Triple

T23125651
Position Surface form Disambiguated ID Type / Status
Subject CRRC Tangshan E577020 entity
Predicate province P604 FINISHED
Object Hebei NE NERFINISHED

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: Hebei | Statement: [CRRC Tangshan, province, Hebei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hebei
Context triple: [CRRC Tangshan, province, Hebei]
  • A. Hebei chosen
    Hebei is a northern Chinese province surrounding Beijing and Tianjin, historically significant as a major political, military, and industrial region.
  • B. Suiyuan Province
    Suiyuan Province was a former province of the Republic of China and early People's Republic of China located in what is now Inner Mongolia, known for its strategic position in northern China.
  • C. Jiaozhi Province
    Jiaozhi Province was a Ming dynasty colonial administrative region established in northern Vietnam during the early 15th century.
  • D. Liaoning
    Liaoning is a northeastern coastal province of China known for its heavy industry, port cities, and role as a gateway to the Korean Peninsula.
  • E. Hubei Province
    Hubei Province is a landlocked region in central China known for its capital city Wuhan, major role in industry and transportation, and significant historical and cultural heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245f7b0e481909c473ff4e6a54e2c completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18e53ac288190b27fe8064fb576c2 completed April 29, 2026, 4:51 a.m.
Created at: April 17, 2026, 3:59 p.m.