Triple

T11674888
Position Surface form Disambiguated ID Type / Status
Subject Shuangshi Jie E277465 entity
Predicate relatedPlace P3158 FINISHED
Object Wuchang 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: Wuchang | Statement: [Shuangshi Jie, relatedPlace, Wuchang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wuchang
Context triple: [Shuangshi Jie, relatedPlace, Wuchang]
  • 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. Huangshi
    Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
  • C. Huangzhou
    Huangzhou is the central urban district and administrative heart of Huanggang in Hubei Province, China.
  • D. Zhongdu
    Zhongdu was the historical capital city of the Jurchen-led Jin dynasty in northern China, located in what is now part of modern Beijing.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a44504c48190b519765a83ff9c5e completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef82f515408190b21f1c7b207a2f0d completed April 27, 2026, 3:38 p.m.
Created at: April 8, 2026, 9:40 p.m.