PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?category ?categoryLabel ?lightestHardware ?lightestHardwareLabel ?heaviestHardware ?heaviestHardwareLabel ?minWeight ?maxWeight WHERE {
  {
    SELECT ?category ( MIN( ?weight ) AS ?minWeight ) ( MAX( ?weight ) AS ?maxWeight ) WHERE {
      ?hardware a pv:Hardware ; pv:hasCategory ?category ; pv:weight_g ?weight .
    }
    GROUP BY ?category
  }
  ?hardwareMin a pv:Hardware ; pv:hasCategory ?category ; pv:weight_g ?minWeight .
  ?hardwareMax a pv:Hardware ; pv:hasCategory ?category ; pv:weight_g ?maxWeight .
  OPTIONAL {
    ?hardwareMin rdfs:label ?lightestHardwareLabel
  }
  OPTIONAL {
    ?hardwareMax rdfs:label ?heaviestHardwareLabel
  }
  OPTIONAL {
    ?category rdfs:label ?categoryLabel
  }
  BIND( ?hardwareMin AS ?lightestHardware ) BIND( ?hardwareMax AS ?heaviestHardware )
}
ORDER BY ?category
LIMIT 100

Got 100 rows and 8 columns, showing the first 5 and last 5 rows below:
| category                                          | categoryLabel | lightestHardware                        | lightestHardwareLabel                         | heaviestHardware                        | heaviestHardwareLabel                                  | minWeight   | maxWeight    |
| ------------------------------------------------- | ------------- | --------------------------------------- | --------------------------------------------- | --------------------------------------- | ------------------------------------------------------ | ----------- | ------------ |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw C770 9751514 (prodi:hw-C770-9751514) | C770-9751514 - Transistor Resonator Breaker   | hw S859 8143033 (prodi:hw-S859-8143033) | S859-8143033 - Field-effect Breaker Strain Transformer | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw M770 3602005 (prodi:hw-M770-3602005) | M770-3602005 - Sensor Capacitor Breaker       | hw E835 1316991 (prodi:hw-E835-1316991) | E835-1316991 - Resistor Breaker                        | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw C770 9751514 (prodi:hw-C770-9751514) | C770-9751514 - Transistor Resonator Breaker   | hw E558 1962104 (prodi:hw-E558-1962104) | E558-1962104 - Planck Breaker Compensator              | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw M770 3602005 (prodi:hw-M770-3602005) | M770-3602005 - Sensor Capacitor Breaker       | hw S859 8143033 (prodi:hw-S859-8143033) | S859-8143033 - Field-effect Breaker Strain Transformer | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw C770 9751514 (prodi:hw-C770-9751514) | C770-9751514 - Transistor Resonator Breaker   | hw W176 3285571 (prodi:hw-W176-3285571) | W176-3285571 - Log-periodic Oscillator Breaker         | 1 (xsd:int) | 20 (xsd:int) |
| ...                                               | ...           | ...                                     | ...                                           | ...                                     | ...                                                    | ...         | ...          |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw I679 1230971 (prodi:hw-I679-1230971) | I679-1230971 - Memristor Compensator          | hw X204 1803083 (prodi:hw-X204-1803083) | X204-1803083 - Crystal Strain Compensator              | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw E868 5063965 (prodi:hw-E868-5063965) | E868-5063965 - Coil Compensator               | hw C605 1105328 (prodi:hw-C605-1105328) | C605-1105328 - Log-periodic Gauge Compensator Meter    | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw P163 9337479 (prodi:hw-P163-9337479) | P163-9337479 - Transistor Encoder Compensator | hw K473 9950981 (prodi:hw-K473-9950981) | K473-9950981 - Coil Compensator                        | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw Y467 5818685 (prodi:hw-Y467-5818685) | Y467-5818685 - Memristor Compensator          | hw K473 9950981 (prodi:hw-K473-9950981) | K473-9950981 - Coil Compensator                        | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw E868 5063965 (prodi:hw-E868-5063965) | E868-5063965 - Coil Compensator               | hw L592 1084147 (prodi:hw-L592-1084147) | L592-1084147 - Coil Potentiometer Compensator          | 1 (xsd:int) | 20 (xsd:int) |

The query returns, per product category, the lightest and heaviest hardware items with their weights. The results include the product category, the lightest hardware item and its weight, and the heaviest hardware item and its weight.

