PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?supplier ?supplierLabel ( AVG( ?reliability ) AS ?avgReliability ) WHERE {
  ?product pv:hasSupplier ?supplier .
  ?product pv:reliabilityIndex ?reliability .
  OPTIONAL {
    ?supplier rdfs:label ?supplierLabel
  }
}
GROUP BY ?supplier ?supplierLabel
ORDER BY DESC ( ?avgReliability )
LIMIT 5

The top 5 suppliers with the best average reliability over their products are:
1. Cooper and Sons (Switzerland) with an average reliability of 0.962
2. Adkins, Lopez and Boyd (Switzerland) with an average reliability of 0.962
3. Grant-Nelson (Australia) with an average reliability of 0.951
4. Wagner-Ramirez (Ireland) with an average reliability of 0.945
5. Larsen-Martinez (Germany) with an average reliability of 0.942

What are the top 5 suppliers with best average reliability over their products.

[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 are the top 5 suppliers with best average reliability over their products.

[Assistant]
To answer this question, I need to identify the entities representing suppliers and their products, as well as the property representing the reliability of products. Then I will calculate the average reliability for each supplier over their products and select the top 5 suppliers with the best average reliability.

Step 1: Search for entities related to suppliers.

[Tool]
Top 10 entity alternatives:
1. Supplier (pv:Supplier): The Supplier of some item(s).
2. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier

[Assistant]
I found an entity "Supplier" (pv:Supplier) and a property "supplier" (pv:hasSupplier) which relates a product to its supplier.

Step 2: Search for properties related to reliability for products.

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

No other items found

[Tool]
Top 10 property alternatives:
1. has reliability index (pv:reliabilityIndex): A computed KPI to have an reliablity indicator in the context of a supply chain., has domain Hardware
2. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
3. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
4. quantity (pv:quantity): The quantity needed., has domain BOM Part
5. is Defined By (rdfs:isDefinedBy)
6. type (rdf:type)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. range (rdfs:range)
10. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country

[Assistant]
I found a property "has reliability index" (pv:reliabilityIndex) which is a computed KPI to have a reliability indicator in the context of a supply chain. It has domain Hardware, but it might be used for products as well.

Step 3: Check if products have the property pv:hasSupplier and pv:reliabilityIndex. I will look for triples with these properties.

[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 912 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                                    | object              |
| --------------------------------------- | ------------------------------------------- | ------------------- |
| hw J785 9314350 (prodi:hw-J785-9314350) | has reliability index (pv:reliabilityIndex) | 0.745 (xsd:decimal) |
| hw V156 6277722 (prodi:hw-V156-6277722) | has reliability index (pv:reliabilityIndex) | 0.633 (xsd:decimal) |
| hw W769 8151254 (prodi:hw-W769-8151254) | has reliability index (pv:reliabilityIndex) | 0.942 (xsd:decimal) |
| hw B918 9468392 (prodi:hw-B918-9468392) | has reliability index (pv:reliabilityIndex) | 0.921 (xsd:decimal) |
| hw H374 8481414 (prodi:hw-H374-8481414) | has reliability index (pv:reliabilityIndex) | 0.929 (xsd:decimal) |
| hw K334 8882985 (prodi:hw-K334-8882985) | has reliability index (pv:reliabilityIndex) | 0.544 (xsd:decimal) |
| hw O875 5580798 (prodi:hw-O875-5580798) | has reliability index (pv:reliabilityIndex) | 0.661 (xsd:decimal) |
| hw J824 9483042 (prodi:hw-J824-9483042) | has reliability index (pv:reliabilityIndex) | 0.641 (xsd:decimal) |
| hw U990 5234138 (prodi:hw-U990-5234138) | has reliability index (pv:reliabilityIndex) | 0.731 (xsd:decimal) |
| hw V488 1866672 (prodi:hw-V488-1866672) | has reliability index (pv:reliabilityIndex) | 0.895 (xsd:decimal) |
| ...                                     | ...                                         | ...                 |

[Assistant]
Products (hardware) have the property pv:hasSupplier linking to suppliers and the property pv:reliabilityIndex representing the reliability index.

Step 4: Construct a SPARQL query to calculate the average reliability index for each supplier over their products and select the top 5 suppliers with the best average reliability. I will also include optional labels for better readability.

[Tool]
Got 5 rows and 3 columns:
| supplier                                                                                | supplierLabel                        | avgReliability      |
| --------------------------------------------------------------------------------------------- | ------------------------------------ | ------------------- |
| suppl 2a51afd9 a3de 45ee 8ada b74203fed37b (prodi:suppl-2a51afd9-a3de-45ee-8ada-b74203fed37b) | Cooper and Sons (Switzerland)        | 0.962 (xsd:decimal) |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | Adkins, Lopez and Boyd (Switzerland) | 0.962 (xsd:decimal) |
| suppl 11f1284a d6f0 4822 b716 3e70d1fb91df (prodi:suppl-11f1284a-d6f0-4822-b716-3e70d1fb91df) | Grant-Nelson (Australia)             | 0.951 (xsd:decimal) |
| suppl 888698ef ad70 4022 9624 4dc111f56c01 (prodi:suppl-888698ef-ad70-4022-9624-4dc111f56c01) | Wagner-Ramirez (Ireland)             | 0.945 (xsd:decimal) |
| suppl 0d183bba b1df 4c41 be10 c0896378b406 (prodi:suppl-0d183bba-b1df-4c41-be10-c0896378b406) | Larsen-Martinez (Germany)            | 0.942 (xsd:decimal) |

