Triple

T1768210
Position Surface form Disambiguated ID Type / Status
Subject Huangshi E38812 entity
Predicate capitalOf P204 FINISHED
Object Huangshi City E38812 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: Huangshi City | Statement: [Huangshi, capitalOf, Huangshi City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huangshi City
Context triple: [Huangshi, capitalOf, Huangshi City]
  • A. Huangshi chosen
    Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
  • B. 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.
  • C. Xiaogan
    Xiaogan is a prefecture-level city in central China known for its cultural heritage and proximity to the provincial capital, Wuhan, within Hubei Province.
  • D. Pingdingshan
    Pingdingshan is a prefecture-level industrial city in central China known for its significant coal mining and energy production.
  • E. Suizhou
    Suizhou is a county-level city in northern Hubei Province, China, known for its historical sites and role as a regional transport and economic 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa648bb44c81909245fb7ee23cb132 completed March 6, 2026, 5:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5cb503bc8190823a843bb58d85e1 completed March 9, 2026, 11:50 p.m.
Created at: March 4, 2026, 7:31 p.m.