Triple

T9135086
Position Surface form Disambiguated ID Type / Status
Subject Air Canada E219179 entity
Predicate hasIcaoCode P419 FINISHED
Object ACA E219179 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: ACA | Statement: [Air Canada, hasIcaoCode, ACA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ACA
Context triple: [Air Canada, hasIcaoCode, ACA]
  • A. ACA
    ACA is a professional scientific organization that promotes the study and application of crystallography and structural science, primarily in North America.
  • B. ACA
    ACA is the common abbreviation for the Affordable Care Act, a major U.S. health care reform law enacted in 2010 to expand insurance coverage and consumer protections.
  • C. ACA chosen
    ACA is the three-letter ICAO airline designator used to identify Air Canada in international aviation operations and communications.
  • D. ACA
    ACA is the acronym commonly used for the Army Comrades Association, an Irish nationalist organization active in the early 20th century.
  • E. ACA
    ACA is a subset of the Atacama Large Millimeter/submillimeter Array (ALMA) consisting of closely spaced radio telescopes designed to improve imaging of extended astronomical objects.
  • 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_69ca83e012288190a5771058adbaabd2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8de0dec8190978c80b9ec8bf25c completed April 1, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d047efc5e48190bc8c4a7e865faef9 completed April 3, 2026, 11:06 p.m.
Created at: March 30, 2026, 7:18 p.m.