Triple

T12447954
Position Surface form Disambiguated ID Type / Status
Subject Kota Kinabalu E297450 entity
Predicate hasAirportIATA P2569 FINISHED
Object BKI E398411 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: BKI | Statement: [Kota Kinabalu, hasAirportIATA, BKI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BKI
Context triple: [Kota Kinabalu, hasAirportIATA, BKI]
  • A. BKI chosen
    BKI is the IATA airport code for Kota Kinabalu International Airport, a major air gateway to the Malaysian state of Sabah on the island of Borneo.
  • B. BKB
    BKB is the IATA airport code for Nal Airport, a regional airport serving Bikaner in the Indian state of Rajasthan.
  • C. BKL
    BKL is an alternative name for the Big Circle Line, a major circular metro line in Moscow’s rapid transit system.
  • D. BKL
    BKL is the FAA airport code for Burke Lakefront Airport, a public airport located on the shore of Lake Erie in Cleveland, Ohio.
  • E. BKM
    BKM is the abbreviated name for Germany’s Federal Government Commissioner for Culture and the Media, the authority responsible for national cultural policy and media affairs.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d9e592c81908cf7f3ca170d942c completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f1501448190b0a95d7cd249ca9d completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:56 p.m.