Triple

T14305553
Position Surface form Disambiguated ID Type / Status
Subject Jinhua E354684 entity
Predicate hasNotableCity P2813 FINISHED
Object Yongkang E1098573 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: Yongkang | Statement: [Jinhua, hasNotableCity, Yongkang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yongkang
Context triple: [Jinhua, hasNotableCity, Yongkang]
  • A. Yongkang chosen
    Yongkang is a county-level city in Zhejiang Province, China, known as a major manufacturing hub, especially for hardware and metal products.
  • B. Yongkang District
    Yongkang District is a major suburban and industrial district of Tainan City in southern Taiwan, known for its manufacturing base and growing residential communities.
  • C. Yueqing
    Yueqing is a county-level coastal city administered by Wenzhou in Zhejiang Province, China, known for its manufacturing industry and economic vitality.
  • D. Jinhua
    Jinhua is a prefecture-level city in eastern China known for its historical sites, transportation hub role, and famous local ham products.
  • E. Jiande
    Jiande was an era name used during the Northern Qi dynasty in imperial China to designate a specific reign period.
  • 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85afabe48190926d6098047f4bcf completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda907abf88190b86ce65390d9ca40 completed May 8, 2026, 9:12 a.m.
Created at: April 10, 2026, 1:12 a.m.