Triple

T15459516
Position Surface form Disambiguated ID Type / Status
Subject Dong Biwu E371859 entity
Predicate placeOfBirth P1 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: [Dong Biwu, placeOfBirth, Huanggang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huanggang
Context triple: [Dong Biwu, placeOfBirth, 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f1623f0819086f6fc2bfd536609 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21b9817c819082e5c571b08bafb5 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:32 a.m.