Triple

T15454454
Position Surface form Disambiguated ID Type / Status
Subject Nivôse E371732 entity
Predicate precedes P97 FINISHED
Object Pluviôse E372843 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: Pluviôse | Statement: [Nivôse, precedes, Pluviôse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pluviôse
Context triple: [Nivôse, precedes, Pluviôse]
  • A. Pluviôse chosen
    Pluviôse is the fifth month of the French Republican Calendar, corresponding roughly to late January and early February and named for its typically rainy weather.
  • B. Nivôse
    Nivôse is the fourth month of the French Republican Calendar, corresponding roughly to late December and early January and associated with snow and winter.
  • C. Floréal
    Floréal is the eighth springtime month of the French Republican Calendar, named to evoke the flowering period of the year.
  • D. Fabvier
    Fabvier was a prominent French Philhellene and military officer who played a key role in supporting the Greek War of Independence in the early 19th century.
  • E. Prairial
    Prairial is the ninth month of the French Republican Calendar, corresponding roughly to late May and most of June and associated with the flowering of meadows.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f131b1481909ff099c3b844ee07 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2cfbae7881909602b187e5219a35 completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3:31 a.m.