Triple

T10215418
Position Surface form Disambiguated ID Type / Status
Subject Massif des Bauges E242427 entity
Predicate containsVillage P4011 FINISHED
Object La Motte-en-Bauges E678130 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: La Motte-en-Bauges | Statement: [Massif des Bauges, containsVillage, La Motte-en-Bauges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Motte-en-Bauges
Context triple: [Massif des Bauges, containsVillage, La Motte-en-Bauges]
  • A. Verrières
    Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
  • B. Escoutoux
    Escoutoux is a small commune in central France’s Puy-de-Dôme department, known for its rural setting in the Auvergne region.
  • C. Vernouillet
    Vernouillet is a commune in northern France located in the Eure-et-Loir department in the Centre-Val de Loire region.
  • D. La Motte
    La Motte is a central character in Ann Radcliffe’s Gothic novel "The Romance of the Forest," depicted as a troubled, morally conflicted man whose actions drive much of the story’s suspense and mystery.
  • E. La Motte chosen
    La Motte is a small commune in southeastern France’s Var department, known for its Provençal countryside, vineyards, and proximity to the Mediterranean coast.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa2894d0819095704449ecc2db6c completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d652f1ffb88190986ea53749fc5e03 completed April 8, 2026, 1:06 p.m.
Created at: April 6, 2026, 11:04 a.m.