PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?category ?categoryLabel ( SAMPLE( ?lhw ) AS ?lightestHardware ) ( SAMPLE( ?lhwLabel ) AS ?lightestHardwareLabel ) ?lightestWeight ( SAMPLE( ?hhw ) AS ?heaviestHardware ) ( SAMPLE( ?hhwLabel ) AS ?heaviestHardwareLabel ) ?heaviestWeight WHERE {
  {
    SELECT ?category ( MIN( ?weight ) AS ?lightestWeight ) ( MAX( ?weight ) AS ?heaviestWeight ) WHERE {
      ?hardware a pv:Hardware .
      ?hardware pv:hasCategory ?category .
      ?hardware pv:weight_g ?weight .
    }
    GROUP BY ?category
  }
  ?lhw a pv:Hardware ; pv:hasCategory ?category ; pv:weight_g ?lightestWeight .
  ?hhw a pv:Hardware ; pv:hasCategory ?category ; pv:weight_g ?heaviestWeight .
  OPTIONAL {
    ?category rdfs:label ?categoryLabel
  }
  OPTIONAL {
    ?lhw rdfs:label ?lhwLabel
  }
  OPTIONAL {
    ?hhw rdfs:label ?hhwLabel
  }
}
GROUP BY ?category ?categoryLabel ?lightestWeight ?heaviestWeight
ORDER BY ?category
LIMIT 20

Per product category, the query returns the lightest and heaviest hardware items with their weights. For example, in the category 'Breaker', the lightest hardware item is 'Z319-4514647 - Phase Resistor Breaker Oscillator' weighing 1 gram, and the heaviest is 'E558-1962104 - Planck Breaker Compensator' weighing 20 grams. Similar results are available for other categories like Capacitor, Coil, Compensator, Crystal, etc.

Per product category, what's our lightest and heaviest hardware item?

[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] Per product category, what's our lightest and heaviest hardware item?

[Assistant]
To answer the question about the lightest and heaviest hardware items per product category, I need to identify the following:

1. The concept of "product category" in the knowledge graph.
2. The concept of "hardware item" and how it is represented.
3. The property that indicates the weight of an item.
4. The relationship between hardware items and their product categories.

I will start by searching for entities related to "product category" to understand how categories are represented.

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

[Assistant] I found that "Product Category" is represented by the entity pv:ProductCategory and products have a property pv:hasCategory linking them to a Product Category. Next, I will search for entities related to "hardware" to identify how hardware items are represented.

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

[Assistant] Hardware items are represented by the entity pv:Hardware, which is a subclass of Product. Now, I need to find the property that indicates the weight of an item. I will search for properties related to "weight" in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware
2. quantity (pv:quantity): The quantity needed., has domain BOM Part
3. amount (pv:amount): has domain Price, The amount.
4. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
5. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
6. currency (pv:currency): has domain Price, The currency.
7. type (rdf:type)
8. name (foaf:name):

9. name (pv:name): The name of something.
10. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware

[Assistant] The property indicating the weight of an item is pv:weight_g, which measures the weight in grams and has the domain Hardware. Now, I will check how hardware items are linked to their product categories using the property pv:hasCategory. I will run a query to get some examples of hardware items with their categories and weights.

[Tool]
Got 10 rows and 5 columns:
| hardware                                | hardwareLabel                                    | category                                  | categoryLabel | weight       |
| --------------------------------------- | ------------------------------------------------ | ----------------------------------------- | ------------- | ------------ |
| hw F414 1779577 (prodi:hw-F414-1779577) | F414-1779577 - Multiplexer Potentiometer Breaker | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 16 (xsd:int) |
| hw A828 3713433 (prodi:hw-A828-3713433) | A828-3713433 - Multiplexer Breaker               | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 8 (xsd:int)  |
| hw A816 3021832 (prodi:hw-A816-3021832) | A816-3021832 - Rheostat Breaker                  | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 18 (xsd:int) |
| hw C301 4034359 (prodi:hw-C301-4034359) | C301-4034359 - Oscillator Breaker                | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 19 (xsd:int) |
| hw F773 4598178 (prodi:hw-F773-4598178) | F773-4598178 - Transistor Breaker Switch         | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 3 (xsd:int)  |
| hw D627 4615108 (prodi:hw-D627-4615108) | D627-4615108 - Coil Dipole Breaker               | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 9 (xsd:int)  |
| hw F332 3707903 (prodi:hw-F332-3707903) | F332-3707903 - Gauge Breaker                     | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 16 (xsd:int) |
| hw E835 1316991 (prodi:hw-E835-1316991) | E835-1316991 - Resistor Breaker                  | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 20 (xsd:int) |
| hw E189 1255687 (prodi:hw-E189-1255687) | E189-1255687 - LCD Potentiometer Breaker         | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 18 (xsd:int) |
| hw C614 4108640 (prodi:hw-C614-4108640) | C614-4108640 - Log-periodic LCD Breaker          | prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | 14 (xsd:int) |

[Assistant] I confirmed that hardware items (pv:Hardware) have a property pv:hasCategory linking them to product categories (pv:ProductCategory), and their weight is given by pv:weight_g. Now, I will write a query to find the lightest and heaviest hardware item per product category. I will use aggregation to find the minimum and maximum weight per category and then join back to get the corresponding hardware items.

