Triple

T2137047
Position Surface form Disambiguated ID Type / Status
Subject Ashford E46676 entity
Predicate twinnedWith P1072 FINISHED
Object Fougères E191224 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: Fougères | Statement: [Ashford, twinnedWith, Fougères]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fougères
Context triple: [Ashford, twinnedWith, Fougères]
  • A. Fougères chosen
    Fougères is a historic town in Brittany, northwestern France, known for its impressive medieval castle and well-preserved old quarter.
  • B. Langres
    Langres is a historic fortified town in northeastern France known for its well-preserved ramparts and as the birthplace of Enlightenment philosopher Denis Diderot.
  • C. Tournus
    Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
  • D. Yvetot
    Yvetot is a small town in the Seine-Maritime department of Normandy in northern France, historically known as the seat of a medieval "kingdom" within France.
  • E. Bourgueil
    Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbdff9254819094d27405478e29a0 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69b261af6c488190906432e93424c9d1 completed March 12, 2026, 6:48 a.m.
Created at: March 4, 2026, 7:44 p.m.