Triple

T329421
Position Surface form Disambiguated ID Type / Status
Subject Kansai International Airport E6591 entity
Predicate JapaneseName P744 FINISHED
Object 関西国際空港 E6591 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: 関西国際空港 | Statement: [Kansai International Airport, JapaneseName, 関西国際空港]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 関西国際空港
Context triple: [Kansai International Airport, JapaneseName, 関西国際空港]
  • A. Kansai International Airport chosen
    Kansai International Airport is a major international airport in Japan built on an artificial island in Osaka Bay, serving as a key gateway to the Kansai region.
  • B. Osaka International Airport
    Osaka International Airport is a major Japanese airport serving the Osaka metropolitan area, primarily handling domestic flights and known locally as Itami Airport.
  • C. Kobe Airport
    Kobe Airport is a regional airport located on an artificial island off the coast of Kobe, Japan, primarily serving domestic flights.
  • D. Haneda Airport
    Haneda Airport is one of Tokyo’s primary international airports and one of Japan’s busiest air travel hubs.
  • E. Narita International Airport
    Narita International Airport is a major international gateway to Japan and one of the primary airports serving the Greater Tokyo area.
  • 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_69a2e7933d6c8190bb2592ad13286ef2 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eaad37b0819085beda2a491da9a8 completed Feb. 28, 2026, 1:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3d24410608190be8da7fa425f1971 completed March 1, 2026, 5:44 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.