Triple

T22310284
Position Surface form Disambiguated ID Type / Status
Subject Baishan E551492 entity
Predicate border P224 FINISHED
Object Tonghua 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: Tonghua | Statement: [Baishan, border, Tonghua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tonghua
Context triple: [Baishan, border, Tonghua]
  • A. Tonghua chosen
    Tonghua is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, pharmaceutical industry, and role as a regional transportation hub.
  • B. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • C. Yifang
    Yifang is a given name of Chinese origin used for both males and females.
  • D. Taohuayuan
    Taohuayuan is a famous scenic area and cultural site in Changde, Hunan, inspired by the classic Chinese utopian tale "Peach Blossom Spring."
  • E. Xinzhu
    Xinzhu is a city that serves as a sister city to Bielefeld, Germany, and is likely a regional urban center with cultural and economic significance.
  • 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_69e11e46c0188190800181a4233f28fe completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1574d53148190a1ec07f849e1ae9d completed April 29, 2026, 12:56 a.m.
Created at: April 16, 2026, 8:42 p.m.