Triple

T2422588
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen Airlines E53450 entity
Predicate focusCity P164 FINISHED
Object Qingdao E130067 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: Qingdao | Statement: [Shenzhen Airlines, focusCity, Qingdao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Qingdao
Context triple: [Shenzhen Airlines, focusCity, Qingdao]
  • A. Qingdao chosen
    Qingdao is a major coastal city in eastern China known for its port, beaches, German colonial architecture, and Tsingtao Brewery.
  • B. Weihai
    Weihai is a coastal city in eastern China known for its strategic location on the Yellow Sea, maritime history, and role as a major port and tourist destination.
  • C. Yantai
    Yantai is a coastal city in Shandong Province, China, known for its port, wine production, and scenic beaches along the Bohai Sea.
  • D. Weifang
    Weifang is a prefecture-level city in eastern China known for its kite-making tradition and annual international kite festival.
  • E. Rizhao
    Rizhao is a coastal city in eastern China known for its sunny climate, beaches, and port on the Yellow Sea.
  • 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_69ab495c44d48190b7235b23719bc3f6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc972934481909e05bd6f31162f9d completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17864e9881909b32b70d55028016 completed March 9, 2026, 6:55 p.m.
Created at: March 6, 2026, 9:42 p.m.