Triple

T9640439
Position Surface form Disambiguated ID Type / Status
Subject Huangzhou District E233049 entity
Predicate prefectureLevelCity P56216 FINISHED
Object Huanggang E41595 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: Huanggang | Statement: [Huangzhou District, prefectureLevelCity, Huanggang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huanggang
Context triple: [Huangzhou District, prefectureLevelCity, Huanggang]
  • A. Huanggang chosen
    Huanggang is a significant prefecture-level city in eastern Hubei, China, known for its long history, agricultural production, and proximity to the Yangtze River.
  • B. Qianjiang
    Qianjiang is a city in China known for its regional industry and cultural exchanges, including international town twinning partnerships.
  • C. Sichun
    Sichun is a Chinese given name notably borne by actress Ma Sichun, known for her roles in contemporary Chinese cinema and television.
  • D. Fuyang
    Fuyang is a major prefecture-level city in northwestern Anhui Province, China, known as a regional transportation and agricultural hub.
  • E. Huangchu
    Huangchu was the first era name of the Cao Wei state during China’s Three Kingdoms period, marking the early reign of Emperor Cao Pi.
  • 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_69ca848a5a908190aad251f4137b0c3a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b552a1c81909a1fab347110eeb1 completed April 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18248ffe4819095d4ea20951eca01 completed April 4, 2026, 9:27 p.m.
Created at: March 30, 2026, 8:12 p.m.