Triple

T18992149
Position Surface form Disambiguated ID Type / Status
Subject La Marche E464711 entity
Predicate succeededBy P78 FINISHED
Object Indre department NE NERFINISHED

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: Indre department | Statement: [La Marche, succeededBy, Indre department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Indre department
Context triple: [La Marche, succeededBy, Indre department]
  • A. Indre department chosen
    The Indre department is an administrative region in central France known for its rural landscapes, historic towns, and location within the Centre-Val de Loire region.
  • B. Orne department
    Orne department is a largely rural administrative region in northwestern France’s Normandy, known for its historic towns, forests, and horse-breeding countryside.
  • C. Aude department
    The Aude department is an administrative region in southern France known for its historic towns, vineyards, and proximity to the Mediterranean coast.
  • D. Ain department
    Ain department is an administrative region in eastern France known for its diverse landscapes, historic towns, and proximity to both the Alps and the Swiss border.
  • E. Nord department
    The Nord department is an administrative region in northern Haiti known for its historic cities, including Cap-Haïtien, and its significant role in the country’s colonial and revolutionary history.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd01a56c81909694a128c66b21d7 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d67eedc88190bfb7b327b47db76d completed April 20, 2026, 7:32 a.m.
Created at: April 10, 2026, 12:01 p.m.