Triple

T4575470
Position Surface form Disambiguated ID Type / Status
Subject American Standards Association E123131 entity
Predicate alsoKnownAs P39 FINISHED
Object ASA E123131 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: ASA | Statement: [American Standards Association, alsoKnownAs, ASA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ASA
Context triple: [American Standards Association, alsoKnownAs, ASA]
  • A. 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.
  • B. ASA
    ASA is an abbreviation commonly used to refer to the Assistant Secretary of the Army, a senior civilian official in the United States Department of the Army responsible for high-level policy and oversight.
  • C. ASA
    ASA is the ICAO airline designator used to identify Alaska Airlines in international aviation operations and communications.
  • D. ASA
    ASA is the commonly used abbreviation for the Academy of Sciences of Albania, the country’s leading scientific research and advisory institution.
  • E. ASA chosen
    ASA is a standards organization that played a key role in formalizing technical specifications such as the ASCII character encoding.
  • 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_69bd46466c7081909d07f36be2d08804 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd58dfe3508190b21836079e951a3c completed March 20, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69bde08756548190bb8433854c3efe01 completed March 21, 2026, 12:04 a.m.
Created at: March 20, 2026, 1:10 p.m.