[Tool] Stopped generation process


PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?areaOfExpertise ( COUNT( ?agent ) AS ?count ) WHERE {
  ?agent pv:areaOfExpertise ?areaOfExpertise
}
GROUP BY ?areaOfExpertise
ORDER BY DESC ( ?count )
LIMIT 3

Got 3 rows and 2 columns:
| areaOfExpertise                                   | count        |
| ------------------------------------------------- | ------------ |
| prod cat Compensator (prodi:prod-cat-Compensator) | 11 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | 9 (xsd:int)  |
| prod cat Crystal (prodi:prod-cat-Crystal)         | 9 (xsd:int)  |

The most relevant area of expertise among our products, inferred from the areas of expertise of agents, is 'Compensator' with 11 agents expert in this area. The next top two areas of expertise are 'Breaker' and 'Crystal', each with 9 agents expert in these areas. There is no explicit skill data available in the knowledge graph to identify the top three skills.

Which area of expertise is most relevant among our products, what are the top three skills?

[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 area of expertise is most relevant among our products, what are the top three skills?

[Assistant]
The user question is asking about the area of expertise that is most relevant among "our products" and the top three skills related to that area of expertise. To answer this, I need to:

1. Identify the products in the knowledge graph.
2. Determine the areas of expertise associated with these products.
3. Find the skills related to these areas of expertise.
4. Rank or identify the top three skills.

First, I will search for entities related to "product" to understand how products are represented in the knowledge graph. Then I will explore properties related to expertise and skills linked to these products.

[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.

[Assistant] The entity "Product" (pv:Product) represents anything that we make and/or sell. This is likely the class for our products. Next, I will look for properties related to "Product" that might link to areas of expertise or skills. I will search for properties of the entity pv:Product to find relevant attributes.

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

No other items found

[Assistant] There are no direct properties related to "expertise" for the entity pv:Product. I will try searching for properties related to "skill" for the entity pv:Product to see if there are any links to skills.

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

No other items found

[Assistant] There are no direct properties related to "skill" for the entity pv:Product either. I will try a broader search for properties related to "expertise" in the knowledge graph to see if there are any relevant properties that might link products to expertise or skills.

[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. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product
4. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
5. vocabulary (void:vocabulary)
6. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
7. name (foaf:name):

8. name (pv:name): The name of something.
9. has manager (pv:hasManager): The manager of the employee., has domain Employee, has range Manager
10. created (dct:created)

[Assistant] There is a property "area of expertise" (pv:areaOfExpertise) which has the domain Agent and range Product Category. This suggests that areas of expertise are linked to agents, not directly to products. I will now check if products have a category and if that category can be linked to an area of expertise. I will search for properties of pv:Product related to "category".

[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

[Assistant] There are no direct properties linking products to categories. I will now search for the class "Product Category" (pv:ProductCategory) and see if it has any properties related to skills or expertise.

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

No other items found

[Assistant] No direct properties related to skills for ProductCategory either. I will now try to find entities related to "skill" to understand how skills are represented in the knowledge graph.

[Tool] No entity items found

[Assistant] There are no entities explicitly named "skill" in the knowledge graph. I will try searching for "expertise" entities to see if there is a concept related to expertise or skills.

[Tool]
Top 10 entity alternatives:
1. area of expertise (pv:areaOfExpertise): The product category agent is expert for., has range Product Category, has domain Agent

[Assistant]
The only relevant entity related to expertise is the property "area of expertise" (pv:areaOfExpertise) linking Agent to Product Category. Since the question is about the area of expertise most relevant among products and the top three skills, and we have found that area of expertise is linked to agents and product categories, I will try to find the top three areas of expertise associated with products or agents related to products.

I will now try to find agents linked to products and their areas of expertise. I will start by listing some products and see if there are agents linked to them.

[Tool]
Got 5 rows and 3 columns:
| subject              | property                         | object                                                                                |
| -------------------- | -------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| Product (pv:Product) | type (rdf:type)                  | Class (owl:Class)                                                                                |
| Product (pv:Product) | label (rdfs:label)               | Product (en)                                                                                |
| Product (pv:Product) | is Defined By (rdfs:isDefinedBy) | pv: Products - Vocab (pv:)                                                                                |
| Product (pv:Product) | comment (rdfs:comment)           | Anything that we make and/or sell. (en)                                                                                |
| Product (pv:Product) | depiction (foaf:depiction)       | product outlined svg?color=#D6AF00&format=svg (<https://api.iconify.design/ant-design/product-outlined.svg?color=%23D6AF00&format=svg>) |

[Assistant] The class pv:Product is defined but no instances of products were listed in this query. I will try to find instances of products by querying for entities of type pv:Product.

[Tool] Got no rows and 1 columns

[Assistant]
There are no instances of products in the knowledge graph. Without product instances, it is not possible to determine the area of expertise most relevant among products or the top three skills related to them.

I will now check if there are any agents and their areas of expertise to see if we can infer something from that.

[Tool]
Got 10 rows and 2 columns:
| agent                                                                                | areaOfExpertise                                 |
| -------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------- |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>)             | prod cat Breaker (prodi:prod-cat-Breaker)       |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>)             | prod cat Coil (prodi:prod-cat-Coil)             |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>)             | prod cat Meter (prodi:prod-cat-Meter)           |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>)             | prod cat Strain (prodi:prod-cat-Strain)         |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>)             | prod cat Transducer (prodi:prod-cat-Transducer) |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | prod cat Gauge (prodi:prod-cat-Gauge)           |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | prod cat Inductor (prodi:prod-cat-Inductor)     |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | prod cat Resonator (prodi:prod-cat-Resonator)   |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | prod cat Sensor (prodi:prod-cat-Sensor)         |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | prod cat Transistor (prodi:prod-cat-Transistor) |

[Assistant]
There are agents with areas of expertise linked to product categories. The product categories include Breaker, Coil, Meter, Strain, Transducer, Gauge, Inductor, Resonator, Sensor, and Transistor.

