Triple

T22835464
Position Surface form Disambiguated ID Type / Status
Subject Gare d'Amboise E565932 entity
Predicate connectsTo P845 FINISHED
Object Blois NE NERFINISHED

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: Blois | Statement: [Gare d'Amboise, connectsTo, Blois]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blois
Context triple: [Gare d'Amboise, connectsTo, Blois]
  • A. Blois chosen
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • B. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • C. Melun
    Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
  • D. Pithiviers
    Pithiviers is a small town in north-central France known for its historical architecture and traditional French pastries.
  • E. La Châtre
    La Châtre is a small historic town in central France known for its picturesque medieval streets and its association with the writer George Sand.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245869e188190a196584f36e682da completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17e2e3e7481909d12dc5008136880 completed April 29, 2026, 3:42 a.m.
Created at: April 17, 2026, 3:35 p.m.