[Tool]
Got 20 rows and 8 columns, showing the first 5 and last 5 rows below:
| category                                  | categoryLabel | lightestHardware                        | lightestHardwareLabel                            | lightestWeight | heaviestHardware                        | heaviestHardwareLabel                          | heaviestWeight |
| ----------------------------------------- | ------------- | --------------------------------------- | ------------------------------------------------ | -------------- | --------------------------------------- | ---------------------------------------------- | -------------- |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw Z319 4514647 (prodi:hw-Z319-4514647) | Z319-4514647 - Phase Resistor Breaker Oscillator | 1 (xsd:int)    | hw E558 1962104 (prodi:hw-E558-1962104) | E558-1962104 - Planck Breaker Compensator      | 20 (xsd:int)   |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw H156 2424615 (prodi:hw-H156-2424615) | H156-2424615 - Polymer Driver Transistor Breaker | 1 (xsd:int)    | hw I696 9739398 (prodi:hw-I696-9739398) | I696-9739398 - Breaker Resonator Encoder       | 20 (xsd:int)   |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw C770 9751514 (prodi:hw-C770-9751514) | C770-9751514 - Transistor Resonator Breaker      | 1 (xsd:int)    | hw E835 1316991 (prodi:hw-E835-1316991) | E835-1316991 - Resistor Breaker                | 20 (xsd:int)   |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw H156 2424615 (prodi:hw-H156-2424615) | H156-2424615 - Polymer Driver Transistor Breaker | 1 (xsd:int)    | hw E835 1316991 (prodi:hw-E835-1316991) | E835-1316991 - Resistor Breaker                | 20 (xsd:int)   |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw Z319 4514647 (prodi:hw-Z319-4514647) | Z319-4514647 - Phase Resistor Breaker Oscillator | 1 (xsd:int)    | hw E835 1316991 (prodi:hw-E835-1316991) | E835-1316991 - Resistor Breaker                | 20 (xsd:int)   |
| ...                                       | ...           | ...                                     | ...                                              | ...            | ...                                     | ...                                            | ...            |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw Z319 4514647 (prodi:hw-Z319-4514647) | Z319-4514647 - Phase Resistor Breaker Oscillator | 1 (xsd:int)    | hw P317 3419187 (prodi:hw-P317-3419187) | P317-3419187 - Network Breaker Transducer      | 20 (xsd:int)   |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw Z319 4514647 (prodi:hw-Z319-4514647) | Z319-4514647 - Phase Resistor Breaker Oscillator | 1 (xsd:int)    | hw W176 3285571 (prodi:hw-W176-3285571) | W176-3285571 - Log-periodic Oscillator Breaker | 20 (xsd:int)   |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw H156 2424615 (prodi:hw-H156-2424615) | H156-2424615 - Polymer Driver Transistor Breaker | 1 (xsd:int)    | hw W176 3285571 (prodi:hw-W176-3285571) | W176-3285571 - Log-periodic Oscillator Breaker | 20 (xsd:int)   |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw M770 3602005 (prodi:hw-M770-3602005) | M770-3602005 - Sensor Capacitor Breaker          | 1 (xsd:int)    | hw W176 3285571 (prodi:hw-W176-3285571) | W176-3285571 - Log-periodic Oscillator Breaker | 20 (xsd:int)   |
| prod cat Breaker (prodi:prod-cat-Breaker) | Breaker       | hw C770 9751514 (prodi:hw-C770-9751514) | C770-9751514 - Transistor Resonator Breaker      | 1 (xsd:int)    | hw W176 3285571 (prodi:hw-W176-3285571) | W176-3285571 - Log-periodic Oscillator Breaker | 20 (xsd:int)   |

[Assistant] The query results show the lightest and heaviest hardware items per product category. However, the results contain multiple rows for the same category with different hardware items having the same minimum or maximum weight. I will refine the query to return only one lightest and one heaviest hardware item per category by using GROUP BY and SAMPLE aggregation for the hardware items and their labels.

[Tool]
SPARQL execution failed:
Invalid SPARQL query: The target ?lightestHardware of an AS clause was already used in the query body.

[Assistant] The error indicates that I cannot use the same variable name in the SELECT clause with AS if it is already used in the query body. I will rename the variables in the SAMPLE aggregation to avoid this conflict and try again.

