Triple

T9821257
Position Surface form Disambiguated ID Type / Status
Subject Eure-et-Loir E238535 entity
Predicate contains P35 FINISHED
Object Châteaudun E343531 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: Châteaudun | Statement: [Eure-et-Loir, contains, Châteaudun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Châteaudun
Context triple: [Eure-et-Loir, contains, Châteaudun]
  • A. Châteaudun chosen
    Châteaudun is a historic town in north-central France known for its medieval château overlooking the Loir River and its role as a gateway to the Loire Valley.
  • B. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • C. Montrichard
    Montrichard is a historic town in central France’s Loire Valley, known for its medieval castle, picturesque setting on the Cher River, and traditional regional architecture.
  • D. Poissy
    Poissy is a commune in the western suburbs of Paris, France, known for hosting Le Corbusier’s iconic modernist Villa Savoye.
  • E. Châtellerault
    Châtellerault is a historic town in western France, known for its former royal arms factory and its role as an important industrial and transport hub in the Vienne department.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3147ecc81908cfca84c05a367d9 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cb4b301c8190907d5e31ca7bb228 completed April 5, 2026, 8:51 p.m.
Created at: March 30, 2026, 8:31 p.m.