The suppliers available to deliver Compensators are listed below (with their IRIs and, where available, their labels):

- prodi:suppl-034022f5-5327-45c2-aaff-524b1be2fbd5 (Drake Ltd (Honduras))
- prodi:suppl-06034b22-8e1b-435f-902e-88739f77d86a (Lee and Sons (Brazil))
- prodi:suppl-06d152e4-f062-46da-b6be-750b192a5a4b (Barnes LLC (Pakistan))
- prodi:suppl-07335cfb-9bbc-4be5-b546-bdd8af104e7e (Guerrero, Sutton and Lucas (United States))
- prodi:suppl-0817f6f5-8011-4c46-aeab-ba89def6df14 (Daniels Group (Antigua and Barbuda))
- ...

There are a total of 90 suppliers. Please refer to the SPARQL query result for the full list.

Which supplier are available to deliver Compensators?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 supplier are available to deliver Compensators?

[Assistant]
Let's break down the question:

1. Entities: "Compensators" (likely a product or product type), "supplier" (entities that deliver/provide products).
2. Properties: "deliver", "available to deliver", "supplier of", "provides", "offers", etc.

Step 1: Search for the entity "Compensators" to identify its IRI in the knowledge graph.

[Tool] No entity items found

[Assistant]
The search for the entity "Compensators" did not return any results. This could mean that the product might be listed under a different name, or it might be a subclass or type of another entity.

Next, I will try searching for the singular form "Compensator" to see if that yields any results.

[Tool]
Top 10 entity alternatives:
1. prod cat Compensator (prodi:prod-cat-Compensator): is a Product Category

[Assistant]
I found an entity called "prod cat Compensator" (prodi:prod-cat-Compensator), which is a Product Category. This is likely the correct entity representing "Compensators".

Next, I need to identify which suppliers are available to deliver products in this category. To do this, I need to find the property that links suppliers to the products or product categories they deliver (e.g., "delivers", "supplies", "offers", etc.).

I will search for properties related to "deliver" to find the correct property.

[Tool]
Top 10 property alternatives:
1. address text (pv:addressText): The address text., has domain Agent
2. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
3. comment (rdfs:comment)
4. quantity (pv:quantity): The quantity needed., has domain BOM Part
5. email (pv:email): The e-mail of an agent., has domain Agent
6. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product
7. created (dct:created)
8. license (<http://creativecommons.org/ns#license>)
9. type (rdf:type)
10. phone number (pv:phone): has domain Agent, A phone number.

[Assistant]
The property pv:hasSupplier ("The supplier of a product") seems relevant. Its domain is Product and its range is Supplier. This suggests that products are linked to their suppliers using this property.

Since "prod cat Compensator" is a Product Category, I need to check if products of this category are linked to suppliers, or if the category itself is linked directly to suppliers.

I'll first check if there are any products that belong to the "prod cat Compensator" category and then see if those products have suppliers via pv:hasSupplier.

[Tool]
Top 10 property alternatives:
1. label (rdfs:label)
2. name (pv:name): The name of something.
3. type (rdf:type)

No other items found

[Assistant]
There are no direct properties linking the product category "Compensator" to products, except for basic properties like label, name, and type.

This suggests that products themselves might have a property indicating their category. I will search for properties of a typical product entity that might link it to its category, such as "category", "product category", or similar.

First, I need to find an example product entity. I'll search for entities related to "Compensator" that might represent individual products.

[Tool]
Top 10 entity alternatives:
1. prod cat Compensator (prodi:prod-cat-Compensator): is a Product Category

[Tool]
Top 10 entity alternatives:
1. Product (pv:Product): Anything that we make and/or sell.
2. Product Category (pv:ProductCategory): The category of a product.
3. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
4. has product manager (pv:hasProductManager): The employee acting as the product manager of the product., has range Employee, has domain Product
5. product outlined svg?color=#D6AF00&format=svg (<https://api.iconify.design/ant-design/product-outlined.svg?color=%23D6AF00&format=svg>)
6. Products - Integration (prodi:)
7. pv: Products - Vocab (pv:): Example vocabulary modeled from a simple sentence about products and services.

