Triple

T2900409
Position Surface form Disambiguated ID Type / Status
Subject Foreign Legion E62639 entity
Predicate trainingLocation P40 FINISHED
Object Castelnaudary E115426 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: Castelnaudary | Statement: [Foreign Legion, trainingLocation, Castelnaudary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Castelnaudary
Context triple: [Foreign Legion, trainingLocation, Castelnaudary]
  • A. Castelnaudary chosen
    Castelnaudary is a historic market town in southern France renowned as a culinary capital for its traditional cassoulet dish.
  • B. Montauban
    Montauban is a historic city in southern France known for its red-brick architecture and role as the capital of the Tarn-et-Garonne department.
  • C. Castelroussin
    Castelroussin is the French demonym for an inhabitant of the city of Châteauroux in central France.
  • D. Castelsarrasin
    Castelsarrasin is a commune in the Tarn-et-Garonne department in southern France, known as a historic town on the banks of the Garonne River.
  • E. Draguignan
    Draguignan is a town in southeastern France’s Var department, known as a former prefecture and gateway to the Provence region.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0b081308190af8875151fb11c4e completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc5925a481908e89f51ad4056708 completed March 11, 2026, 5:23 a.m.
Created at: March 6, 2026, 10:10 p.m.