Triple

T13680014
Position Surface form Disambiguated ID Type / Status
Subject Aude E327974 entity
Predicate borders P224 FINISHED
Object Hérault E97297 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: Hérault | Statement: [Aude, borders, Hérault]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hérault
Context triple: [Aude, borders, Hérault]
  • A. Hérault chosen
    Hérault is a department in southern France known for its Mediterranean coastline, vineyards, and historic cities such as Montpellier and Béziers.
  • B. 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.
  • C. Lozère
    Lozère is a sparsely populated department in southern France known for its rugged landscapes, including parts of the Cévennes and numerous river valleys.
  • D. 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.
  • E. Aveyron
    Aveyron is a rural department in southern France known for its rugged landscapes, medieval villages, and traditional gastronomy including Roquefort cheese.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc66cbb088190907cb89dda8e4ebd completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a8416d808190bd9cb77e0dd0d4be completed May 3, 2026, 7:55 p.m.
Created at: April 9, 2026, 9:53 p.m.