Triple

T17727435
Position Surface form Disambiguated ID Type / Status
Subject Blériot-SPAD S.33 E442498 entity
Predicate operator P179 FINISHED
Object CIDNA 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: CIDNA | Statement: [Blériot-SPAD S.33, operator, CIDNA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CIDNA
Context triple: [Blériot-SPAD S.33, operator, CIDNA]
  • A. CIDNA chosen
    CIDNA was a pioneering French airline of the early 20th century that operated international routes in Europe before being absorbed into Air France.
  • B. CID
    The CID was a high-level British government body responsible for coordinating defense and military policy across the Empire in the early 20th century.
  • C. CID
    CID is the abbreviated name for the Criminal Investigations Division of the Metropolitan Police Department, responsible for conducting in-depth investigations into serious crimes.
  • D. CID
    CID is a common abbreviation for Seattle’s Chinatown–International District, a historic neighborhood known for its Asian American communities, businesses, and cultural institutions.
  • E. CID
    CID is the three-letter IATA airport code for The Eastern Iowa Airport serving the Cedar Rapids area in Iowa, United States.
  • 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_69d8b9ec79688190b86bdcef85a7b3aa completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e478e3cb708190b47456ad2008a65e completed April 19, 2026, 6:40 a.m.
Created at: April 10, 2026, 10:07 a.m.