Triple

T317277
Position Surface form Disambiguated ID Type / Status
Subject Osaka International Airport E7734 entity
Predicate focusCityFor P164 FINISHED
Object Japan Airlines E12451 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: Japan Airlines | Statement: [Osaka International Airport, focusCityFor, Japan Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japan Airlines
Context triple: [Osaka International Airport, focusCityFor, Japan Airlines]
  • A. Japan Airlines chosen
    Japan Airlines is the flag carrier of Japan, operating an extensive network of domestic and international flights across Asia, Europe, and the Americas.
  • B. All Nippon Airways
    All Nippon Airways is a major Japanese airline and Star Alliance member known for its extensive domestic and international route network and high service standards.
  • C. Korean Air
    Korean Air is South Korea’s largest airline and flag carrier, operating extensive international and domestic passenger and cargo services worldwide.
  • D. Cathay Pacific
    Cathay Pacific is a major Hong Kong-based international airline known for its extensive global network and premium full-service operations.
  • E. China Airlines
    China Airlines is the flag carrier of Taiwan, operating an extensive network of international passenger and cargo flights across Asia, Europe, North America, and Oceania.
  • 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_69a2e7e7af7881908890039d6be4e9b8 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ea65ca7081908093e6aaaf2d34f7 completed Feb. 28, 2026, 1:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3cafef7d48190b00f577488298605 completed March 1, 2026, 5:13 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.