Next, I will try to find skills related to these areas of expertise or product categories. I will check if these product categories have any properties related to skills. I will start with one product category, e.g., "prod cat Breaker" (prodi:prod-cat-Breaker), and look for properties.

[Tool]
Got 3 rows and 3 columns:
| subject                                   | property           | object                                |
| ----------------------------------------- | ------------------ | ------------------------------------- |
| prod cat Breaker (prodi:prod-cat-Breaker) | type (rdf:type)    | Product Category (pv:ProductCategory) |
| prod cat Breaker (prodi:prod-cat-Breaker) | label (rdfs:label) | Breaker                               |
| prod cat Breaker (prodi:prod-cat-Breaker) | name (pv:name)     | Breaker                               |

[Assistant] The product category "Breaker" has no direct properties related to skills. I will now try to find if there are any skills linked to agents. I will search for properties of an agent to see if there is any property related to skills. I will use the agent "empl Adolfina Hoch@company org" as an example.

[Tool] Constraint "prodi:empl-Adolfina.Hoch@company.org" for subject position is not a valid IRI. IRIs can be given in prefixed form, like "wd:Q937", as URIs, like "http://www.wikidata.org/entity/Q937", or in full form, like "<http://www.wikidata.org/entity/Q937>".

[Assistant] The agent IRI was not correctly formatted. I will use angle brackets to enclose the full IRI for the agent "empl Adolfina Hoch@company org" and try again. The IRI is <http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>.

[Tool]
Got 13 rows and 3 columns, showing the first 10 rows below:
| subject                                                                                | property                               | object                                                                                |
| -------------------------------------------------------------------------------------------------------- | -------------------------------------- | ---------------------------------------------------------------------------------------------------------------- |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | type (rdf:type)                        | Employee (pv:Employee)                                                                                |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | label (rdfs:label)                     | Adolfina Hoch                                                                                |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | name (pv:name)                         | Adolfina Hoch                                                                                |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | area of expertise (pv:areaOfExpertise) | prod cat Transducer (prodi:prod-cat-Transducer)                                                                  |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | email (pv:email)                       | Adolfina.Hoch@company.org                                                                                |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | member of (pv:memberOf)                | dept 22183 (prodi:dept-22183)                                                                                |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | has manager (pv:hasManager)            | empl Franz Kornhaeusel@company org (<http://ld.company.org/prod-instances/empl-Franz.Kornhaeusel%40company.org>) |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | phone number (pv:phone)                | +49-109-5719002                                                                                |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | address text (pv:addressText)          | Motzstraße 26, 13611 Gartz                                                                                |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>) | area of expertise (pv:areaOfExpertise) | prod cat Breaker (prodi:prod-cat-Breaker)                                                                        |
| ...                                                                                | ...                                    | ...                                                                                |

[Assistant] The agent "Adolfina Hoch" has multiple areas of expertise linked to product categories but no direct properties related to skills. I will now try to find if there are any skills linked to product categories or agents in general by searching for properties related to "skill" 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. type (rdf:type)
3. quantity (pv:quantity): The quantity needed., has domain BOM Part
4. created (dct:created)
5. range (rdfs:range)
6. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
7. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
8. vocabulary (void:vocabulary)
9. name (foaf:name):

10. name (pv:name): The name of something.

[Assistant]
There is no direct property related to "skill" in the knowledge graph. Since the question asks for the top three skills related to the most relevant area of expertise among products, and we have found that areas of expertise are linked to agents and product categories, but no explicit skills are found, it seems the knowledge graph does not contain explicit skill data.

I will now summarize the findings:
- Products are represented by pv:Product but no instances found.
- Areas of expertise are linked to agents and product categories via pv:areaOfExpertise.
- Agents have areas of expertise linked to product categories.
- No explicit skills are found linked to products, product categories, or agents.

Given this, the best we can do is to identify the top three most common areas of expertise (product categories) among agents as a proxy for relevant expertise among products.

I will write a query to count the occurrences of each area of expertise among agents and return the top three.

[Tool]
Got 3 rows and 2 columns:
| areaOfExpertise                                   | count        |
| ------------------------------------------------- | ------------ |
| prod cat Compensator (prodi:prod-cat-Compensator) | 11 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | 9 (xsd:int)  |
| prod cat Crystal (prodi:prod-cat-Crystal)         | 9 (xsd:int)  |

[Tool] Stopped generation process


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?compatibleProduct ?compatibleProductLabel WHERE {
  prodi:hw-U990-5234138 pv:compatibleProduct ?compatibleProduct .
  OPTIONAL {
    ?compatibleProduct rdfs:label ?compatibleProductLabel
  }
}

The products compatible with the U990 LCD Inductor (prodi:hw-U990-5234138) are:
1. A360-3041803 - Inductor Transformer Warp
2. A509-5571891 - Multiplexer Inductor
3. F675-6890144 - Resistor Inductor Strain
4. I264-7314323 - Film Inductor Memristor
5. J178-7002767 - Flow LCD Transistor Transducer
6. S113-2439377 - LCD Potentiometer

What products 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 are compatible with the U990 LCD Inductor?

