Triple

T22570243
Position Surface form Disambiguated ID Type / Status
Subject Chinese characters E558057 entity
Predicate alsoKnownAs P39 FINISHED
Object Chữ Hán 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: Chữ Hán | Statement: [Chinese characters, alsoKnownAs, Chữ Hán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chữ Hán
Context triple: [Chinese characters, alsoKnownAs, Chữ Hán]
  • A. Chinese characters chosen
    Chinese characters are logographic symbols used for writing the Chinese language and several other East Asian languages, each typically representing a morpheme or meaningful unit.
  • B. Chữ Nôm
    Chữ Nôm is a historic logographic writing system that adapted and expanded Chinese characters to represent the Vietnamese language before the widespread adoption of the Latin-based quốc ngữ script.
  • C. Qin script
    Qin script is an ancient standardized form of Chinese writing used during the Qin dynasty, particularly known for its role in unifying written characters across China.
  • D. Zhuyin
    Zhuyin is a phonetic writing system for transcribing the sounds of Mandarin Chinese, primarily used in Taiwan for teaching pronunciation and literacy.
  • E. Grammata Serica
    Grammata Serica is a seminal scholarly work that systematically reconstructs and analyzes the phonology and characters of ancient Chinese, laying the foundation for modern historical Chinese linguistics.
  • 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15fad35448190b51a3dd639ca8568 completed April 29, 2026, 1:32 a.m.
Created at: April 16, 2026, 8:52 p.m.