Triple

T13145025
Position Surface form Disambiguated ID Type / Status
Subject Kimbe E312313 entity
Predicate airportServes P4363 FINISHED
Object Kimbe Airport E1026143 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: Kimbe Airport | Statement: [Kimbe, airportServes, Kimbe Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimbe Airport
Context triple: [Kimbe, airportServes, Kimbe Airport]
  • A. Kimbe Airport chosen
    Kimbe Airport is a regional airport serving the town of Kimbe and the surrounding West New Britain Province in Papua New Guinea.
  • B. Sibu Airport
    Sibu Airport is a regional airport serving the town of Sibu in Sarawak, Malaysia, handling domestic flights and acting as an important air transport hub for central Sarawak.
  • C. Kalemie Airport
    Kalemie Airport is a public airport serving the town of Kalemie in the Tanganyika Province of the Democratic Republic of the Congo, providing regional air transport connections.
  • D. Umroi Airport
    Umroi Airport is a domestic airport serving the city of Shillong and the surrounding region in the Indian state of Meghalaya.
  • E. Butaritari Airport
    Butaritari Airport is a small public airfield serving the island of Butaritari in Kiribati, providing vital domestic air connections for the local population.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bcf6d0c819081d078f33e4bdedc completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff0c88dc8190bcb83482d6df39b5 completed May 3, 2026, 7:53 a.m.
Created at: April 9, 2026, 9:10 p.m.