[Tool]
Got 20 rows and 8 columns, showing the first 5 and last 5 rows below:
| category                                              | categoryLabel | lightestHardware                        | lightestHardwareLabel                                   | lightestWeight | heaviestHardware                        | heaviestHardwareLabel                          | heaviestWeight |
| ----------------------------------------------------- | ------------- | --------------------------------------- | ------------------------------------------------------- | -------------- | --------------------------------------- | ---------------------------------------------- | -------------- |
| prod cat Breaker (prodi:prod-cat-Breaker)             | Breaker       | hw Z319 4514647 (prodi:hw-Z319-4514647) | Z319-4514647 - Phase Resistor Breaker Oscillator        | 1 (xsd:int)    | hw E558 1962104 (prodi:hw-E558-1962104) | E558-1962104 - Planck Breaker Compensator      | 20 (xsd:int)   |
| prod cat Capacitor (prodi:prod-cat-Capacitor)         | Capacitor     | hw M770 3602005 (prodi:hw-M770-3602005) | M770-3602005 - Sensor Capacitor Breaker                 | 1 (xsd:int)    | hw X408 2200602 (prodi:hw-X408-2200602) | X408-2200602 - Inductor Capacitor Meter        | 20 (xsd:int)   |
| prod cat Coil (prodi:prod-cat-Coil)                   | Coil          | hw E868 5063965 (prodi:hw-E868-5063965) | E868-5063965 - Coil Compensator                         | 1 (xsd:int)    | hw W358 5750223 (prodi:hw-W358-5750223) | W358-5750223 - Coil Warp                       | 20 (xsd:int)   |
| prod cat Compensator (prodi:prod-cat-Compensator)     | Compensator   | hw Y467 5818685 (prodi:hw-Y467-5818685) | Y467-5818685 - Memristor Compensator                    | 1 (xsd:int)    | hw K473 9950981 (prodi:hw-K473-9950981) | K473-9950981 - Coil Compensator                | 20 (xsd:int)   |
| prod cat Crystal (prodi:prod-cat-Crystal)             | Crystal       | hw C213 4995667 (prodi:hw-C213-4995667) | C213-4995667 - Potentiometer Crystal Encoder            | 1 (xsd:int)    | hw L619 5092078 (prodi:hw-L619-5092078) | L619-5092078 - Crystal Resonator Transformer   | 20 (xsd:int)   |
| ...                                                   | ...           | ...                                     | ...                                                     | ...            | ...                                     | ...                                            | ...            |
| prod cat Potentiometer (prodi:prod-cat-Potentiometer) | Potentiometer | hw T504 8448784 (prodi:hw-T504-8448784) | T504-8448784 - Flow Potentiometer Gauge Oscillator      | 1 (xsd:int)    | hw C245 8365837 (prodi:hw-C245-8365837) | C245-8365837 - Potentiometer Resonator Encoder | 20 (xsd:int)   |
| prod cat Resistor (prodi:prod-cat-Resistor)           | Resistor      | hw Z319 4514647 (prodi:hw-Z319-4514647) | Z319-4514647 - Phase Resistor Breaker Oscillator        | 1 (xsd:int)    | hw W846 7438265 (prodi:hw-W846-7438265) | W846-7438265 - Resistor Memristor Capacitor    | 20 (xsd:int)   |
| prod cat Resonator (prodi:prod-cat-Resonator)         | Resonator     | hw T608 9573692 (prodi:hw-T608-9573692) | T608-9573692 - Coil Resonator                           | 1 (xsd:int)    | hw L619 5092078 (prodi:hw-L619-5092078) | L619-5092078 - Crystal Resonator Transformer   | 20 (xsd:int)   |
| prod cat Rheostat (prodi:prod-cat-Rheostat)           | Rheostat      | hw U651 8669022 (prodi:hw-U651-8669022) | U651-8669022 - Heisenberg Inductor Rheostat Transformer | 1 (xsd:int)    | hw L612 4428366 (prodi:hw-L612-4428366) | L612-4428366 - Resonator Rheostat              | 20 (xsd:int)   |
| prod cat Sensor (prodi:prod-cat-Sensor)               | Sensor        | hw E405 1045893 (prodi:hw-E405-1045893) | E405-1045893 - Polymer Sensor                           | 1 (xsd:int)    | hw N171 1815828 (prodi:hw-N171-1815828) | N171-1815828 - LCD Sensor                      | 20 (xsd:int)   |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the lightest and heaviest hardware items per product category along with their weights and labels. The query uses appropriate aggregation (MIN and MAX) to find the weights and then matches the hardware items with those weights per category. The results are consistent with the question, showing the lightest and heaviest hardware items for each category. The query also includes optional labels for better readability. The execution result confirms that the query returns meaningful and relevant data. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
SELECT DISTINCT ?country ?countryLabel WHERE {
  prodi:bom-17 pv:hasBomPart ?bomPart .
  ?bomPart pv:hasPart ?hardware .
  ?hardware pv:hasSupplier ?supplier .
  ?supplier pv:country ?country .
  OPTIONAL {
    ?country rdfs:label ?countryLabel
  }
}

Got 7 rows and 2 columns:
| country                                                         | countryLabel |
| --------------------------------------------------------------- | ------------ |
| Belarus (dbpedia:Belarus)                                       |              |
| Finland (dbpedia:Finland)                                       |              |
| Germany (dbpedia:Germany)                                       |              |
| Kingdom of the Netherlands (dbpedia:Kingdom_of_the_Netherlands) |              |
| Slovakia (dbpedia:Slovakia)                                     |              |
| Tanzania (dbpedia:Tanzania)                                     |              |
| Vietnam (dbpedia:Vietnam)                                       |              |

The countries from which the BOM parts of SkySync MechWave are delivered can be retrieved by this query.

From which countries are the BOM parts of our SkySync MechWave delivered?

[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] From which countries are the BOM parts of our SkySync MechWave delivered?

[Assistant]
Step 1: Understand the question and identify key entities and properties.
The question asks for the countries from which the BOM (Bill of Materials) parts of a product called "SkySync MechWave" are delivered. Key entities are "SkySync MechWave" and "BOM parts." Key properties likely involve the relationship between the product and its BOM parts, and the delivery or origin country of those parts.

Step 2: Search for the entity "SkySync MechWave" in the knowledge graph to confirm its existence and get its identifier.
I will search for the entity "SkySync MechWave" in the ck25 knowledge graph.

[Tool] No entity items found

[Assistant] The entity "SkySync MechWave" is not found in the knowledge graph. I will try a more general search for "SkySync" to see if there is a related entity or product with a similar name.

[Tool] No entity items found

[Assistant]
The product "SkySync MechWave" or any related entity with the name "SkySync" is not found in the knowledge graph. Without the exact entity for the product, it is not possible to directly query the BOM parts and their delivery countries.

I will try to search for entities related to "MechWave" to see if there is any relevant product or component.

[Tool] No entity items found

[Assistant]
The product or entity "MechWave" is also not found in the knowledge graph. It seems that the product "SkySync MechWave" is not present in the knowledge graph, so I cannot directly find the BOM parts or their delivery countries.

I will now try to search for properties related to "BOM parts" or "Bill of Materials" to see if there is a general property that links products to their BOM parts.

[Tool]
Top 10 property alternatives:
1. has BOM Part (pv:hasBomPart): has domain Bill of Material (BOM), A part(s) used in this BOM., has range BOM Part
2. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
3. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
4. type (rdf:type)
5. label (rdfs:label)
6. quantity (pv:quantity): The quantity needed., has domain BOM Part
7. created (dct:created)
8. comment (rdfs:comment)
9. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
10. ID (pv:id): The ID of a thing.

[Assistant]
There is a property "has BOM Part" (pv:hasBomPart) which links a Bill of Material (BOM) to its parts. Also, there is a property "part" (pv:hasPart) that links a BOM Part to the Product needed.

Next, I will try to find entities related to "SkySync MechWave" by searching for "SkySync MechWave" as a product or similar in the knowledge graph. Since the exact entity was not found, I will try to find products or entities with "SkySync" or "MechWave" in their labels or descriptions.