[Tool]
Top 10 property alternatives:
1. label (rdfs:label)
2. type (rdf:type)
3. is Defined By (rdfs:isDefinedBy)
4. depiction (foaf:depiction)
5. comment (rdfs:comment)

No other items found

[Tool]
Top 10 property alternatives:
1. is Defined By (rdfs:isDefinedBy)
2. label (rdfs:label)
3. comment (rdfs:comment)
4. type (rdf:type)
5. depiction (foaf:depiction)

No other items found

[Tool]
Top 10 property alternatives:
1. label (rdfs:label)
2. type (rdf:type)
3. comment (rdfs:comment)
4. is Defined By (rdfs:isDefinedBy)
5. depiction (foaf:depiction)

No other items found

[Tool]
Top 10 property alternatives:
1. has category (pv:hasCategory): The category name of a product., has range Product Category, has domain Product
2. label (rdfs:label)
3. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
4. type (rdf:type)
5. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
6. vocabulary (void:vocabulary)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. sub Class Of (rdfs:subClassOf)
10. is Defined By (rdfs:isDefinedBy)

[Tool]
Got 110 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                      | object                                            |
| --------------------------------------- | ----------------------------- | ------------------------------------------------- |
| hw A145 1240844 (prodi:hw-A145-1240844) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw A181 1118563 (prodi:hw-A181-1118563) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw A391 9508821 (prodi:hw-A391-9508821) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw A607 3251492 (prodi:hw-A607-3251492) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw A994 9085459 (prodi:hw-A994-9085459) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw A998 9941987 (prodi:hw-A998-9941987) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw B232 9941304 (prodi:hw-B232-9941304) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw B625 4480024 (prodi:hw-B625-4480024) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw B825 7596233 (prodi:hw-B825-7596233) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw B937 9245602 (prodi:hw-B937-9245602) | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| ...                                     | ...                           | ...                                               |

[Tool]
Got 1,000 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                  | object                                                                                |
| --------------------------------------- | ------------------------- | --------------------------------------------------------------------------------------------- |
| hw J785 9314350 (prodi:hw-J785-9314350) | supplier (pv:hasSupplier) | suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) |
| hw V156 6277722 (prodi:hw-V156-6277722) | supplier (pv:hasSupplier) | suppl f76eb805 4d84 4b4b 9aa3 95c287be41d0 (prodi:suppl-f76eb805-4d84-4b4b-9aa3-95c287be41d0) |
| hw W769 8151254 (prodi:hw-W769-8151254) | supplier (pv:hasSupplier) | suppl 4d849ba4 b932 4ffc 8b52 61a704dddf0b (prodi:suppl-4d849ba4-b932-4ffc-8b52-61a704dddf0b) |
| hw B918 9468392 (prodi:hw-B918-9468392) | supplier (pv:hasSupplier) | suppl 47528cbf c41b 4897 b917 6f4c1394fe1f (prodi:suppl-47528cbf-c41b-4897-b917-6f4c1394fe1f) |
| hw H374 8481414 (prodi:hw-H374-8481414) | supplier (pv:hasSupplier) | suppl 9a27c6be 84c6 4fe8 a671 d9d6a5ec7f6a (prodi:suppl-9a27c6be-84c6-4fe8-a671-d9d6a5ec7f6a) |
| hw K334 8882985 (prodi:hw-K334-8882985) | supplier (pv:hasSupplier) | suppl 06d152e4 f062 46da b6be 750b192a5a4b (prodi:suppl-06d152e4-f062-46da-b6be-750b192a5a4b) |
| hw L557 1467804 (prodi:hw-L557-1467804) | supplier (pv:hasSupplier) | suppl 4b796fba c152 4137 b01d fce80aef6e3c (prodi:suppl-4b796fba-c152-4137-b01d-fce80aef6e3c) |
| hw O875 5580798 (prodi:hw-O875-5580798) | supplier (pv:hasSupplier) | suppl fdd83431 425f 4291 b8e4 f08805b6b89d (prodi:suppl-fdd83431-425f-4291-b8e4-f08805b6b89d) |
| hw T808 9704137 (prodi:hw-T808-9704137) | supplier (pv:hasSupplier) | suppl 8f607810 ca93 4274 9c27 d0a8dcba7c4a (prodi:suppl-8f607810-ca93-4274-9c27-d0a8dcba7c4a) |
| hw J824 9483042 (prodi:hw-J824-9483042) | supplier (pv:hasSupplier) | suppl 33da751a 1358 4530 b0e5 e3b9a509e952 (prodi:suppl-33da751a-1358-4530-b0e5-e3b9a509e952) |
| ...                                     | ...                       | ...                                                                                |

