Triple

T1162404
Position Surface form Disambiguated ID Type / Status
Subject Touraine E24522 entity
Predicate containsCity P294 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: [Touraine, containsCity, Chinon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chinon
Context triple: [Touraine, containsCity, 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. 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.
  • E. Brienne-le-Château
    Brienne-le-Château is a commune in northeastern France best known as the town where Napoleon Bonaparte attended military school in his youth.
  • 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_69a494060e148190abb42f971242c197 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bcb2bb84819088bd94e91c10fb0c completed March 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69acb2f6f3e4819099310a5e21455c21 completed March 7, 2026, 11:21 p.m.
Created at: March 1, 2026, 7:45 p.m.