I will search for entities with the label containing "SkySync MechWave" or similar.

[Tool] No entity items found

[Assistant]
Since the product "SkySync MechWave" is not found in the knowledge graph, I will try to find all products or entities that have BOM parts and then check if any of them have a label or description that matches or is similar to "SkySync MechWave."

I will query for entities that have the property pv:hasBomPart to see what products or BOMs are available.

[Tool]
Got 10 rows and 2 columns:
| product               | label                   |
| --------------------- | ----------------------- |
| bom 1 (prodi:bom-1)   | ElectroMech ProDrive    |
| bom 10 (prodi:bom-10) | OmegaDrive MechTech     |
| bom 11 (prodi:bom-11) | TransElectro Voyager    |
| bom 12 (prodi:bom-12) | AeroVibe Matrix         |
| bom 13 (prodi:bom-13) | MechaPulse SkyForge     |
| bom 14 (prodi:bom-14) | NexusWing ElectroMotive |
| bom 15 (prodi:bom-15) | QuantMech Voyager       |
| bom 16 (prodi:bom-16) | ElectroSphere Vesselink |
| bom 17 (prodi:bom-17) | SkySync MechWave        |
| bom 18 (prodi:bom-18) | HydraPulse ElectraCraft |

[Assistant]
I found an entity with the label "SkySync MechWave" and the identifier prodi:bom-17. This seems to be the BOM for the product "SkySync MechWave."

Step 3: Now I will find the BOM parts of this BOM using the property pv:hasBomPart and then find the countries from which these parts are delivered. I need to find the property that links BOM parts to their delivery countries.

I will first list the properties of the BOM entity prodi:bom-17 to see what properties are available.

[Tool]
Got 11 rows and 3 columns, showing the first 10 rows below:
| subject               | property                     | object                                                    |
| --------------------- | ---------------------------- | --------------------------------------------------------- |
| bom 17 (prodi:bom-17) | type (rdf:type)              | Bill of Material (BOM) (pv:BillOfMaterial)                |
| bom 17 (prodi:bom-17) | label (rdfs:label)           | SkySync MechWave                                          |
| bom 17 (prodi:bom-17) | name (pv:name)               | SkySync MechWave                                          |
| bom 17 (prodi:bom-17) | has BOM Part (pv:hasBomPart) | bom part 17 A243 3332548 (prodi:bom-part-17-A243-3332548) |
| bom 17 (prodi:bom-17) | has BOM Part (pv:hasBomPart) | bom part 17 H958 9648652 (prodi:bom-part-17-H958-9648652) |
| bom 17 (prodi:bom-17) | has BOM Part (pv:hasBomPart) | bom part 17 M812 1436368 (prodi:bom-part-17-M812-1436368) |
| bom 17 (prodi:bom-17) | has BOM Part (pv:hasBomPart) | bom part 17 N573 1498086 (prodi:bom-part-17-N573-1498086) |
| bom 17 (prodi:bom-17) | has BOM Part (pv:hasBomPart) | bom part 17 Q696 9337626 (prodi:bom-part-17-Q696-9337626) |
| bom 17 (prodi:bom-17) | has BOM Part (pv:hasBomPart) | bom part 17 R599 8820686 (prodi:bom-part-17-R599-8820686) |
| bom 17 (prodi:bom-17) | has BOM Part (pv:hasBomPart) | bom part 17 X480 1491345 (prodi:bom-part-17-X480-1491345) |
| ...                   | ...                          | ...                                                       |

[Assistant]
The BOM "SkySync MechWave" (prodi:bom-17) has multiple BOM parts linked by the property pv:hasBomPart. Now I need to find the property that indicates the delivery country for these BOM parts.

I will check the properties of one of the BOM parts, for example, prodi:bom-part-17-A243-3332548, to find any property related to delivery country or origin country.

[Tool]
Got 4 rows and 3 columns:
| subject                                                   | property               | object                                  |
| --------------------------------------------------------- | ---------------------- | --------------------------------------- |
| bom part 17 A243 3332548 (prodi:bom-part-17-A243-3332548) | type (rdf:type)        | BOM Part (pv:BomPart)                   |
| bom part 17 A243 3332548 (prodi:bom-part-17-A243-3332548) | label (rdfs:label)     | A243-3332548 (75)                       |
| bom part 17 A243 3332548 (prodi:bom-part-17-A243-3332548) | quantity (pv:quantity) | 75                                      |
| bom part 17 A243 3332548 (prodi:bom-part-17-A243-3332548) | part (pv:hasPart)      | hw A243 3332548 (prodi:hw-A243-3332548) |

[Assistant]
The BOM part prodi:bom-part-17-A243-3332548 has a property pv:hasPart linking to a hardware entity prodi:hw-A243-3332548. The delivery country might be linked to the hardware entity.

I will now check the properties of the hardware entity prodi:hw-A243-3332548 to find any property related to delivery country or origin country.

[Tool]
Got 15 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                                   | object                                                                                |
| --------------------------------------- | ------------------------------------------ | ------------------------------------------------------------------------------------------------------ |
| hw A243 3332548 (prodi:hw-A243-3332548) | type (rdf:type)                            | Hardware (pv:Hardware)                                                                                |
| hw A243 3332548 (prodi:hw-A243-3332548) | label (rdfs:label)                         | A243-3332548 - Bipolar-junction Crystal Meter                                                          |
| hw A243 3332548 (prodi:hw-A243-3332548) | has category (pv:hasCategory)              | prod cat Crystal (prodi:prod-cat-Crystal)                                                              |
| hw A243 3332548 (prodi:hw-A243-3332548) | compatible product (pv:compatibleProduct)  | hw Z439 5790785 (prodi:hw-Z439-5790785)                                                                |
| hw A243 3332548 (prodi:hw-A243-3332548) | name (pv:name)                             | Bipolar-junction Crystal Meter                                                                         |
| hw A243 3332548 (prodi:hw-A243-3332548) | ID (pv:id)                                 | A243-3332548                                                                                |
| hw A243 3332548 (prodi:hw-A243-3332548) | has product manager (pv:hasProductManager) | empl Ulrik Denzel@company org (<http://ld.company.org/prod-instances/empl-Ulrik.Denzel%40company.org>) |
| hw A243 3332548 (prodi:hw-A243-3332548) | price (pv:price)                           | price hw A243 3332548 EUR (prodi:price-hw-A243-3332548-EUR)                                            |
| hw A243 3332548 (prodi:hw-A243-3332548) | depth (mm) (pv:depth_mm)                   | 17 (xsd:int)                                                                                |
| hw A243 3332548 (prodi:hw-A243-3332548) | supplier (pv:hasSupplier)                  | suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248)          |
| ...                                     | ...                                        | ...                                                                                |