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 this question, I need to identify the following:
1. The entity or class representing "product category."
2. The entity or class representing "hardware item."
3. The property that links a hardware item to its product category.
4. The property that indicates the weight of a hardware item.

Step 1: Search for entities related to "product category" and "hardware item" in the knowledge graph.

[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.

[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. 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

[Tool] Got no rows and 3 columns

[Tool]
Got 2,339 rows and 3 columns, showing the first 10 rows below:
| subject                                   | property                      | object                                            |
| ----------------------------------------- | ----------------------------- | ------------------------------------------------- |
| srv N558 1730215 (prodi:srv-N558-1730215) | has category (pv:hasCategory) | prod cat Sensor (prodi:prod-cat-Sensor)           |
| hw A145 1240844 (prodi:hw-A145-1240844)   | has category (pv:hasCategory) | prod cat Compensator (prodi:prod-cat-Compensator) |
| hw A243 3332548 (prodi:hw-A243-3332548)   | has category (pv:hasCategory) | prod cat Crystal (prodi:prod-cat-Crystal)         |
| hw A909 7626614 (prodi:hw-A909-7626614)   | has category (pv:hasCategory) | prod cat Encoder (prodi:prod-cat-Encoder)         |
| hw A166 3766336 (prodi:hw-A166-3766336)   | has category (pv:hasCategory) | prod cat LCD (prodi:prod-cat-LCD)                 |
| hw A360 3041803 (prodi:hw-A360-3041803)   | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor)       |
| hw A816 3021832 (prodi:hw-A816-3021832)   | has category (pv:hasCategory) | prod cat Breaker (prodi:prod-cat-Breaker)         |
| hw A599 2465791 (prodi:hw-A599-2465791)   | has category (pv:hasCategory) | prod cat Memristor (prodi:prod-cat-Memristor)     |
| hw A595 2446575 (prodi:hw-A595-2446575)   | has category (pv:hasCategory) | prod cat Capacitor (prodi:prod-cat-Capacitor)     |
| hw A315 1730287 (prodi:hw-A315-1730287)   | has category (pv:hasCategory) | prod cat Network (prodi:prod-cat-Network)         |
| ...                                       | ...                           | ...                                               |

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

[Tool]
Got 1 row and 3 columns:
| subject                                 | property                 | object       |
| --------------------------------------- | ------------------------ | ------------ |
| hw A145 1240844 (prodi:hw-A145-1240844) | weight (g) (pv:weight_g) | 14 (xsd:int) |

[Assistant]
I found that hardware items are instances of pv:Hardware and they have a property pv:hasCategory linking them to a product category (pv:ProductCategory). The weight of hardware items is given by the property pv:weight_g (weight in grams).

Next, I will write a SPARQL query to get, per product category, the lightest and heaviest hardware items based on their weight. I will use aggregation and grouping to achieve this.

