Triple

T2562643
Position Surface form Disambiguated ID Type / Status
Subject Mandarin phonology E57275 entity
Predicate usesRomanization P23170 FINISHED
Object Pinyin E175084 NE FINISHED

How this triple was built (3 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: Pinyin | Statement: [Mandarin phonology, usesRomanization, Pinyin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pinyin
Context triple: [Mandarin phonology, usesRomanization, 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.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesRomanization
Context triple: [Mandarin phonology, usesRomanization, Pinyin]
  • A. hasRomanizationOf
    Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
  • B. hasRomanizationStandard chosen
    Indicates that an entity’s romanized form follows a specified romanization standard or system.
  • C. hasRomanizationContrast
    Indicates that there is a meaningful difference between two or more romanized representations of the same original form.
  • D. usesRomanNumerals
    Indicates that something represents numbers or sequences using the Roman numeral system rather than standard Arabic digits.
  • E. usesKatakanaFor
    Indicates that one entity is written or represented using katakana script in relation to another entity.
  • F. None of above.

Provenance (4 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_69ab4a4ef9008190a0e6d4422b9418b7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd35c6ee88190b6eaa1841d3e99a4 completed March 7, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98ab023481908ab51febe79b963c completed March 10, 2026, 4:06 a.m.
PD Predicate disambiguation batch_69abd0caeb488190b0dd8e48d0f2777d completed March 7, 2026, 7:16 a.m.
Created at: March 6, 2026, 9:48 p.m.