[Assistant]
The hardware entity prodi:hw-A243-3332548 has a property pv:hasSupplier linking to a supplier entity prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248.

I will now check the properties of the supplier entity to find any property related to the country of the supplier.

[Tool]
Got 10 rows and 3 columns:
| subject                                                                                | property                                     | object                               |
| --------------------------------------------------------------------------------------------- | -------------------------------------------- | ------------------------------------ |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | type (rdf:type)                              | Supplier (pv:Supplier)               |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | label (rdfs:label)                           | Davis Ltd (Belarus)                  |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | name (pv:name)                               | Davis Ltd                            |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | ID (pv:id)                                   | b8b7794e-329e-4bdc-9fcb-5ddfe9b71248 |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | address country (pv:addressCountry)          | Belarus                              |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | address country code (pv:addressCountryCode) | BY                                   |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | address locality (pv:addressLocality)        | Pinsk                                |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | lat (wgs84:lat)                              | 52.1113862                           |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | long (wgs84:long)                            | 26.1025274                           |
| suppl b8b7794e 329e 4bdc 9fcb 5ddfe9b71248 (prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248) | country (pv:country)                         | Belarus (dbpedia:Belarus)            |

[Assistant]
The supplier entity prodi:suppl-b8b7794e-329e-4bdc-9fcb-5ddfe9b71248 has properties indicating the country "Belarus" (pv:addressCountry, pv:country).

Step 4: I will now write a SPARQL query to get all distinct countries from which the BOM parts of "SkySync MechWave" (prodi:bom-17) are delivered by traversing from BOM to BOM parts to hardware to supplier to country.

I will include optional labels for better readability.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the distinct countries from which the BOM parts of SkySync MechWave are delivered. It uses the appropriate properties and entities, and the execution result shows a reasonable list of countries. The query also optionally retrieves the country labels, which is good for readability. The answer is complete and accurate based on the query results.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?manager ?managerName WHERE {
  <http://ld.company.org/prod-instances/empl-Heinrich.Hoch%40company.org> pv:hasManager ?manager .
  OPTIONAL {
    ?manager rdfs:label ?managerName
  }
  OPTIONAL {
    ?manager pv:name ?managerName
  }
}
LIMIT 10

The manager of Heinrich Hoch is Waldtraud Kuttner.

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

You have access to the following knowledge graphs:
ck25 at http://localhost:9333

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

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

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

[User] Who is the manager of Heinrich Hoch?

[Assistant] Step 1: Identify the entity "Heinrich Hoch" in the knowledge graph to get its IRI. I will search for the entity "Heinrich Hoch" first.

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

[Assistant]
I found an entity for Heinrich Hoch as an employee: <http://ld.company.org/prod-instances/empl-Heinrich.Hoch%40company.org>.

Step 2: Now I will search for properties related to "manager" for this entity to find the manager of Heinrich Hoch.

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

No other items found

[Assistant]
The property "has manager" (pv:hasManager) is the relevant property to find the manager of Heinrich Hoch.

Step 3: I will now write a SPARQL query to get the manager of Heinrich Hoch using the property pv:hasManager. I will also try to get the label or name of the manager if available.

[Tool]
Got 1 row and 2 columns:
| manager                                                                                | managerName       |
| ---------------------------------------------------------------------------------------------------------------- | ----------------- |
| empl Waldtraud Kuttner@company org (<http://ld.company.org/prod-instances/empl-Waldtraud.Kuttner%40company.org>) | Waldtraud Kuttner |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the manager of Heinrich Hoch by using the property pv:hasManager. It also optionally retrieves the manager's name using both rdfs:label and pv:name, ensuring a human-readable answer. The query returns exactly one manager, Waldtraud Kuttner, which matches the provided answer. The query is well-formed, executes successfully on the given knowledge graph, and the answer is accurate and complete. No further refinement is needed.


PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?hardware ?width ?height ?depth WHERE {
  ?hardware rdf:type pv:Hardware .
  ?hardware pv:width_mm ?width .
  ?hardware pv:height_mm ?height .
  ?hardware pv:depth_mm ?depth .
  FILTER ( ?width > ?height && ?depth < 50 )
}
ORDER BY ?hardware

There are 485 hardware items that are wider than they are tall and have a depth under 50 mm. The query returns their dimensions (width, height, depth) along with their identifiers.

Which hardware items are wider than they are tall, and have a depth under 50 mm? List their dimensions.

[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 are wider than they are tall, and have a depth under 50 mm? List their dimensions.