[Assistant] To answer the question "What products are compatible with the U990 LCD Inductor?", I will first search for the entity "U990 LCD Inductor" in the knowledge graph to identify its exact identifier. Then, I will look for properties related to compatibility or products associated with this entity.

[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] The entity "U990 LCD Inductor" seems to correspond to "hw U990 5234138" (prodi:hw-U990-5234138) which is a Hardware entity. Next, I will search for properties related to compatibility or products associated with this hardware entity. I will start by listing properties of this entity to find relevant ones.

[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] There is a property "compatible product" (pv:compatibleProduct) which indicates a compatible product and has domain and range as Product. This seems to be the relevant property to find products compatible with the U990 LCD Inductor hardware. I will now query for products that are compatible with the hardware entity prodi:hw-U990-5234138 using this property.

[Tool]
Got 6 rows and 2 columns:
| compatibleProduct                       | compatibleProductLabel                        |
| --------------------------------------- | --------------------------------------------- |
| hw A360 3041803 (prodi:hw-A360-3041803) | A360-3041803 - Inductor Transformer Warp      |
| hw A509 5571891 (prodi:hw-A509-5571891) | A509-5571891 - Multiplexer Inductor           |
| hw F675 6890144 (prodi:hw-F675-6890144) | F675-6890144 - Resistor Inductor Strain       |
| hw I264 7314323 (prodi:hw-I264-7314323) | I264-7314323 - Film Inductor Memristor        |
| hw J178 7002767 (prodi:hw-J178-7002767) | J178-7002767 - Flow LCD Transistor Transducer |
| hw S113 2439377 (prodi:hw-S113-2439377) | S113-2439377 - LCD Potentiometer              |

[Tool] Stopped generation process


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?coil ?label ?weight ?depth ?height ?width ( ( ?weight / ( ?depth * ?height * ?width ) ) AS ?density ) WHERE {
  ?coil pv:hasCategory prodi:prod-cat-Coil .
  ?coil pv:weight_g ?weight .
  ?coil pv:depth_mm ?depth .
  ?coil pv:height_mm ?height .
  ?coil pv:width_mm ?width .
  OPTIONAL {
    ?coil rdfs:label ?label
  }
}
ORDER BY DESC ( ?density )
LIMIT 1

The SPARQL query calculates the density for each coil by dividing weight by the product of depth, height, and width, then returns the coil with the highest density.

[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 coil has the highest density?

[Assistant]
To answer the question "Which coil has the highest density?", I need to identify entities related to "coil" and the property related to "density" in the knowledge graph. Then I will query for coils and their densities and find the one with the highest density.

Step 1: Search for entities related to "coil" in the knowledge graph.

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

[Assistant] There is an entity "prodi:prod-cat-Coil" which is a product category for Coil. Next, I will search for properties related to "density" to find the appropriate property to use in the query.

[Tool]
Top 10 property alternatives:
1. quantity (pv:quantity): The quantity needed., has domain BOM Part
2. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware
3. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
4. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
5. type (rdf:type)
6. amount (pv:amount): has domain Price, The amount.
7. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
8. lat (wgs84:lat)
9. is Defined By (rdfs:isDefinedBy)
10. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware

[Assistant] I did not find a direct property named "density" in the top search results. I will try to search for properties related to "density" specifically for the coil product category entity "prodi:prod-cat-Coil" to see if there is a more specific property.

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

No other items found

[Assistant] There is no direct property related to "density" for the coil product category entity. I will try to find instances of coils and check their properties to see if any property corresponds to density.

[Tool]
Got 3 rows and 3 columns:
| subject                             | property           | object                                |
| ----------------------------------- | ------------------ | ------------------------------------- |
| prod cat Coil (prodi:prod-cat-Coil) | type (rdf:type)    | Product Category (pv:ProductCategory) |
| prod cat Coil (prodi:prod-cat-Coil) | label (rdfs:label) | Coil                                  |
| prod cat Coil (prodi:prod-cat-Coil) | name (pv:name)     | Coil                                  |

[Assistant] The entity "prodi:prod-cat-Coil" is a product category but it does not list specific coil instances. I will try to find instances of products that belong to this category by searching for products with the property "category" or similar pointing to "prodi:prod-cat-Coil".

[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] There is a property "pv:hasCategory" which links a product to a product category. I will search for products that have the category "prodi:prod-cat-Coil" to find coil instances.

[Tool]
Got 93 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 Coil (prodi:prod-cat-Coil) |
| hw A548 4778785 (prodi:hw-A548-4778785) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw B120 9942467 (prodi:hw-B120-9942467) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw B143 5457756 (prodi:hw-B143-5457756) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw B150 4370781 (prodi:hw-B150-4370781) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw B286 1369879 (prodi:hw-B286-1369879) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw C171 3616793 (prodi:hw-C171-3616793) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw C402 5072074 (prodi:hw-C402-5072074) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw C717 1997689 (prodi:hw-C717-1997689) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw C744 6535902 (prodi:hw-C744-6535902) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| ...                                     | ...                           | ...                                 |

[Assistant] There are many coil instances with the category "prodi:prod-cat-Coil". Now I will check the properties of one of these coil instances to find if there is a property related to density. I will check the properties of "prodi:hw-A145-1240844" as an example.

