Triple

T4143796
Position Surface form Disambiguated ID Type / Status
Subject Zeng E89334 entity
Predicate romanizationSystem P6517 FINISHED
Object Hanyu Pinyin E175084 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: Hanyu Pinyin | Statement: [Zeng, romanizationSystem, Hanyu Pinyin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanyu Pinyin
Context triple: [Zeng, romanizationSystem, Hanyu Pinyin]
  • A. Hanyu Pinyin chosen
    Hanyu Pinyin is the official romanization system for Standard Mandarin Chinese, using the Latin alphabet to represent Chinese pronunciation.
  • B. Tongyong Pinyin
    Tongyong Pinyin is a romanization system for Mandarin Chinese that was once officially used in Taiwan as an alternative to Hanyu Pinyin.
  • C. Zhuyin
    Zhuyin is a phonetic writing system for transcribing the sounds of Mandarin Chinese, primarily used in Taiwan for teaching pronunciation and literacy.
  • D. Pe̍h-ōe-jī
    Pe̍h-ōe-jī is a Latin-based orthography developed by Western missionaries for writing Southern Min (Hokkien) and related Chinese dialects.
  • E. Taiwanese Romanization System
    The Taiwanese Romanization System is a standardized Latin-based orthography used to phonetically represent Taiwanese Hokkien.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af025d2984819095f299327cc399d5 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f2e787881908a9721877b0fd4ae completed March 14, 2026, 3:30 p.m.
Created at: March 9, 2026, 3:43 p.m.