Triple

T8663735
Position Surface form Disambiguated ID Type / Status
Subject Huangshi Port E205611 entity
Predicate locatedIn P40 FINISHED
Object Huangshi 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 | Statement: [Huangshi Port, locatedIn, Huangshi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huangshi
Context triple: [Huangshi Port, locatedIn, Huangshi]
  • 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. Pingdingshan
    Pingdingshan is a prefecture-level industrial city in central China known for its significant coal mining and energy production.
  • C. 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.
  • 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. 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_69ca83516ae88190aefe034b3bc589e3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc489f7edc8190bde1b4dc09249207 completed March 31, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6ed1e0548190b02d43c5d7e65e08 completed April 3, 2026, 7:40 a.m.
Created at: March 30, 2026, 6:30 p.m.