[Tool]
Got 100 rows and 8 columns, showing the first 5 and last 5 rows below:
| category                                          | categoryLabel | lightestHardware                        | lightestHardwareLabel                         | heaviestHardware                        | heaviestHardwareLabel                                  | minWeight   | maxWeight    |
| ------------------------------------------------- | ------------- | --------------------------------------- | --------------------------------------------- | --------------------------------------- | ------------------------------------------------------ | ----------- | ------------ |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw C770 9751514 (prodi:hw-C770-9751514) | C770-9751514 - Transistor Resonator Breaker   | hw S859 8143033 (prodi:hw-S859-8143033) | S859-8143033 - Field-effect Breaker Strain Transformer | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw M770 3602005 (prodi:hw-M770-3602005) | M770-3602005 - Sensor Capacitor Breaker       | hw E835 1316991 (prodi:hw-E835-1316991) | E835-1316991 - Resistor Breaker                        | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw C770 9751514 (prodi:hw-C770-9751514) | C770-9751514 - Transistor Resonator Breaker   | hw E558 1962104 (prodi:hw-E558-1962104) | E558-1962104 - Planck Breaker Compensator              | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw M770 3602005 (prodi:hw-M770-3602005) | M770-3602005 - Sensor Capacitor Breaker       | hw S859 8143033 (prodi:hw-S859-8143033) | S859-8143033 - Field-effect Breaker Strain Transformer | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Breaker (prodi:prod-cat-Breaker)         | Breaker       | hw C770 9751514 (prodi:hw-C770-9751514) | C770-9751514 - Transistor Resonator Breaker   | hw W176 3285571 (prodi:hw-W176-3285571) | W176-3285571 - Log-periodic Oscillator Breaker         | 1 (xsd:int) | 20 (xsd:int) |
| ...                                               | ...           | ...                                     | ...                                           | ...                                     | ...                                                    | ...         | ...          |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw I679 1230971 (prodi:hw-I679-1230971) | I679-1230971 - Memristor Compensator          | hw X204 1803083 (prodi:hw-X204-1803083) | X204-1803083 - Crystal Strain Compensator              | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw E868 5063965 (prodi:hw-E868-5063965) | E868-5063965 - Coil Compensator               | hw C605 1105328 (prodi:hw-C605-1105328) | C605-1105328 - Log-periodic Gauge Compensator Meter    | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw P163 9337479 (prodi:hw-P163-9337479) | P163-9337479 - Transistor Encoder Compensator | hw K473 9950981 (prodi:hw-K473-9950981) | K473-9950981 - Coil Compensator                        | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw Y467 5818685 (prodi:hw-Y467-5818685) | Y467-5818685 - Memristor Compensator          | hw K473 9950981 (prodi:hw-K473-9950981) | K473-9950981 - Coil Compensator                        | 1 (xsd:int) | 20 (xsd:int) |
| prod cat Compensator (prodi:prod-cat-Compensator) | Compensator   | hw E868 5063965 (prodi:hw-E868-5063965) | E868-5063965 - Coil Compensator               | hw L592 1084147 (prodi:hw-L592-1084147) | L592-1084147 - Coil Potentiometer Compensator          | 1 (xsd:int) | 20 (xsd:int) |

[Tool] Stopped generation process


I could not find the product 'SkySync MechWave' or its BOM parts in the knowledge graph. Additionally, the BOM parts present in the knowledge graph do not have linked suppliers or countries. Therefore, I am unable to determine the countries from which the BOM parts of 'SkySync MechWave' are delivered.

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]
To answer this question, I need to identify the following:
1. The entity representing "SkySync MechWave" in the knowledge graph.
2. The BOM (Bill of Materials) parts associated with "SkySync MechWave."
3. The countries from which these BOM parts are delivered.

Step 1: Search for the entity "SkySync MechWave" in the knowledge graph.

[Tool] No entity items found

[Assistant] I could not find an entity named "SkySync MechWave" in the knowledge graph. I will try searching for just "SkySync" to see if there is a related entity.

[Tool] No entity items found

[Assistant]
I could not find any entity related to "SkySync" or "SkySync MechWave" in the knowledge graph. It is possible that the product name is stored differently or under another identifier.

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

[Tool] No entity items found

[Assistant]
There are no entities related to "SkySync MechWave" or its components in the knowledge graph. Without the exact entity or identifier for the product or its BOM parts, I cannot proceed to find the countries from which the BOM parts are delivered.

I will now try a different approach by searching for entities related to "BOM parts" or "parts" to see if there is any relevant information about parts and their delivery countries.

