Triple

T20709107
Position Surface form Disambiguated ID Type / Status
Subject Wuhan Zall E508983 entity
Predicate represents P129 FINISHED
Object city of Wuhan NE NERFINISHED

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: city of Wuhan | Statement: [Wuhan Zall, represents, city of Wuhan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Wuhan
Context triple: [Wuhan Zall, represents, city of Wuhan]
  • A. central Wuhan
    Central Wuhan is the bustling commercial and cultural heart of Wuhan, known for its dense urban development, major shopping streets, and historic riverfront areas.
  • B. Wuhan chosen
    Wuhan is a major city in central China, known as a key industrial, commercial, and transportation hub located at the confluence of the Yangtze and Han rivers.
  • C. Port of Wuhan
    The Port of Wuhan is a major inland river port on the Yangtze River in central China, serving as a key hub for regional trade and transportation.
  • D. Hongshan District, Wuhan
    Hongshan District is a major urban district in southeastern Wuhan, China, known for its concentration of universities, research institutions, and technology-oriented development.
  • E. Qingshan District, Wuhan
    Qingshan District, Wuhan is an urban district on the Yangtze River in Wuhan, Hubei Province, known for its heavy industry and educational institutions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c40ad88190b81f77695366d328 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1961090819090daf7254f90a176 completed April 21, 2026, 12:15 a.m.
Created at: April 16, 2026, 12:14 p.m.