Triple

T22589507
Position Surface form Disambiguated ID Type / Status
Subject Alaska Horizon E564902 entity
Predicate ICAOCodeUsed P419 FINISHED
Object ASA 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: ASA | Statement: [Alaska Horizon, ICAOCodeUsed, ASA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ASA
Context triple: [Alaska Horizon, ICAOCodeUsed, ASA]
  • A. ASA
    ASA is the commonly used abbreviation for the Academy of Sciences of Albania, the country’s leading scientific research and advisory institution.
  • B. ASA
    ASA is the leading professional organization in the United States dedicated to advancing the practice and profession of statistics.
  • C. ASA chosen
    ASA is the ICAO airline designator used to identify Alaska Airlines in international aviation operations and communications.
  • D. ASA
    ASA is a standards organization that played a key role in formalizing technical specifications such as the ASCII character encoding.
  • E. ASA
    ASA is the acronym for Aeropuertos y Servicios Auxiliares, the Mexican government agency responsible for operating and managing numerous airports and providing auxiliary aviation services in Mexico.
  • 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_69e245836014819091b91ed3074742a3 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1615f63788190acf776b313f0794a completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 2:48 p.m.