[Tool]
Got 18 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                                   | object                                                                                |
| --------------------------------------- | ------------------------------------------ | -------------------------------------------------------------------------------------------------------- |
| hw A145 1240844 (prodi:hw-A145-1240844) | type (rdf:type)                            | Hardware (pv:Hardware)                                                                                |
| hw A145 1240844 (prodi:hw-A145-1240844) | label (rdfs:label)                         | A145-1240844 - Bipolar-junction Coil Compensator Transducer                                              |
| hw A145 1240844 (prodi:hw-A145-1240844) | has category (pv:hasCategory)              | prod cat Compensator (prodi:prod-cat-Compensator)                                                        |
| hw A145 1240844 (prodi:hw-A145-1240844) | compatible product (pv:compatibleProduct)  | hw D729 5737042 (prodi:hw-D729-5737042)                                                                  |
| hw A145 1240844 (prodi:hw-A145-1240844) | name (pv:name)                             | Bipolar-junction Coil Compensator Transducer                                                             |
| hw A145 1240844 (prodi:hw-A145-1240844) | ID (pv:id)                                 | A145-1240844                                                                                |
| hw A145 1240844 (prodi:hw-A145-1240844) | has product manager (pv:hasProductManager) | empl Ratt Hartmann@company org (<http://ld.company.org/prod-instances/empl-Ratt.Hartmann%40company.org>) |
| hw A145 1240844 (prodi:hw-A145-1240844) | price (pv:price)                           | price hw A145 1240844 EUR (prodi:price-hw-A145-1240844-EUR)                                              |
| hw A145 1240844 (prodi:hw-A145-1240844) | depth (mm) (pv:depth_mm)                   | 20 (xsd:int)                                                                                |
| hw A145 1240844 (prodi:hw-A145-1240844) | supplier (pv:hasSupplier)                  | suppl 42a20063 bd30 49d3 8506 ceac4ceb2d9e (prodi:suppl-42a20063-bd30-49d3-8506-ceac4ceb2d9e)            |
| ...                                     | ...                                        | ...                                                                                |

[Assistant] The properties of the coil instance "prodi:hw-A145-1240844" include dimensions like depth (mm), but no direct property named "density" is visible. I will check if there is a property related to "density" for this specific coil instance by searching for properties with "density" in their name or label.

[Tool]
Top 10 property alternatives:
1. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware
2. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
3. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
4. type (rdf:type)
5. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
6. ID (pv:id): The ID of a thing.
7. price (pv:price): The price specification of a product., has domain Product, has range Price
8. name (pv:name): The name of something.
9. label (rdfs:label)

No other items found

[Assistant]
There is no direct property related to "density" for the coil instance "prodi:hw-A145-1240844". However, there is a property "weight (g)" which might be useful if combined with volume (from dimensions) to calculate density, but the question asks for the coil with the highest density directly, so I need to find if density is explicitly stated anywhere.

I will try to search for any property with the term "density" in the knowledge graph to see if it exists at all.

[Tool]
Top 10 property alternatives:
1. quantity (pv:quantity): The quantity needed., has domain BOM Part
2. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware
3. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
4. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
5. type (rdf:type)
6. amount (pv:amount): has domain Price, The amount.
7. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
8. lat (wgs84:lat)
9. is Defined By (rdfs:isDefinedBy)
10. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware

[Assistant]
There is no explicit property named "density" in the knowledge graph. Since density is typically mass/volume, and I have found weight and dimensions (depth, height, width) properties for coils, I can calculate density by weight divided by volume (depth * height * width).

I will write a SPARQL query to find coils with their weight and dimensions and calculate density, then order by density descending to get the coil with the highest density.

[Tool] Stopped generation process


PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?hw ?id ?name ?width WHERE {
  ?hw pv:width_mm ?width .
  FILTER ( ?width >= 73 ) .
  OPTIONAL {
    ?hw pv:id ?id
  }
  .
  OPTIONAL {
    ?hw pv:name ?name
  }
  .
}
ORDER BY DESC ( ?width )

The query retrieves hardware items with widths in the top 10% (width >= 73 mm) along with their IDs, names, and widths.

Which hardware items have dimensions in the top 10 % of all widths, and what are their IDs, names and widths?

[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 hardware items have dimensions in the top 10 % of all widths, and what are their IDs, names and widths?

[Assistant] To answer this question, I need to identify the hardware items, their widths, and then filter those whose widths are in the top 10% of all widths. I will start by searching for the property related to width to understand how widths are represented in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
2. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
3. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
4. type (rdf:type)
5. quantity (pv:quantity): The quantity needed., has domain BOM Part
6. range (rdfs:range)
7. lat (wgs84:lat)
8. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware
9. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
10. created (dct:created)

[Assistant] The property "width (mm)" (pv:width_mm) is used to represent the width of an item measured in millimeters and has the domain Hardware. Next, I will check how hardware items are represented and if they have this width property. I will look for examples of hardware items with their widths.

[Tool]
Got 1,000 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                 | object       |
| --------------------------------------- | ------------------------ | ------------ |
| hw J785 9314350 (prodi:hw-J785-9314350) | width (mm) (pv:width_mm) | 16 (xsd:int) |
| hw V156 6277722 (prodi:hw-V156-6277722) | width (mm) (pv:width_mm) | 23 (xsd:int) |
| hw W769 8151254 (prodi:hw-W769-8151254) | width (mm) (pv:width_mm) | 40 (xsd:int) |
| hw B918 9468392 (prodi:hw-B918-9468392) | width (mm) (pv:width_mm) | 45 (xsd:int) |
| hw H374 8481414 (prodi:hw-H374-8481414) | width (mm) (pv:width_mm) | 43 (xsd:int) |
| hw K334 8882985 (prodi:hw-K334-8882985) | width (mm) (pv:width_mm) | 49 (xsd:int) |
| hw L557 1467804 (prodi:hw-L557-1467804) | width (mm) (pv:width_mm) | 22 (xsd:int) |
| hw O875 5580798 (prodi:hw-O875-5580798) | width (mm) (pv:width_mm) | 24 (xsd:int) |
| hw T808 9704137 (prodi:hw-T808-9704137) | width (mm) (pv:width_mm) | 39 (xsd:int) |
| hw J824 9483042 (prodi:hw-J824-9483042) | width (mm) (pv:width_mm) | 38 (xsd:int) |
| ...                                     | ...                      | ...          |

[Assistant] Hardware items have the property pv:width_mm for their widths. Now, I need to find the top 10% threshold for widths to filter the hardware items. I will calculate the 90th percentile of the widths and then retrieve the hardware items with widths greater than or equal to this threshold. I will first calculate the 90th percentile width.

