Triple

T5434220
Position Surface form Disambiguated ID Type / Status
Subject Journey to a War E121567 entity
Predicate setting P1957 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: [Journey to a War, setting, Hankou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hankou
Context triple: [Journey to a War, setting, 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_69bd463c65f0819082ee6483ab4b466a completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd91af68308190810c64e76c83fa46 completed March 20, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3accb6748190989257c3b991a760 completed March 22, 2026, 12:41 a.m.
Created at: March 20, 2026, 2:06 p.m.