Triple

T5995362
Position Surface form Disambiguated ID Type / Status
Subject Indre-et-Loire E133453 entity
Predicate contains P35 FINISHED
Object Chinon E76462 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: Chinon | Statement: [Indre-et-Loire, contains, Chinon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chinon
Context triple: [Indre-et-Loire, contains, Chinon]
  • A. Chinon chosen
    Chinon is a renowned Loire Valley wine appellation in France, best known for its elegant, medium-bodied red wines primarily made from Cabernet Franc.
  • B. Amboise
    Amboise is a historic town in central France on the Loire River, known for its royal château and as the place where Leonardo da Vinci spent his final years.
  • C. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • D. Lusignan, Vienne
    Lusignan, Vienne is a commune in western France historically notable as the ancestral seat of the medieval Lusignan noble dynasty.
  • E. 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.
  • 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_69c00870ddbc81909880fa3864f4f38d completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04e943dcc8190a09817e8ef0e4188 completed March 22, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11cd900a48190b5aa83c28b3dfc1a completed March 23, 2026, 10:58 a.m.
Created at: March 22, 2026, 4:05 p.m.