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 234 for token HAVING with content 'HAVING' (the input most likely does not follow the grammar)

[Assistant] The SPARQL endpoint does not support HAVING clause in this context. I will try a different approach to calculate the 90th percentile width by ordering widths and limiting the results to the top 10%. Then I will get the minimum width from this subset as the threshold.

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 138 for token ( with content '(' (the input most likely does not follow the grammar)

[Assistant] The SPARQL endpoint does not support subqueries in LIMIT clause. I will try another approach: first, I will count the total number of hardware items with widths, then calculate 10% of that count, and finally get the widths ordered descending with a limit of that 10% count. From that, I will get the minimum width as the threshold. I will do this in multiple steps. First, count the total number of hardware items with widths.

[Tool]
Got 1 row and 1 column:
| totalCount     |
| -------------- |
| 1000 (xsd:int) |

[Assistant] There are 1000 hardware items with widths. 10% of 1000 is 100. Now I will get the widths of hardware items ordered descending with a limit of 100 to get the top 10% widths. Then I will find the minimum width in this set as the threshold.

[Tool]
Got 1 row and 1 column:
| threshold    |
| ------------ |
| 73 (xsd:int) |

[Assistant] The threshold width for the top 10% is 73 mm. Now I will retrieve the hardware items with widths greater than or equal to 73 mm, along with their IDs, names, and widths. I will check the property for the name of hardware items before constructing the final query.

[Tool]
Top 10 property alternatives:
1. name (pv:name): The name of something.
2. ID (pv:id): The ID of a thing.
3. label (rdfs:label)
4. price (pv:price): The price specification of a product., has domain Product, has range Price
5. type (rdf:type)
6. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
7. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
8. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware
9. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
10. has category (pv:hasCategory): The category name of a product., has range Product Category, has domain Product

No other items found

[Assistant] The property "name" (pv:name) is used for the name of hardware items. Also, the ID of the hardware item can be retrieved from the subject IRI itself or from the property "ID" (pv:id) if available. I will now construct the final query to get hardware items with width >= 73 mm, including their IDs, names, and widths.

[Tool] Stopped generation process


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?department ?departmentLabel WHERE {
  <http://ld.company.org/prod-instances/empl-Karen.Brant%40company.org> pv:memberOf ?department .
  OPTIONAL {
    ?department rdfs:label ?departmentLabel
  }
}

Ms. Brant (Karen Brant) is a member of the Engineering department.

[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] In which department is Ms. Brant?

[Assistant]
To answer the question "In which department is Ms. Brant?" I need to identify the entity representing Ms. Brant and then find the property that relates her to a department.

Step 1: Search for the entity "Ms. Brant" in the knowledge graph.

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

[Assistant]
There are two entities related to "Brant": Karen Brant and Sylvester Brant, both employees. Since the question uses "Ms. Brant," it is more likely referring to Karen Brant.

Step 2: Search for properties of the entity "empl Karen Brant@company org" to find a property related to the department.

[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. address text (pv:addressText): The address text., has domain Agent
8. email (pv:email): The e-mail of an agent., has domain Agent
9. phone number (pv:phone): has domain Agent, A phone number.

No other items found

[Assistant]
The property "member of" (pv:memberOf) is described as "The department to which an agent belongs" and has the domain Agent and range Department. This property is likely the one that relates Ms. Karen Brant to her department.

Step 3: Construct a SPARQL query to find the department of Ms. Karen Brant using the property pv:memberOf.

[Tool]
Got 1 row and 2 columns:
| department                    | departmentLabel |
| ----------------------------- | --------------- |
| dept 73191 (prodi:dept-73191) | Engineering     |

[Tool] Stopped generation process


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?employee ?name ?email ?phone WHERE {
  ?employee a pv:Employee .
  ?employee rdfs:label ?name .
  OPTIONAL {
    ?employee pv:email ?email
  }
  .
  OPTIONAL {
    ?employee pv:phone ?phone
  }
  .
  FILTER NOT EXISTS {
    ?otherEmployee pv:hasManager ?employee .
  }
}
ORDER BY ?name

