Triple

T15605393
Position Surface form Disambiguated ID Type / Status
Subject Floréal E375146 entity
Predicate precedes P97 FINISHED
Object Prairial E377020 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: Prairial | Statement: [Floréal, precedes, Prairial]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prairial
Context triple: [Floréal, precedes, Prairial]
  • A. Prairial chosen
    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.
  • B. Floréal
    Floréal is the eighth springtime month of the French Republican Calendar, named to evoke the flowering period of the year.
  • C. Fructidor
    Fructidor is the twelfth and final month of the French Republican Calendar, corresponding roughly to late August and early September and associated with the fruit harvest.
  • D. Vendémiaire
    Vendémiaire is the first month of the French Republican Calendar, corresponding roughly to late September and early October and associated with the grape harvest.
  • E. Pluviôse
    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.
  • 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e7d9328819090e93d55881269a5 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f37383c81909d0efce84508a034 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:12 a.m.