Triple

T11081653
Position Surface form Disambiguated ID Type / Status
Subject Libourne E262008 entity
Predicate demonym P191 FINISHED
Object Libournais E313294 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: Libournais | Statement: [Libourne, demonym, Libournais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Libournais
Context triple: [Libourne, demonym, Libournais]
  • A. Libournais chosen
    Libournais is a renowned wine-producing region on Bordeaux’s Right Bank in southwestern France, known for its Merlot-dominant red wines and appellations such as Pomerol and Saint-Émilion.
  • B. Lyonnais
    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.
  • C. Loulé
    Loulé is a historic market town and municipality in southern Portugal known for its traditional architecture, lively festivals, and role as a cultural and commercial center in the Algarve region.
  • D. Donin
    Donin is a surname that appears as a variant spelling of Donen.
  • E. Brionnais
    Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799985650819089b2c0f35a212414 completed April 9, 2026, 12:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e789d7248190a40de0bdda539f45 completed April 18, 2026, 8:20 p.m.
Created at: April 8, 2026, 9:27 p.m.