Triple

T1909903
Position Surface form Disambiguated ID Type / Status
Subject Snake Hill E38083 entity
Predicate partOf P40 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: [Snake Hill, partOf, Wuchang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wuchang
Context triple: [Snake Hill, partOf, 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. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • 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. 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.
  • 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_69a8862a26088190aae5243695aeefc0 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1b7095c8190ad7e472aada30d3d completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf046d388190a0224f76a4e13e08 completed March 9, 2026, 12:37 p.m.
Created at: March 4, 2026, 7:35 p.m.