Triple

T3604721
Position Surface form Disambiguated ID Type / Status
Subject GelreDome E76341 entity
Predicate owner P347 FINISHED
Object Gemeente Arnhem
Gemeente Arnhem is the municipal government of the Dutch city of Arnhem, responsible for local administration, services, and urban development.
E388771 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Gemeente Arnhem | Statement: [GelreDome, owner, Gemeente Arnhem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gemeente Arnhem
Context triple: [GelreDome, owner, Gemeente Arnhem]
  • A. Harderwijk
    Harderwijk is a historic Dutch city known for its former Hanseatic trading role and scenic location on the shores of the Veluwemeer.
  • B. Gorinchem
    Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
  • C. Almelo
    Almelo is a city in the eastern Netherlands known for its industrial history and location in the province of Overijssel.
  • D. Wijchen
    Wijchen is a town and municipality in the Dutch province of Gelderland, located just southwest of the city of Nijmegen.
  • E. Amersfoort
    Amersfoort is a historic city in the province of Utrecht in the Netherlands, known for its well-preserved medieval center and strategic location as a rail and road hub.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gemeente Arnhem
Triple: [GelreDome, owner, Gemeente Arnhem]
Generated description
Gemeente Arnhem is the municipal government of the Dutch city of Arnhem, responsible for local administration, services, and urban development.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gemeente Arnhem
Target entity description: Gemeente Arnhem is the municipal government of the Dutch city of Arnhem, responsible for local administration, services, and urban development.
  • A. Harderwijk
    Harderwijk is a historic Dutch city known for its former Hanseatic trading role and scenic location on the shores of the Veluwemeer.
  • B. Gorinchem
    Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
  • C. Almelo
    Almelo is a city in the eastern Netherlands known for its industrial history and location in the province of Overijssel.
  • D. Wijchen
    Wijchen is a town and municipality in the Dutch province of Gelderland, located just southwest of the city of Nijmegen.
  • E. Amersfoort
    Amersfoort is a historic city in the province of Utrecht in the Netherlands, known for its well-preserved medieval center and strategic location as a rail and road hub.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad85d93dcc819094fba90cf70f4996 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc1e07bc481908d9fce18d36d8e0d completed March 8, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f01c47d881908e9489db7bf47b11 completed March 14, 2026, 5:20 a.m.
NEDg Description generation batch_69b4f0d7b6308190a0c823640b857ea4 completed March 14, 2026, 5:23 a.m.
NED2 Entity disambiguation (via description) batch_69b4f174f30881908231bde0d85aefdc completed March 14, 2026, 5:26 a.m.
Created at: March 8, 2026, 3:22 p.m.