Triple

T6764817
Position Surface form Disambiguated ID Type / Status
Subject Wuhan Metro Line 29 E154690 entity
Predicate serves P98 FINISHED
Object city of Wuhan E1680 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: city of Wuhan | Statement: [Wuhan Metro Line 29, serves, city of Wuhan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Wuhan
Context triple: [Wuhan Metro Line 29, serves, city of Wuhan]
  • A. 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.
  • B. 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.
  • C. Huangshi
    Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
  • D. Yichang
    Yichang is a key city in western Hubei, China, best known as the gateway to the Three Gorges region and the nearby Three Gorges Dam on the Yangtze River.
  • E. Jiang’an District, Wuhan
    Jiang’an District is a central urban district of Wuhan, China, known for its historic riverfront along the Yangtze and Han rivers and its legacy as part of the former foreign concession area in Hankou.
  • 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_69c688109c1c8190added9a221292af0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d217bbfc81908c9e55efaf7f8594 completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712b9e7f081909d9fcc219ac525b8 completed March 27, 2026, 11:28 p.m.
Created at: March 27, 2026, 2:12 p.m.