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

[Assistant]
I found an entity "BOM Part" (pv:BomPart) which represents parts in a Bill of Material (BOM). There are also several BOM instances (prodi:bom-4, prodi:bom-19, etc.).

Next, I will try to find if there is any product related to "SkySync MechWave" or similar in the knowledge graph by searching for products or instances with "SkySync" or "MechWave" in their labels or descriptions.

[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 a general entity "Product" (pv:Product) which represents anything that is made and/or sold.

Next, I will try to find products with labels or descriptions containing "SkySync" or "MechWave" by searching for entities of type pv:Product and filtering by label or description.

[Tool] Got no rows and 2 columns

[Assistant]
There are no products with labels containing "SkySync" or "MechWave" in the knowledge graph.

Since I cannot find the specific product "SkySync MechWave," I cannot directly find its BOM parts or the countries from which they are delivered.

I will now try to find a general pattern of how BOM parts and their delivery countries are represented in the knowledge graph by exploring properties of BOM parts and any related delivery or country information. I will start by listing properties of the entity pv:BomPart.

[Tool]
Got 5 rows and 3 columns:
| subject               | property                         | object                                                                                |
| --------------------- | -------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- |
| BOM Part (pv:BomPart) | type (rdf:type)                  | Class (owl:Class)                                                                                |
| BOM Part (pv:BomPart) | label (rdfs:label)               | BOM Part (en)                                                                                |
| BOM Part (pv:BomPart) | is Defined By (rdfs:isDefinedBy) | pv: Products - Vocab (pv:)                                                                                |
| BOM Part (pv:BomPart) | comment (rdfs:comment)           | A (number of) part(s) in a BOM. (en)                                                                                |
| BOM Part (pv:BomPart) | depiction (foaf:depiction)       | puzzle cube piece 20 filled svg?color=#D6AF00&format=svg (<https://api.iconify.design/fluent/puzzle-cube-piece-20-filled.svg?color=%23D6AF00&format=svg>) |

[Assistant]
The class pv:BomPart represents parts in a BOM, but this does not give information about properties related to delivery or countries.

I will now try to find properties related to delivery or country by searching for properties with keywords "delivery" and "country" in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
2. quantity (pv:quantity): The quantity needed., has domain BOM Part
3. address text (pv:addressText): The address text., has domain Agent
4. email (pv:email): The e-mail of an agent., has domain Agent
5. label (rdfs:label)
6. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product
7. phone number (pv:phone): has domain Agent, A phone number.
8. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
9. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
10. type (rdf:type)

[Assistant]
I found a relevant property "supplier" (pv:hasSupplier) which links a product to its supplier, and a property "country" (pv:country) which indicates the country where the supplier is located. The domain of pv:country is Supplier.

This suggests that BOM parts may have suppliers, and suppliers have countries.

Next, I will try to find BOM parts and their suppliers and countries by querying for BOM parts, their suppliers, and the countries of those suppliers.

[Tool]
Got 20 rows and 6 columns, showing the first 5 and last 5 rows below:
| bomPart                                                   | bomPartLabel      | supplier | supplierLabel | country | countryLabel |
| --------------------------------------------------------- | ----------------- | -------- | ------------- | ------- | ------------ |
| bom part 1 C247 3833661 (prodi:bom-part-1-C247-3833661)   | C247-3833661 (72) |          |               |         |              |
| bom part 1 E355 4376121 (prodi:bom-part-1-E355-4376121)   | E355-4376121 (70) |          |               |         |              |
| bom part 1 G826 1197003 (prodi:bom-part-1-G826-1197003)   | G826-1197003 (73) |          |               |         |              |
| bom part 1 N560 4369045 (prodi:bom-part-1-N560-4369045)   | N560-4369045 (52) |          |               |         |              |
| bom part 1 P253 1288849 (prodi:bom-part-1-P253-1288849)   | P253-1288849 (38) |          |               |         |              |
| ...                                                       | ...               | ...      | ...           | ...     | ...          |
| bom part 10 W986 7950553 (prodi:bom-part-10-W986-7950553) | W986-7950553 (10) |          |               |         |              |
| bom part 10 X716 6172862 (prodi:bom-part-10-X716-6172862) | X716-6172862 (90) |          |               |         |              |
| bom part 11 B646 2108570 (prodi:bom-part-11-B646-2108570) | B646-2108570 (23) |          |               |         |              |
| bom part 11 G439 8153345 (prodi:bom-part-11-G439-8153345) | G439-8153345 (96) |          |               |         |              |
| bom part 11 H173 1200706 (prodi:bom-part-11-H173-1200706) | H173-1200706 (63) |          |               |         |              |