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

[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)

[Tool]
Top 10 property alternatives:
1. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
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. quantity (pv:quantity): The quantity needed., has domain BOM Part
5. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
6. type (rdf:type)
7. range (rdfs:range)
8. lat (wgs84:lat)
9. name (foaf:name):

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

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

[Tool]
Got 485 rows and 4 columns, showing the first 5 and last 5 rows below:
| hardware                                | width        | height       | depth        |
| --------------------------------------- | ------------ | ------------ | ------------ |
| hw A166 3766336 (prodi:hw-A166-3766336) | 77 (xsd:int) | 53 (xsd:int) | 14 (xsd:int) |
| hw A225 1988393 (prodi:hw-A225-1988393) | 77 (xsd:int) | 59 (xsd:int) | 18 (xsd:int) |
| hw A243 3332548 (prodi:hw-A243-3332548) | 46 (xsd:int) | 43 (xsd:int) | 17 (xsd:int) |
| hw A315 1730287 (prodi:hw-A315-1730287) | 74 (xsd:int) | 28 (xsd:int) | 12 (xsd:int) |
| hw A360 3041803 (prodi:hw-A360-3041803) | 62 (xsd:int) | 33 (xsd:int) | 14 (xsd:int) |
| ...                                     | ...          | ...          | ...          |
| hw Z872 5435339 (prodi:hw-Z872-5435339) | 37 (xsd:int) | 18 (xsd:int) | 19 (xsd:int) |
| hw Z889 8463159 (prodi:hw-Z889-8463159) | 61 (xsd:int) | 41 (xsd:int) | 15 (xsd:int) |
| hw Z927 4746244 (prodi:hw-Z927-4746244) | 69 (xsd:int) | 42 (xsd:int) | 18 (xsd:int) |
| hw Z980 8040792 (prodi:hw-Z980-8040792) | 42 (xsd:int) | 41 (xsd:int) | 17 (xsd:int) |
| hw Z994 6661823 (prodi:hw-Z994-6661823) | 57 (xsd:int) | 30 (xsd:int) | 15 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves hardware items that are wider than they are tall and have a depth under 50 mm, returning their dimensions as requested. The query uses appropriate filters and properties, and the execution result confirms it returns a substantial and relevant set of results. The answer clearly states the number of such hardware items and provides their dimensions, fulfilling the user's request accurately and completely.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?productA ?productALabel ?productB ?productBLabel WHERE {
  ?productA pv:compatibleProduct ?productB .
  ?productB pv:compatibleProduct ?productA .
  OPTIONAL {
    ?productA rdfs:label ?productALabel
  }
  OPTIONAL {
    ?productB rdfs:label ?productBLabel
  }
}
LIMIT 100

I found cycles of product compatibility where product A is compatible with product B and product B is compatible with product A. The query results include pairs of products with mutual compatibility, such as:
- D729-5737042 - Coil Resistor Warp and A145-1240844 - Bipolar-junction Coil Compensator Transducer
- I625-9097378 - Coil Compensator and A145-1240844 - Bipolar-junction Coil Compensator Transducer
- X235-5406274 - Sensor Transducer and A145-1240844 - Bipolar-junction Coil Compensator Transducer
- X204-1803083 - Crystal Strain Compensator and A145-1240844 - Bipolar-junction Coil Compensator Transducer
- H745-5284103 - Gauge Breaker Compensator and A166-3766336 - Aluminum LCD Driver Gauge

These pairs represent mutual compatibility cycles between products.

Show me any cycles of product compatibility — i.e. product A says it's compatible with B, and B says it's compatible with A (mutual pairs).

[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] Show me any cycles of product compatibility — i.e. product A says it's compatible with B, and B says it's compatible with A (mutual pairs).

[Assistant]
To find cycles of product compatibility where product A is compatible with product B and product B is compatible with product A, I need to identify the property that represents "compatibility" between products in the knowledge graph.

Step 1: Search for properties related to "compatibility" in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
2. eligible for (pv:eligibleFor): Valid product service combinations (bundles, accessories)., has domain Service, has range Product
3. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
4. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
5. type (rdf:type)
6. version Info (owl:versionInfo)
7. created (dct:created)
8. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
9. license (<http://creativecommons.org/ns#license>)
10. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware

[Assistant]
The property "compatible product" (pv:compatibleProduct) seems to represent compatibility between products. It has domain Product and range Product, which fits the requirement.

Step 2: I will now write a SPARQL query to find pairs of products A and B where A is compatible with B and B is compatible with A (mutual compatibility). I will also include optional labels for better readability.

[Tool]
Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| productA                                | productALabel                                     | productB                                | productBLabel                                               |
| --------------------------------------- | ------------------------------------------------- | --------------------------------------- | ----------------------------------------------------------- |
| hw D729 5737042 (prodi:hw-D729-5737042) | D729-5737042 - Coil Resistor Warp                 | hw A145 1240844 (prodi:hw-A145-1240844) | A145-1240844 - Bipolar-junction Coil Compensator Transducer |
| hw I625 9097378 (prodi:hw-I625-9097378) | I625-9097378 - Coil Compensator                   | hw A145 1240844 (prodi:hw-A145-1240844) | A145-1240844 - Bipolar-junction Coil Compensator Transducer |
| hw X235 5406274 (prodi:hw-X235-5406274) | X235-5406274 - Sensor Transducer                  | hw A145 1240844 (prodi:hw-A145-1240844) | A145-1240844 - Bipolar-junction Coil Compensator Transducer |
| hw X204 1803083 (prodi:hw-X204-1803083) | X204-1803083 - Crystal Strain Compensator         | hw A145 1240844 (prodi:hw-A145-1240844) | A145-1240844 - Bipolar-junction Coil Compensator Transducer |
| hw H745 5284103 (prodi:hw-H745-5284103) | H745-5284103 - Gauge Breaker Compensator          | hw A166 3766336 (prodi:hw-A166-3766336) | A166-3766336 - Aluminum LCD Driver Gauge                    |
| ...                                     | ...                                               | ...                                     | ...                                                         |
| hw M522 9124638 (prodi:hw-M522-9124638) | M522-9124638 - Flow LCD Resistor Encoder          | hw B519 3674576 (prodi:hw-B519-3674576) | B519-3674576 - LCD Crystal Encoder                          |
| hw P360 3765415 (prodi:hw-P360-3765415) | P360-3765415 - LCD Dipole                         | hw B519 3674576 (prodi:hw-B519-3674576) | B519-3674576 - LCD Crystal Encoder                          |
| hw F251 2666285 (prodi:hw-F251-2666285) | F251-2666285 - Bipolar-junction Strain Transducer | hw B523 5464510 (prodi:hw-B523-5464510) | B523-5464510 - Bipolar-junction Switch Transducer           |
| hw N269 8309461 (prodi:hw-N269-8309461) | N269-8309461 - LCD Potentiometer Warp             | hw B541 8783084 (prodi:hw-B541-8783084) | B541-8783084 - Flow Potentiometer Gauge                     |
| hw H374 8481414 (prodi:hw-H374-8481414) | H374-8481414 - Network Multiplexer Resonator      | hw B625 4480024 (prodi:hw-B625-4480024) | B625-4480024 - Sensor Resonator Compensator                 |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies pairs of products with mutual compatibility by checking that product A is compatible with product B and product B is compatible with product A. The query returns both the product identifiers and their labels, which is helpful for readability. The execution result confirms that the query returns relevant pairs of mutually compatible products, fulfilling the user's request accurately and completely. No further refinement is necessary.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
SELECT ( COUNT( DISTINCT ?supplier ) AS ?supplierCount ) WHERE {
  prodi:hw-K367-1320550 pv:compatibleProduct ?altProduct .
  ?altProduct pv:hasSupplier ?supplier .
}

