Triple

T1932002
Position Surface form Disambiguated ID Type / Status
Subject Hans van Heeswijk E40965 entity
Predicate workLocation P7 FINISHED
Object Assen E132426 NE FINISHED

How this triple was built (2 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: Assen | Statement: [Hans van Heeswijk, workLocation, Assen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Assen
Context triple: [Hans van Heeswijk, workLocation, Assen]
  • A. Assen chosen
    Assen is a city in the northeastern Netherlands best known as the capital of the province of Drenthe and for hosting the annual TT Circuit motorcycle races.
  • B. Zandvoort
    Zandvoort is a Dutch coastal town on the North Sea known for its sandy beaches and the nearby Circuit Zandvoort motor racing track.
  • C. Enschede, Netherlands
    Enschede is a city in the eastern Netherlands known for its former textile industry, technical university, and location near the German border.
  • D. Arnhem
    Arnhem is a city in the eastern Netherlands best known as the site of a major World War II battle during Operation Market Garden.
  • E. Asten, Netherlands
    Asten is a town in the Dutch province of North Brabant known for its bell foundry and carillon manufacturing industry.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a8864711648190b07bed24ed76258e completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb297ec2c819092ad62d72005223d completed March 7, 2026, 5:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3ef29e0819081b37664224dee91 completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:35 p.m.