[Assistant]
I found BOM parts in the knowledge graph, but none of them have suppliers or countries linked.

Since I cannot find the specific product "SkySync MechWave" or its BOM parts, and the BOM parts in general do not have supplier or country information, I am unable to answer the question about the countries from which the BOM parts of "SkySync MechWave" are delivered.

I will now provide a final response explaining this.

[Tool] Stopped generation process


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

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" in the knowledge graph ck25.

[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>. Next, 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. Now I will query the knowledge graph to find the manager of Heinrich Hoch using this property.

[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


PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?hardware ?width ?height ?depth WHERE {
  ?hardware a 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 hardware items that are wider than they are tall and have a depth under 50 mm. The query returns their dimensions including width, height, and depth in millimeters. For example, hw A166 3766336 has width 77 mm, height 53 mm, and depth 14 mm. The query result includes 485 such hardware items with their dimensions.

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]
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


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

There are multiple cycles of product compatibility (mutual pairs) in the knowledge graph. For example, product D729-5737042 - Coil Resistor Warp is compatible with product A145-1240844 - Bipolar-junction Coil Compensator Transducer, and vice versa. Similarly, product I625-9097378 - Coil Compensator is compatible with product A145-1240844 - Bipolar-junction Coil Compensator Transducer, and vice versa. The query found 100 such mutual compatibility pairs.

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: Construct a SPARQL query to find pairs of products (A, 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                                | labelA                                            | productB                                | labelB                                                      |
| --------------------------------------- | ------------------------------------------------- | --------------------------------------- | ----------------------------------------------------------- |
| 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


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

Got 1 row and 1 column:
| countSuppliers |
| -------------- |
| 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 following:
1. The entity representing the "K367 Strain Encoder."
2. The property or relation that links this product to its alternative compatible products.
3. The suppliers that can deliver these alternative compatible products.

Step 1: Search for the entity "K367 Strain Encoder" in the knowledge graph.

[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. Next, I will search for properties related to alternative compatible products for this 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) seems to represent alternative compatible products. Next, I will find the suppliers that can deliver these compatible products for the K367 Strain Encoder.

[Tool]
Got 6 rows and 1 column:
| supplier                                                                                |
| --------------------------------------------------------------------------------------------- |
| suppl 06d152e4 f062 46da b6be 750b192a5a4b (prodi:suppl-06d152e4-f062-46da-b6be-750b192a5a4b) |
| suppl 79274f67 b225 49fa ad8c fb20560cb1d5 (prodi:suppl-79274f67-b225-49fa-ad8c-fb20560cb1d5) |
| suppl 7f696243 08d9 458c 8041 e114a223b897 (prodi:suppl-7f696243-08d9-458c-8041-e114a223b897) |
| suppl 8f607810 ca93 4274 9c27 d0a8dcba7c4a (prodi:suppl-8f607810-ca93-4274-9c27-d0a8dcba7c4a) |
| suppl ee3143c4 d3eb 4457 b884 651cac99ee9d (prodi:suppl-ee3143c4-d3eb-4457-b884-651cac99ee9d) |
| suppl f76eb805 4d84 4b4b 9aa3 95c287be41d0 (prodi:suppl-f76eb805-4d84-4b4b-9aa3-95c287be41d0) |

[Assistant] There are 6 distinct suppliers that can deliver alternative compatible products for the K367 Strain Encoder. I will now provide the final answer with the SPARQL query used.

