Triple

T15505502
Position Surface form Disambiguated ID Type / Status
Subject Vallée du Tarn E379069 entity
Predicate crossesDepartment P27425 FINISHED
Object Lozère E93541 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: Lozère | Statement: [Vallée du Tarn, crossesDepartment, Lozère]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lozère
Context triple: [Vallée du Tarn, crossesDepartment, Lozère]
  • A. Lozère chosen
    Lozère is a sparsely populated department in southern France known for its rugged landscapes, including parts of the Cévennes and numerous river valleys.
  • B. Drôme
    Drôme is a department in southeastern France known for its diverse landscapes, historic towns, and location between the Alps and the Rhône Valley.
  • C. Bouches-du-Rhône
    Bouches-du-Rhône is a department in southern France known for the city of Marseille, its Mediterranean coastline, and parts of the historic Provence region.
  • D. Hérault
    Hérault is a department in southern France known for its Mediterranean coastline, vineyards, and historic cities such as Montpellier and Béziers.
  • E. Pays de Lunel
    Pays de Lunel is a French intercommunal structure (communauté de communes) that groups together Lunel and neighboring municipalities in the Hérault department for cooperative local governance and shared public services.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fcd5d948190b25a67a72ef980e9 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d4cf35c8190aa8d2db6dd744c3f completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 3:55 a.m.