Triple

T2563218
Position Surface form Disambiguated ID Type / Status
Subject Han River (Wuhan) E57289 entity
Predicate flowsThrough P225 FINISHED
Object Hankou 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: Hankou | Statement: [Han River (Wuhan), flowsThrough, Hankou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hankou
Context triple: [Han River (Wuhan), flowsThrough, Hankou]
  • 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. Huangzhou
    Huangzhou is the central urban district and administrative heart of Huanggang in Hubei Province, China.
  • C. 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.
  • D. Xiangyang
    Xiangyang is a historic prefecture-level city in northern Hubei Province, China, known for its strategic location on the Han River and well-preserved ancient city walls.
  • E. Ezhou
    Ezhou is a prefecture-level city in eastern Hubei Province, China, known for its location along the Yangtze River and its growing role as a regional transportation and industrial hub.
  • 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_69ab4a4ef9008190a0e6d4422b9418b7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3374c648190a29b2cc209d66668 completed March 7, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69b203287b48819080791588c7f7f5ab completed March 12, 2026, 12:04 a.m.
Created at: March 6, 2026, 9:48 p.m.