[Tool] Stopped generation process


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?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 to find 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" exists as a product category with the identifier prodi:prod-cat-Transistor. Next, I will search for properties related to expertise or skills that might link a person or entity to this product category. I will search for properties related to "expertise".

[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, with the range being Product Category. This fits well with the entity "Transistor" which is a product category.

Next, I will query the knowledge graph to find agents who have "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


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX dbpedia: <http://dbpedia.org/resource/>
SELECT ( COUNT( DISTINCT ?supplier ) AS ?count ) WHERE {
  ?supplier rdf:type pv: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 links suppliers to their location or country.
3. The entity 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]
I found an entity "Supplier" with the IRI prefix pv:Supplier which represents the supplier of some items. This seems to be the class or entity representing suppliers.

Next, I will search for properties related to the entity pv:Supplier to find a property that links suppliers to their location or country.

[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

[Assistant]
The search for properties related to "location" for the entity pv:Supplier did not return any specific property linking suppliers to their location or country.

I will try a broader search for properties related to "country" or "address" for the entity pv:Supplier.

[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

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

No other items found

[Assistant]
There are no direct properties related to location, country, or address for the entity pv:Supplier.

I will try to find if there is any property that links suppliers to some other entity that might represent location or country. I will search for properties with the object "Supplier" to see if suppliers are linked from other entities.

[Tool]
No entity items found

No other items found

No literal items found

[Assistant]
There are no properties with the object "Supplier" that can help us find location information indirectly.

I will now search for the entity "France" to see how it is represented in the knowledge graph. This might help me identify if there is a location or country entity that suppliers could be linked to.

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

[Assistant]
The entity representing France is dbpedia:France.

Since I could not find a direct property linking suppliers to a location or country, I will try to find all instances of suppliers and check if any property links them to dbpedia:France.

I will start by listing some triples with the subject pv:Supplier to see if there are any properties that might indicate location or country.

[Tool]
Got 5 rows and 3 columns:
| subject                | property                         | object                                                                                |
| ---------------------- | -------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| Supplier (pv:Supplier) | type (rdf:type)                  | Class (owl:Class)                                                                                |
| Supplier (pv:Supplier) | label (rdfs:label)               | Supplier (en)                                                                                |
| Supplier (pv:Supplier) | is Defined By (rdfs:isDefinedBy) | pv: Products - Vocab (pv:)                                                                                |
| Supplier (pv:Supplier) | comment (rdfs:comment)           | The Supplier of some item(s). (en)                                                                             |
| Supplier (pv:Supplier) | depiction (foaf:depiction)       | company svg?color=#D6AF00&format=svg (<https://api.iconify.design/mdi/company.svg?color=%23D6AF00&format=svg>) |

[Assistant]
The entity pv:Supplier is a class with no direct properties indicating location or country.

I will now try to find instances of suppliers in the knowledge graph by searching for entities of type pv:Supplier. This might help me find properties related to location or country for those instances.

