Triple

T20489759
Position Surface form Disambiguated ID Type / Status
Subject David Séchard E502706 entity
Predicate conflictWith P4897 FINISHED
Object Cérizet 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: Cérizet | Statement: [David Séchard, conflictWith, Cérizet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cérizet
Context triple: [David Séchard, conflictWith, Cérizet]
  • A. Cérizet chosen
    Cérizet is a scheming, opportunistic former clerk who becomes a key antagonist in Honoré de Balzac’s novel "Les Souffrances de l’inventeur."
  • B. Ceret
    Ceret is a historic town in southern France’s Pyrénées-Orientales, renowned for its modern art museum and strong Catalan cultural heritage.
  • C. Cèze
    The Cèze is a river in southern France known for its scenic gorges, clear waters, and popular swimming and canoeing spots.
  • D. Monpezat
    Monpezat is a French noble family name associated with Prince Henrik of Denmark and his descendants.
  • E. Cressat
    Cressat is a small rural commune in central France’s Creuse department, characterized by its agricultural landscape and traditional village setting.
  • 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_69e0b4b0373881909dd3e9387f82eab4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69b5d93ec81908259696359090b35 completed April 20, 2026, 9:32 p.m.
Created at: April 16, 2026, 11:34 a.m.