Triple

T10455084
Position Surface form Disambiguated ID Type / Status
Subject Munster E246530 entity
Predicate knownFor P22 FINISHED
Object Munster cheese E107185 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: Munster cheese | Statement: [Munster, knownFor, Munster cheese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munster cheese
Context triple: [Munster, knownFor, Munster cheese]
  • A. Munster cheese chosen
    Munster cheese is a strong-smelling, soft cow’s milk cheese from eastern France, especially known for its washed rind and pungent, tangy flavor.
  • B. Cheshire cheese
    Cheshire cheese is a traditional, crumbly British cow's milk cheese from the county of Cheshire, known as one of England's oldest recorded cheese varieties.
  • C. Salers cheese
    Salers cheese is a traditional French farmhouse cheese from the Auvergne region, known for its firm texture, rich, complex flavor, and production from raw cow’s milk.
  • D. Red Leicester cheese
    Red Leicester cheese is a traditional English hard cow's milk cheese known for its firm texture, rich nutty flavor, and distinctive orange-red color.
  • E. 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.
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fe47fee48190b38ec0466ff0165a completed April 7, 2026, 12:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87f10b45c81908f1d3128c65750f8 completed April 10, 2026, 4:39 a.m.
Created at: April 6, 2026, 12:17 p.m.