[Tool]
Got 90 rows and 1 column, showing the first 5 and last 5 rows below:
| supplier                                                                                |
| --------------------------------------------------------------------------------------------- |
| suppl 034022f5 5327 45c2 aaff 524b1be2fbd5 (prodi:suppl-034022f5-5327-45c2-aaff-524b1be2fbd5) |
| suppl 06034b22 8e1b 435f 902e 88739f77d86a (prodi:suppl-06034b22-8e1b-435f-902e-88739f77d86a) |
| suppl 06d152e4 f062 46da b6be 750b192a5a4b (prodi:suppl-06d152e4-f062-46da-b6be-750b192a5a4b) |
| suppl 07335cfb 9bbc 4be5 b546 bdd8af104e7e (prodi:suppl-07335cfb-9bbc-4be5-b546-bdd8af104e7e) |
| suppl 0817f6f5 8011 4c46 aeab ba89def6df14 (prodi:suppl-0817f6f5-8011-4c46-aeab-ba89def6df14) |
| ...                                                                                |
| suppl f78ea3cf fe86 4b17 ba41 96dd934e043e (prodi:suppl-f78ea3cf-fe86-4b17-ba41-96dd934e043e) |
| suppl f8337d39 2d97 423a 9f94 35a45ee9ade6 (prodi:suppl-f8337d39-2d97-423a-9f94-35a45ee9ade6) |
| suppl f9bfd642 7152 407c 8158 d53fbc55f45b (prodi:suppl-f9bfd642-7152-407c-8158-d53fbc55f45b) |
| suppl fbc53ab7 1c1e 41c8 afe2 44b405858cda (prodi:suppl-fbc53ab7-1c1e-41c8-afe2-44b405858cda) |
| suppl fdd83431 425f 4291 b8e4 f08805b6b89d (prodi:suppl-fdd83431-425f-4291-b8e4-f08805b6b89d) |

[Tool]
Got 90 rows and 2 columns, showing the first 5 and last 5 rows below:
| supplier                                                                                | label                                      |
| --------------------------------------------------------------------------------------------- | ------------------------------------------ |
| suppl 034022f5 5327 45c2 aaff 524b1be2fbd5 (prodi:suppl-034022f5-5327-45c2-aaff-524b1be2fbd5) | Drake Ltd (Honduras)                       |
| suppl 06034b22 8e1b 435f 902e 88739f77d86a (prodi:suppl-06034b22-8e1b-435f-902e-88739f77d86a) | Lee and Sons (Brazil)                      |
| suppl 06d152e4 f062 46da b6be 750b192a5a4b (prodi:suppl-06d152e4-f062-46da-b6be-750b192a5a4b) | Barnes LLC (Pakistan)                      |
| suppl 07335cfb 9bbc 4be5 b546 bdd8af104e7e (prodi:suppl-07335cfb-9bbc-4be5-b546-bdd8af104e7e) | Guerrero, Sutton and Lucas (United States) |
| suppl 0817f6f5 8011 4c46 aeab ba89def6df14 (prodi:suppl-0817f6f5-8011-4c46-aeab-ba89def6df14) | Daniels Group (Antigua and Barbuda)        |
| ...                                                                                | ...                                        |
| suppl f78ea3cf fe86 4b17 ba41 96dd934e043e (prodi:suppl-f78ea3cf-fe86-4b17-ba41-96dd934e043e) | Powell-Nguyen (United Kingdom)             |
| suppl f8337d39 2d97 423a 9f94 35a45ee9ade6 (prodi:suppl-f8337d39-2d97-423a-9f94-35a45ee9ade6) | May, Ruiz and Butler (Turkey)              |
| suppl f9bfd642 7152 407c 8158 d53fbc55f45b (prodi:suppl-f9bfd642-7152-407c-8158-d53fbc55f45b) | Harris, Graves and Gonzalez (Turkey)       |
| suppl fbc53ab7 1c1e 41c8 afe2 44b405858cda (prodi:suppl-fbc53ab7-1c1e-41c8-afe2-44b405858cda) | Harris, Wright and Morales (Japan)         |
| suppl fdd83431 425f 4291 b8e4 f08805b6b89d (prodi:suppl-fdd83431-425f-4291-b8e4-f08805b6b89d) | Thomas-Jenkins (Bangladesh)                |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and complete for the user's question. It retrieves all suppliers that are associated with products in the 'Compensator' category, returning their IRIs and optionally their labels. The query is executed and returns the expected results. No further refinement is needed.