Triple

T1600773
Position Surface form Disambiguated ID Type / Status
Subject Franche-Comté E34385 entity
Predicate knownFor P22 FINISHED
Object Mont d'Or cheese E144929 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: Mont d'Or cheese | Statement: [Franche-Comté, knownFor, Mont d'Or cheese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mont d'Or cheese
Context triple: [Franche-Comté, knownFor, Mont d'Or cheese]
  • A. Mont d'Or cheese chosen
    Mont d'Or cheese is a soft, rich, washed-rind cow’s milk cheese from the Jura region of France, traditionally sold in a spruce-wood box and eaten warm and spoonable.
  • B. Roquefort
    Roquefort is a famous French blue cheese made from sheep's milk and aged in the natural caves of Roquefort-sur-Soulzon.
  • C. 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.
  • D. Camembert cheese
    Camembert cheese is a soft, creamy, surface-ripened cow’s milk cheese from France, famous for its bloomy white rind and rich, earthy flavor.
  • 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_69a885fdcb9c819081ce6f0b8cd477dd completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9094a27908190bf0d9b5d43617192 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad46aafce08190855f8e0b760ab5ac completed March 8, 2026, 9:51 a.m.
Created at: March 4, 2026, 7:28 p.m.