Triple

T3847803
Position Surface form Disambiguated ID Type / Status
Subject ZBAD E85214 entity
Predicate hubFor P423 FINISHED
Object XiamenAir E30720 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: XiamenAir | Statement: [ZBAD, hubFor, XiamenAir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: XiamenAir
Context triple: [ZBAD, hubFor, XiamenAir]
  • A. XiamenAir chosen
    XiamenAir is a Chinese airline based in Xiamen that operates domestic and international flights across Asia and beyond.
  • B. Hainan Airlines
    Hainan Airlines is a major Chinese airline headquartered in Haikou, known for its extensive domestic and international route network and high service quality ratings.
  • C. Kunming Airlines
    Kunming Airlines is a Chinese domestic carrier based in Kunming, Yunnan Province, operating passenger and cargo services to destinations across China.
  • D. Shanghai Airlines
    Shanghai Airlines is a Chinese airline based in Shanghai that operates domestic and international passenger flights as a subsidiary of China Eastern Airlines.
  • E. Shenzhen Airlines
    Shenzhen Airlines is a major Chinese carrier based in Shenzhen that operates extensive domestic and regional flights across Asia.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeebcc8a0481909c35161336bdfbf9 completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5122eb2708190b1aa9da233481015 completed March 14, 2026, 7:45 a.m.
Created at: March 9, 2026, 3:18 p.m.