Got 1 row and 1 column:
| supplierCount |
| ------------- |
| 6 (xsd:int)   |

There are 6 distinct suppliers that can deliver alternative compatible products for the K367 Strain Encoder.

How many suppliers can deliver alternative compatible products for the K367 Strain Encoder?

[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] How many suppliers can deliver alternative compatible products for the K367 Strain Encoder?

[Assistant]
To answer this question, I need to identify the entity representing the "K367 Strain Encoder" and then find suppliers that can deliver alternative compatible products for it.

Step 1: Search for the entity "K367 Strain Encoder" in the knowledge graph.
Step 2: Identify properties related to alternative compatible products for this entity.
Step 3: Identify suppliers that can deliver these alternative compatible products.
Step 4: Count the number of such suppliers.

I will start with step 1 and search for the entity "K367 Strain Encoder."

[Tool]
Top 10 entity alternatives:
1. prod cat Encoder (prodi:prod-cat-Encoder): is a Product Category
2. prod cat Strain (prodi:prod-cat-Strain): is a Product Category
3. hw K367 1320550 (prodi:hw-K367-1320550): is a Hardware
4. bom part 10 K367 1320550 (prodi:bom-part-10-K367-1320550): is a BOM Part
5. bom part 9 K367 1320550 (prodi:bom-part-9-K367-1320550): is a BOM Part
6. price hw K367 1320550 EUR (prodi:price-hw-K367-1320550-EUR): is a Price

[Assistant] The entity "hw K367 1320550" (prodi:hw-K367-1320550) seems to represent the "K367 Strain Encoder" as hardware. I will now look for properties related to alternative compatible products for this hardware entity.

[Tool]
Top 10 property alternatives:
1. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
2. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
3. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
4. type (rdf:type)
5. label (rdfs:label)
6. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
7. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
8. has product manager (pv:hasProductManager): The employee acting as the product manager of the product., has range Employee, has domain Product
9. ID (pv:id): The ID of a thing.
10. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware

No other items found

[Assistant]
The property "compatible product" (pv:compatibleProduct) is used to indicate alternative compatible products. Also, the property "supplier" (pv:hasSupplier) indicates the supplier of a product.

Next, I will query for suppliers that can deliver alternative compatible products for the hardware "hw K367 1320550" using these properties. I will count the distinct suppliers.

[Tool]
Got 1 row and 1 column:
| supplierCount |
| ------------- |
| 6 (xsd:int)   |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the distinct suppliers that can deliver alternative compatible products for the K367 Strain Encoder. It uses the appropriate properties and entities, and the execution result matches the provided answer. The query is well-formed and returns the expected result, so no further refinement is needed.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
SELECT ?agent ?agentLabel WHERE {
  ?agent pv:areaOfExpertise prodi:prod-cat-Transistor .
  OPTIONAL {
    ?agent rdfs:label ?agentLabel
  }
}

Got 4 rows and 2 columns:
| agent                                                                                | agentLabel          |
| -------------------------------------------------------------------------------------------------------------------- | ------------------- |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | Anamchara Foerstner |
| empl Erhard Fried@company org (<http://ld.company.org/prod-instances/empl-Erhard.Fried%40company.org>)               | Erhard Fried        |
| empl Lili Geier@company org (<http://ld.company.org/prod-instances/empl-Lili.Geier%40company.org>)                   | Lili Geier          |
| empl Manfred Foth@company org (<http://ld.company.org/prod-instances/empl-Manfred.Foth%40company.org>)               | Manfred Foth        |

The following agents have expertise in Transistors: Anamchara Foerstner, Erhard Fried, Lili Geier, and Manfred Foth.

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

You have access to the following knowledge graphs:
ck25 at http://localhost:9333

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

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

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

[User] Who has expertise in Transistors?

[Assistant]
To answer the question "Who has expertise in Transistors?", I will follow these steps:

1. Identify the entity "Transistors" in the knowledge graph.
2. Identify the property or relation that links a person or entity to their expertise.
3. Query the knowledge graph for entities (people or organizations) that have expertise in "Transistors".

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

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

[Assistant] The entity "Transistor" is found as a product category with the IRI prodi:prod-cat-Transistor. Next, I will search for properties that might relate a person or entity to expertise or knowledge about this product category. I will search for properties related to "expertise" or "knowledge" in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. area of expertise (pv:areaOfExpertise): The product category agent is expert for., has range Product Category, has domain Agent
2. contributor (dct:contributor)
3. 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]
The property "area of expertise" (pv:areaOfExpertise) seems to be the most relevant for linking an agent (person or entity) to their expertise in a product category. The domain is Agent and the range is Product Category, which fits our need.

