Triple

T16889157
Position Surface form Disambiguated ID Type / Status
Subject Route nationale 106 E421618 entity
Predicate locatedIn P40 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: [Route nationale 106, locatedIn, Lozère]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lozère
Context triple: [Route nationale 106, locatedIn, 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc3b5188190ac713b4d4166e961 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2c1eee48190bc906e658d7729a4 completed May 10, 2026, 5:39 p.m.
Created at: April 10, 2026, 5:29 a.m.