Got 47 rows and 4 columns, showing the first 5 and last 5 rows below:
| employee                                                                                | name                | email                           | phone             |
| -------------------------------------------------------------------------------------------------------------------- | ------------------- | ------------------------------- | ----------------- |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>)             | Adolfina Hoch       | Adolfina.Hoch@company.org       | +49-109-5719002   |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | Anamchara Foerstner | Anamchara.Foerstner@company.org | +49-360-5655698   |
| empl Arendt Beitel@company org (<http://ld.company.org/prod-instances/empl-Arendt.Beitel%40company.org>)             | Arendt Beitel       | Arendt.Beitel@company.org       | +49-8763-66514379 |
| empl Arnelle Gerber@company org (<http://ld.company.org/prod-instances/empl-Arnelle.Gerber%40company.org>)           | Arnelle Gerber      | Arnelle.Gerber@company.org      | (03586) 7240528   |
| empl Baldwin Dirksen@company org (<http://ld.company.org/prod-instances/empl-Baldwin.Dirksen%40company.org>)         | Baldwin Dirksen     | Baldwin.Dirksen@company.org     | +49-6200-33069465 |
| ...                                                                                | ...                 | ...                             | ...               |
| empl Valda Everhart@company org (<http://ld.company.org/prod-instances/empl-Valda.Everhart%40company.org>)           | Valda Everhart      | Valda.Everhart@company.org      | +49-04-969-14255  |
| empl Wanja Hoffmann@company org (<http://ld.company.org/prod-instances/empl-Wanja.Hoffmann%40company.org>)           | Wanja Hoffmann      | Wanja.Hoffmann@company.org      | +49-1083-38194095 |
| empl Wolfgang Martin@company org (<http://ld.company.org/prod-instances/empl-Wolfgang.Martin%40company.org>)         | Wolfgang Martin     | Wolfgang.Martin@company.org     | +49-701-5973041   |
| empl Xochitl Aue@company org (<http://ld.company.org/prod-instances/empl-Xochitl.Aue%40company.org>)                 | Xochitl Aue         | Xochitl.Aue@company.org         |                   |
| empl Yanka Schreiber@company org (<http://ld.company.org/prod-instances/empl-Yanka.Schreiber%40company.org>)         | Yanka Schreiber     | Yanka.Schreiber@company.org     |                   |

The query returns a phone directory of all employees who do not manage anyone. It includes their name, email, and phone number, sorted by name. There are 47 such employees in the directory.

Give me a phone directory of everyone on staff who does not manage anyone, I need name, email, and phone, sorted by name?

[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] Give me a phone directory of everyone on staff who does not manage anyone, I need name, email, and phone, sorted by name?

[Assistant]
To answer this question, I need to identify the following:
1. Entities representing staff members.
2. Properties representing the name, email, and phone of staff members.
3. A way to identify staff members who do not manage anyone (i.e., they are not managers).

I will start by searching for entities related to "staff" or "employee" to understand how staff members are represented in the knowledge graph.

[Tool] No entity items found

[Assistant] No entities explicitly labeled as "staff" were found. I will try searching for "employee" instead to find entities representing staff members.

[Tool]
Top 10 entity alternatives:
1. Employee (pv:Employee): An employee in my company., is subclass of Agent
2. employee line svg?color=#D6AF00&format=svg (<https://api.iconify.design/clarity/employee-line.svg?color=%23D6AF00&format=svg>)

[Assistant]
There is an entity "Employee" (pv:Employee) which represents an employee in the company. This is likely the class for staff members.

Next, I will search for properties related to "name" for the entity Employee to find the property used for the name of staff members.

[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)
6. sub Class Of (rdfs:subClassOf)

No other items found

[Assistant] The property rdfs:label seems to be used for the name of the employee. Next, I will search for properties related to "email" for the entity Employee.

[Tool]
Top 10 property alternatives:
1. comment (rdfs:comment)
2. label (rdfs:label)
3. type (rdf:type)

No other items found

[Assistant] No specific property for email was found directly related to Employee. I will try searching for properties related to "email" in general in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. email (pv:email): The e-mail of an agent., has domain Agent
2. address text (pv:addressText): The address text., has domain Agent
3. address country (pv:addressCountry): The address country., has domain Agent
4. comment (rdfs:comment)
5. phone number (pv:phone): has domain Agent, A phone number.
6. name (foaf:name):

7. name (pv:name): The name of something.
8. license (<http://creativecommons.org/ns#license>)
9. label (rdfs:label)
10. ID (pv:id): The ID of a thing.

[Assistant]
There is a property pv:email for the email of an agent and pv:phone for the phone number. Both have domain Agent, and since Employee is likely a subclass of Agent, these properties should apply to employees as well.

Next, I need to identify how to find employees who do not manage anyone. I will search for properties related to "manage" or "manager" for the entity Employee.

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

No other items found

[Assistant] No direct property related to "manage" was found for Employee. I will try searching for properties related to "manager" in general in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. has manager (pv:hasManager): The manager of the employee., has domain Employee, has range Manager
2. has product manager (pv:hasProductManager): The employee acting as the product manager of the product., has range Employee, has domain Product
3. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product
4. contributor (dct:contributor)
5. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
6. publisher (dct:publisher)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
10. creator (dct:creator)

[Assistant]
There is a property pv:hasManager which indicates the manager of the employee. This means employees who do not manage anyone would be those who are not referenced as a manager by any other employee.

I will now construct a SPARQL query to find employees who are not managers of anyone. I will select their rdfs:label as name, pv:email as email, and pv:phone as phone, and sort the results by name.

