Triple

T14517753
Position Surface form Disambiguated ID Type / Status
Subject Akasa Air E340567 entity
Predicate callsign P1565 FINISHED
Object AKASA AIR E340567 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: AKASA AIR | Statement: [Akasa Air, callsign, AKASA AIR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AKASA AIR
Context triple: [Akasa Air, callsign, AKASA AIR]
  • A. Akasa Air chosen
    Akasa Air is an Indian low-cost airline that began operations in 2022, offering domestic flights with a focus on affordable fares and a modern fleet.
  • B. Japan Air System
    Japan Air System was a major Japanese domestic airline that operated from 1971 until its 2004 merger into Japan Airlines, known for its colorful liveries and extensive regional network.
  • C. Wasaya Airways
    Wasaya Airways is a Canadian regional airline based in northern Ontario that primarily provides passenger and cargo services to remote First Nations and northern communities.
  • D. Amakusa Airlines
    Amakusa Airlines is a small Japanese regional airline based in Kumamoto Prefecture that operates domestic routes connecting remote islands and regional cities.
  • E. Japan Airlines
    Japan Airlines is the flag carrier of Japan, operating an extensive network of domestic and international flights across Asia, Europe, and the Americas.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de9a6f50208190b687b505f5cd1aa2 completed April 14, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8aaeaf40819087fa0db989813e02 completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:22 a.m.