Triple

T5534072
Position Surface form Disambiguated ID Type / Status
Subject Roman calendar E145116 entity
Predicate includedMonth P6433 FINISHED
Object Februarius E145118 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: Februarius | Statement: [Roman calendar, includedMonth, Februarius]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Februarius
Context triple: [Roman calendar, includedMonth, Februarius]
  • A. February chosen
    February is the second month of the year in both the Julian and Gregorian calendars, typically having 28 days and 29 in leap years.
  • B. 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.
  • C. 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.
  • D. Januária
    Januária was a Brazilian princess of the Empire of Brazil, daughter of Emperor Pedro I and heir presumptive before the birth of her younger brother Pedro II.
  • E. 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.
  • 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_69c008f9955881909bfa8348b56b4739 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c021d76e4081908570dc34217c66fe completed March 22, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04ce1bce4819095559af19cf072f8 completed March 22, 2026, 8:11 p.m.
Created at: March 22, 2026, 3:34 p.m.