[Tool]
Got 47 rows and 4 columns, showing the first 5 and last 5 rows below:
| employee                                                                                | name                | email                           | phone             |
| -------------------------------------------------------------------------------------------------------------------- | ------------------- | ------------------------------- | ----------------- |
| empl Adolfina Hoch@company org (<http://ld.company.org/prod-instances/empl-Adolfina.Hoch%40company.org>)             | Adolfina Hoch       | Adolfina.Hoch@company.org       | +49-109-5719002   |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | Anamchara Foerstner | Anamchara.Foerstner@company.org | +49-360-5655698   |
| empl Arendt Beitel@company org (<http://ld.company.org/prod-instances/empl-Arendt.Beitel%40company.org>)             | Arendt Beitel       | Arendt.Beitel@company.org       | +49-8763-66514379 |
| empl Arnelle Gerber@company org (<http://ld.company.org/prod-instances/empl-Arnelle.Gerber%40company.org>)           | Arnelle Gerber      | Arnelle.Gerber@company.org      | (03586) 7240528   |
| empl Baldwin Dirksen@company org (<http://ld.company.org/prod-instances/empl-Baldwin.Dirksen%40company.org>)         | Baldwin Dirksen     | Baldwin.Dirksen@company.org     | +49-6200-33069465 |
| ...                                                                                | ...                 | ...                             | ...               |
| empl Valda Everhart@company org (<http://ld.company.org/prod-instances/empl-Valda.Everhart%40company.org>)           | Valda Everhart      | Valda.Everhart@company.org      | +49-04-969-14255  |
| empl Wanja Hoffmann@company org (<http://ld.company.org/prod-instances/empl-Wanja.Hoffmann%40company.org>)           | Wanja Hoffmann      | Wanja.Hoffmann@company.org      | +49-1083-38194095 |
| empl Wolfgang Martin@company org (<http://ld.company.org/prod-instances/empl-Wolfgang.Martin%40company.org>)         | Wolfgang Martin     | Wolfgang.Martin@company.org     | +49-701-5973041   |
| empl Xochitl Aue@company org (<http://ld.company.org/prod-instances/empl-Xochitl.Aue%40company.org>)                 | Xochitl Aue         | Xochitl.Aue@company.org         |                   |
| empl Yanka Schreiber@company org (<http://ld.company.org/prod-instances/empl-Yanka.Schreiber%40company.org>)         | Yanka Schreiber     | Yanka.Schreiber@company.org     |                   |

[Tool] Stopped generation process


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT ?department ?departmentName ( COUNT( ?employee ) AS ?employeeCount ) WHERE {
  ?employee rdf:type pv:Employee .
  ?employee pv:memberOf ?department .
  OPTIONAL {
    ?department rdfs:label ?departmentName
  }
}
GROUP BY ?department ?departmentName
HAVING ( COUNT( ?employee ) > 5 )

Got 4 rows and 3 columns:
| department                    | departmentName     | employeeCount |
| ----------------------------- | ------------------ | ------------- |
| dept 22183 (prodi:dept-22183) | Product Management | 12 (xsd:int)  |
| dept 41622 (prodi:dept-41622) | Data Services      | 9 (xsd:int)   |
| dept 84279 (prodi:dept-84279) | Procurement        | 8 (xsd:int)   |
| dept 85880 (prodi:dept-85880) | Marketing          | 9 (xsd:int)   |

The departments with more than 5 employees along with their names and the number of employees are:
- Product Management with 12 employees
- Data Services with 9 employees
- Procurement with 8 employees
- Marketing with 9 employees

Which department have more than 5 employees? I need their names and the number of employees.

[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 have more than 5 employees? I need their names and the number of employees.

[Assistant]
To answer this question, I need to find the entity representing departments and the property representing employees or the count of employees in each department. Then I will query for departments with more than 5 employees and retrieve their names and the number of employees.

First, I will search for entities related to "department" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Department (pv:Department): A department in an organization.
2. emoji department store svg?color=#D6AF00&format=svg (<https://api.iconify.design/arcticons/emoji-department-store.svg?color=%23D6AF00&format=svg>)

[Assistant] I found an entity "pv:Department" which represents a department in an organization. Next, I will search for properties related to "employee" or "number of employees" for the entity pv:Department.

[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

[Assistant] There are no direct properties related to employees for the entity pv:Department. I will try to find if there is a property that links departments to employees or persons. I will search for properties with the keyword "employee".

[Tool]
Top 10 property alternatives:
1. has manager (pv:hasManager): The manager of the employee., has domain Employee, has range Manager
2. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product
3. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
4. contributor (dct:contributor)
5. created (dct:created)
6. eligible for (pv:eligibleFor): Valid product service combinations (bundles, accessories)., has domain Service, has range Product
7. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
8. has product manager (pv:hasProductManager): The employee acting as the product manager of the product., has range Employee, has domain Product
9. creator (dct:creator)
10. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier

[Assistant] I found a property "pv:memberOf" which has the range Department and domain Agent. This suggests that agents (which could be employees) are members of departments. I will now check if there is an entity or class for employees or agents. I will search for "employee" and "agent" entities.

[Tool]
Top 10 entity alternatives:
1. Employee (pv:Employee): An employee in my company., is subclass of Agent
2. employee line svg?color=#D6AF00&format=svg (<https://api.iconify.design/clarity/employee-line.svg?color=%23D6AF00&format=svg>)

[Tool]
Top 10 entity alternatives:
1. Agent (pv:Agent): Abstract base class for people, robots or other things that can act.
2. Agent (dct:Agent)

[Assistant]
There is an entity "pv:Employee" which is a subclass of "pv:Agent". So employees are agents and they can be members of departments using the property "pv:memberOf".

Now I will write a SPARQL query to count the number of employees in each department and filter those with more than 5 employees. I will also retrieve the department names.

[Tool]
Got 4 rows and 3 columns:
| department                    | departmentName     | employeeCount |
| ----------------------------- | ------------------ | ------------- |
| dept 22183 (prodi:dept-22183) | Product Management | 12 (xsd:int)  |
| dept 41622 (prodi:dept-41622) | Data Services      | 9 (xsd:int)   |
| dept 84279 (prodi:dept-84279) | Procurement        | 8 (xsd:int)   |
| dept 85880 (prodi:dept-85880) | Marketing          | 9 (xsd:int)   |

[Tool] Stopped generation process