Triple

T13306118
Position Surface form Disambiguated ID Type / Status
Subject Stewart International Airport E316938 entity
Predicate ICAOCode P419 FINISHED
Object KSWF E316939 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: KSWF | Statement: [Stewart International Airport, ICAOCode, KSWF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KSWF
Context triple: [Stewart International Airport, ICAOCode, KSWF]
  • A. KSWF chosen
    KSWF is the ICAO airport code for Stewart International Airport, a public airport in New York’s Hudson Valley serving both civilian and military aviation.
  • B. KSWI
    KSWI is the ICAO airport code for Sherman Municipal Airport, a public airport serving Sherman, Texas, in the United States.
  • C. KWSWK
    KWSWK is the UN/LOCODE identifier for the Port of Shuwaikh in Kuwait, used in international shipping and logistics.
  • D. KWS
    KWS is the government agency responsible for conserving and managing Kenya’s wildlife and protected areas.
  • E. KWF
    KWF is the acronym for the Komisyon sa Wikang Filipino, the Philippine government agency responsible for developing, preserving, and promoting the Filipino language and other native languages of the Philippines.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a76adc8190ab9abcdb79a21ca8 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716e3617081909eea9989cf5e7b30 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:28 p.m.