Triple

T3934784
Position Surface form Disambiguated ID Type / Status
Subject Georges Couthon E90882 entity
Predicate placeOfBirth P1 FINISHED
Object Auvergne E213603 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: Auvergne | Statement: [Georges Couthon, placeOfBirth, Auvergne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Auvergne
Context triple: [Georges Couthon, placeOfBirth, Auvergne]
  • A. Auvergne chosen
    Auvergne is a historic region in central France known for its volcanic landscapes, rural character, and Romanesque heritage.
  • B. Auvergnat
    Auvergnat is a variety of the Occitan language traditionally spoken in France’s Auvergne region and surrounding areas.
  • C. Auvergne-Rhône-Alpes region
    The Auvergne-Rhône-Alpes region is a large administrative region in east-central France known for its major cities like Lyon and Grenoble, diverse landscapes from the Alps to volcanic highlands, and strong industrial and agricultural economy.
  • D. Massif Central
    The Massif Central is a vast highland region in south-central France characterized by ancient volcanic mountains, plateaus, and deep river valleys.
  • E. Cévennes
    The Cévennes is a rugged mountainous region in south-central France known for its dramatic landscapes, chestnut forests, and historical role as a refuge for Protestant Huguenots.
  • 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_69aed95f26e0819094b0e71974543a19 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedcbf0188190a5e828707a77752a completed March 9, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69becf8f926481908f6e1cf33fc79a04 completed March 21, 2026, 5:04 p.m.
Created at: March 9, 2026, 3:23 p.m.