Triple

T9191285
Position Surface form Disambiguated ID Type / Status
Subject Dauphiné E220592 entity
Predicate borders P224 FINISHED
Object Lyonnais E426772 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: Lyonnais | Statement: [Dauphiné, borders, Lyonnais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lyonnais
Context triple: [Dauphiné, borders, Lyonnais]
  • A. Lyonnais chosen
    Lyonnais is a historical region in east-central France centered around the city of Lyon, known for its rich cultural heritage, gastronomy, and role as a major economic hub.
  • B. Roannais
    Roannais is a natural region in central France known for its rolling countryside, agricultural landscapes, and proximity to the upper Loire River.
  • C. Brionnais
    Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
  • D. Auberjonois
    Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
  • E. Rousset
    Rousset is a French town in the Provence-Alpes-Côte d’Azur region known for hosting significant semiconductor and microelectronics facilities, including a major STMicroelectronics design center.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd5bf25c081909e651b67ef8ecc33 completed April 1, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c272f508190aade1769c88cf16d completed April 4, 2026, 12:32 a.m.
Created at: March 30, 2026, 7:24 p.m.