Triple

T4036452
Position Surface form Disambiguated ID Type / Status
Subject Aisne E83838 entity
Predicate contains P35 FINISHED
Object Thiérache E258527 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: Thiérache | Statement: [Aisne, contains, Thiérache]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thiérache
Context triple: [Aisne, contains, Thiérache]
  • A. Thiérache chosen
    Thiérache is a rural, historically fortified region in northern France known for its bocage landscapes, brick churches, and traditional dairy production.
  • B. Cottévrard
    Cottévrard is a small commune in the Seine-Maritime department of the Normandy region in northern France.
  • C. Creuse
    Creuse is a rural department in central France known for its sparsely populated landscapes, traditional agriculture, and part of the historic Limousin region.
  • D. Vallée de la Marne
    Vallée de la Marne is a key subregion of France’s Champagne wine area, known for its vineyards along the Marne River and its significant production of Pinot Meunier–based sparkling wines.
  • E. Val-d'Oise
    Val-d'Oise is a department in northern France that forms part of the Paris metropolitan region and includes both suburban areas and rural landscapes.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb349e648190b9f227df4cd76fa0 completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f15f0088190b2ec453183f0ca7f completed March 14, 2026, 3:30 p.m.
Created at: March 9, 2026, 3:36 p.m.