Triple

T2483515
Position Surface form Disambiguated ID Type / Status
Subject middle reaches of the Yangtze River E55872 entity
Predicate hasMajorCityOnBanks P14915 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: [middle reaches of the Yangtze River, hasMajorCityOnBanks, Huangshi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huangshi
Context triple: [middle reaches of the Yangtze River, hasMajorCityOnBanks, 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd82f2020819086bbd321a750ce43 completed March 7, 2026, 7:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69b1f84f2c5c819084c82bfbd6a3b6f0 completed March 11, 2026, 11:18 p.m.
Created at: March 6, 2026, 9:45 p.m.