Triple

T22229908
Position Surface form Disambiguated ID Type / Status
Subject Geling Yan E549438 entity
Predicate name P16 FINISHED
Object Geling Yan 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: Geling Yan | Statement: [Geling Yan, name, Geling Yan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geling Yan
Context triple: [Geling Yan, name, Geling Yan]
  • A. Geling Yan chosen
    Geling Yan is a Chinese-American novelist and screenwriter known for her emotionally powerful works that often explore the human impact of war, political upheaval, and social change in modern Chinese history.
  • B. Zhilin Yang
    Zhilin Yang is a computer scientist and AI researcher known for his work on large-scale language models and as a lead author of the XLNet architecture.
  • C. Shuicheng Yan
    Shuicheng Yan is a computer vision and machine learning researcher known for his influential work in deep learning architectures and visual recognition.
  • D. Yiping Gan
    Yiping Gan is a regional variety of Gan Chinese, a Sinitic language spoken primarily in Jiangxi province and surrounding areas.
  • E. Yiliang Peng
    Yiliang Peng, better known as Doublelift, is a retired professional League of Legends AD carry from North America renowned for his multiple LCS titles and status as one of the region’s greatest players.
  • 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12bf173308190a3d21bfc59b39728 completed April 28, 2026, 9:51 p.m.
Created at: April 16, 2026, 8:37 p.m.