Next, I will query for agents who have "Transistor" (prodi:prod-cat-Transistor) as their area of expertise.

[Tool]
Got 4 rows and 2 columns:
| agent                                                                                | agentLabel          |
| -------------------------------------------------------------------------------------------------------------------- | ------------------- |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | Anamchara Foerstner |
| empl Erhard Fried@company org (<http://ld.company.org/prod-instances/empl-Erhard.Fried%40company.org>)               | Erhard Fried        |
| empl Lili Geier@company org (<http://ld.company.org/prod-instances/empl-Lili.Geier%40company.org>)                   | Lili Geier          |
| empl Manfred Foth@company org (<http://ld.company.org/prod-instances/empl-Manfred.Foth%40company.org>)               | Manfred Foth        |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves agents with expertise in Transistors by querying the property 'areaOfExpertise' with the object 'prod-cat-Transistor'. The query returns the expected agents along with their labels, matching the human-readable answer. The query is well-formed, uses appropriate prefixes and properties, and the execution result confirms the correctness of the answer. No further refinement is needed.


PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX dbpedia: <http://dbpedia.org/resource/>
PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ( COUNT( ?supplier ) AS ?count ) WHERE {
  ?supplier rdf:type pv:Supplier .
  ?supplier pv:country dbpedia:France .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 9 (xsd:int) |

There are 9 suppliers in France.

How many suppliers do we have in France?

[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] How many suppliers do we have in France?

[Assistant]
To answer the question "How many suppliers do we have in France?" I need to identify the following:

1. The entity or class representing "suppliers" in the knowledge graph.
2. The property that indicates the location or country of the suppliers.
3. The entity or literal representing "France" in the knowledge graph.

I will start by searching for the entity "supplier" in the knowledge graph to understand how suppliers are represented.

[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] The entity representing suppliers is pv:Supplier. Next, I need to find the property that indicates the location or country of the suppliers. I will search for properties related to "location" or "country" for the entity pv:Supplier.

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

No other items found

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

No other items found

[Assistant] There are no direct properties related to location or country for the entity pv:Supplier. I will try to find if there is any property related to address or location in general in the knowledge graph that might be linked to suppliers. I will search for properties with the keyword "address".

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

8. name (pv:name): The name of something.
9. lat (wgs84:lat)
10. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country

[Assistant] I found a property "pv:country" which has the domain Supplier and range Country. This seems to be the property that links suppliers to their country. Now I need to find the entity representing France in the knowledge graph. I will search for the entity "France".

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

[Assistant] The entity representing France is dbpedia:France. Now I will write a SPARQL query to count the number of suppliers that have the country property set to France.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 9 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of suppliers located in France by filtering suppliers with the country property set to France. The query returns the expected result of 9, which matches the provided answer. The query uses appropriate entities and properties, and the execution result confirms the correctness. No further refinement is needed.


The knowledge graph does not contain any instances of products, nor any data about product prices or product compatibility. Therefore, it is not possible to answer the question with the current data.

For every product, list what other products it is compatible with and the price differences between both.

[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] For every product, list what other products it is compatible with and the price differences between both.

[Assistant]
To answer this question, I need to identify the properties related to product compatibility and product price in the knowledge graph. Then I will construct a query to list each product, the products it is compatible with, and the price differences between them.

Step 1: Search for entities related to "product" to confirm the product entity I should use.
Step 2: Search for properties related to "compatible" to find the compatibility property.
Step 3: Search for properties related to "price" to find the price property.
Step 4: Construct the SPARQL query to get the products, compatible products, and price differences.

I will start with step 1 and search for entities related to "product."

[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]
I found the entity "Product" with the IRI prefix pv:Product which represents anything that we make and/or sell. This seems to be the correct entity for products.

Next, I will search for properties related to "compatible" to find the property that indicates product compatibility.

[Tool]
Top 10 property alternatives:
1. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
2. eligible for (pv:eligibleFor): Valid product service combinations (bundles, accessories)., has domain Service, has range Product
3. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
4. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
5. type (rdf:type)
6. version Info (owl:versionInfo)
7. created (dct:created)
8. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
9. license (<http://creativecommons.org/ns#license>)
10. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware

[Assistant]
I found the property "compatible product" with the IRI prefix pv:compatibleProduct. It has domain Product and range Product, which indicates it is used to link compatible products.

Next, I will search for properties related to "price" to find the property that indicates the price of a product.

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

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

[Assistant]
I found the property "price" with the IRI prefix pv:price. It has domain Product and range Price. Additionally, the price amount is represented by the property pv:amount with domain Price.

Now I will construct a SPARQL query to list each product, the products it is compatible with, and the price differences between them. I will retrieve the price amounts for both products and calculate the difference.

I will proceed with the query construction and execution.

[Tool] Got no rows and 7 columns

[Assistant]
The query returned no results, which might indicate that the price information or compatibility links are not fully populated or structured differently in the knowledge graph.

I will try a simpler query to check if there are any products with prices at all. This will help verify if the price data is available and correctly linked.

[Tool] Got no rows and 2 columns

[Assistant]
There are no products with price amounts in the knowledge graph, which explains why the previous query returned no results.

I will now check if there are any products with compatible products at all to verify the compatibility data.

[Tool] Got no rows and 2 columns

[Assistant]
There are no products with compatible products linked in the knowledge graph either.

It seems that the knowledge graph does not contain data about product prices or product compatibility.

I will now check if there are any products at all in the knowledge graph.

[Tool] Got no rows and 1 columns

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified that the knowledge graph does not contain any instances of products, product prices, or compatibility information. Since the data required to answer the question is not present, it is appropriate that the system failed to find an answer. No SPARQL query could be constructed to retrieve the requested information. The explanation is clear and accurate, so the output is correct and complete in its current form.