Triple

T3795170
Position Surface form Disambiguated ID Type / Status
Subject Gard E89752 entity
Predicate borderedBy 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: [Gard, borderedBy, Hérault]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hérault
Context triple: [Gard, borderedBy, 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. Aveyron
    Aveyron is a rural department in southern France known for its rugged landscapes, medieval villages, and traditional gastronomy including Roquefort cheese.
  • E. Rouergue
    Rouergue is a historic cultural region in southern France, centered around the present-day Aveyron department and known for its rural landscapes, medieval towns, and Occitan heritage.
  • 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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee79db2e88190b3aa2b8e8d885e19 completed March 9, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb232650819089feed9d5bb8c91a completed March 14, 2026, 6:07 a.m.
Created at: March 9, 2026, 3:15 p.m.