[Tool]
Got 10 rows and 1 column:
| supplier                                                                                |
| --------------------------------------------------------------------------------------------- |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) |
| suppl 0301f65d 2290 456b a3f7 b2096a632198 (prodi:suppl-0301f65d-2290-456b-a3f7-b2096a632198) |
| suppl 034022f5 5327 45c2 aaff 524b1be2fbd5 (prodi:suppl-034022f5-5327-45c2-aaff-524b1be2fbd5) |
| suppl 05b5a686 c821 41c4 bc2c b66d35bac1d8 (prodi:suppl-05b5a686-c821-41c4-bc2c-b66d35bac1d8) |
| suppl 06034b22 8e1b 435f 902e 88739f77d86a (prodi:suppl-06034b22-8e1b-435f-902e-88739f77d86a) |
| suppl 06d152e4 f062 46da b6be 750b192a5a4b (prodi:suppl-06d152e4-f062-46da-b6be-750b192a5a4b) |
| suppl 07335cfb 9bbc 4be5 b546 bdd8af104e7e (prodi:suppl-07335cfb-9bbc-4be5-b546-bdd8af104e7e) |
| suppl 0817f6f5 8011 4c46 aeab ba89def6df14 (prodi:suppl-0817f6f5-8011-4c46-aeab-ba89def6df14) |
| suppl 092bb1b2 b39f 4521 9c21 c853db9d9a09 (prodi:suppl-092bb1b2-b39f-4521-9c21-c853db9d9a09) |
| suppl 0c327a40 c6d8 44da ba2d e84f924c5208 (prodi:suppl-0c327a40-c6d8-44da-ba2d-e84f924c5208) |

[Assistant]
I found instances of suppliers in the knowledge graph. Now I will check the properties of one of these supplier instances to see if there is any property indicating location or country.

I will list the properties of the first supplier instance prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a.

[Tool]
Got 10 rows and 3 columns:
| subject                                                                                | property                                     | object                               |
| --------------------------------------------------------------------------------------------- | -------------------------------------------- | ------------------------------------ |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | type (rdf:type)                              | Supplier (pv:Supplier)               |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | label (rdfs:label)                           | Allen-Short (South Africa)           |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | name (pv:name)                               | Allen-Short                          |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | ID (pv:id)                                   | 0058fc5e-e9e8-46eb-ac6d-673e436a5d7a |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | address country (pv:addressCountry)          | South Africa                         |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | address country code (pv:addressCountryCode) | ZA                                   |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | address locality (pv:addressLocality)        | Mondlo                               |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | lat (wgs84:lat)                              | -27.958203                           |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | long (wgs84:long)                            | 30.7196884                           |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | country (pv:country)                         | South Africa (dbpedia:South_Africa)  |

[Assistant]
The supplier instance prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a has properties indicating location:
- pv:addressCountry with literal value "South Africa"
- pv:addressCountryCode with literal value "ZA"
- pv:addressLocality with literal value "Mondlo"
- pv:country linking to dbpedia:South_Africa

This means suppliers have a property pv:country linking to a country entity.

I will now check if there is a supplier with pv:country dbpedia:France to count how many suppliers are in France.

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

[Tool] Stopped generation process


The knowledge graph does not contain any data or properties related to product compatibility (pv:compatibleProduct) or product price (pv:price) for the entity pv:Product. Queries to find compatible products and price information returned no results, indicating that this information is either not present or stored differently. Therefore, it is not possible to generate a SPARQL query that lists products, their compatible products, and the price differences between them based on the available 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 using the identified entities and properties.

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 which has domain Product and range Product. This property indicates product compatibility.

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 which has domain Product and range Price. Additionally, the price entity seems to have properties "currency" and "amount" which might be useful to get the actual price value.

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.

[Tool] Got no rows and 7 columns

[Assistant]
The query returned no results, which might indicate that the data is not structured exactly as assumed or that some products do not have compatible products or price information filled in.

I will try a simpler query to check if there are any products with compatible products at all.

[Tool] Got no rows and 4 columns

[Assistant]
There are no triples with the property pv:compatibleProduct linking products in the dataset. This means the compatibility information might be stored differently or not present.

I will now check if there are any products with price information at all.

[Tool] Got no rows and 4 columns

[Assistant]
There are no triples with the property pv:price linking products to price information in the dataset either. This suggests that the price information might be stored differently or not present.

I will now try to find any properties related to price for products by searching for properties of the entity pv:Product related to "price".

[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

[Assistant]
There are no properties directly related to price for the entity pv:Product in the dataset.

Given the lack of data on product compatibility and price in the knowledge graph, I am unable to construct a query that answers the question as requested.

I will now provide a detailed explanation and cancel the query generation.

[Tool] Stopped generation process