Triple

T3753313
Position Surface form Disambiguated ID Type / Status
Subject Nieuwkoop E81382 entity
Predicate locatedNear P294 FINISHED
Object Gouda E70496 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: Gouda | Statement: [Nieuwkoop, locatedNear, Gouda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gouda
Context triple: [Nieuwkoop, locatedNear, Gouda]
  • A. Gouda chosen
    Gouda is a historic Dutch city renowned worldwide for its namesake cheese, traditional cheese market, and well-preserved medieval architecture.
  • B. Maasdam cheese
    Maasdam cheese is a Dutch semi-hard cow's milk cheese similar to Swiss Emmental, known for its large holes, sweet nutty flavor, and good melting properties.
  • C. Edam
    Edam is a historic Dutch town in North Holland, internationally known for its namesake Edam cheese and traditional cheese markets.
  • D. Comté cheese
    Comté cheese is a traditional French cow’s milk cheese from the Jura region, known for its firm texture, complex nutty flavor, and long aging process.
  • E. Munster cheese
    Munster cheese is a strong-smelling, soft cow’s milk cheese from eastern France, especially known for its washed rind and pungent, tangy flavor.
  • 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_69ad8b19b7b08190a6188804e99c53e9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb9340e0819083215989718b4598 completed March 8, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e5044f3c8190969828966b37e729 completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:35 p.m.