Triple

T4125897
Position Surface form Disambiguated ID Type / Status
Subject Lac de Saint-Ferréol E92722 entity
Predicate region P40 FINISHED
Object Lauragais E99840 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: Lauragais | Statement: [Lac de Saint-Ferréol, region, Lauragais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lauragais
Context triple: [Lac de Saint-Ferréol, region, Lauragais]
  • A. Lauragais chosen
    Lauragais is a historic rural region in southwestern France known for its rolling agricultural landscapes, traditional villages, and strong Occitan cultural heritage.
  • B. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • C. Laumière
    Laumière is a Paris Métro station on the city’s northeastern side, located in the 19th arrondissement near the Canal de l’Ourcq.
  • D. Aiguillon
    Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
  • E. Largentière
    Largentière is a historic town in southern France known for its medieval architecture and former silver mining industry.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af0219f0e48190b0a925f09d858d65 completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e4d20dd0819080773876f6198250 completed March 14, 2026, 10:44 p.m.
Created at: March 9, 2026, 3:41 p.m.