Triple

T16934998
Position Surface form Disambiguated ID Type / Status
Subject Hokkien E410805 entity
Predicate writingSystem P454 FINISHED
Object Taiwanese Romanization System E228709 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: Taiwanese Romanization System | Statement: [Hokkien, writingSystem, Taiwanese Romanization System]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taiwanese Romanization System
Context triple: [Hokkien, writingSystem, Taiwanese Romanization System]
  • A. Taiwanese Romanization System chosen
    The Taiwanese Romanization System is a standardized Latin-based orthography used to phonetically represent Taiwanese Hokkien.
  • B. Hakka Romanization System
    The Hakka Romanization System is a standardized method of writing the Hakka Chinese language using the Latin alphabet to represent its sounds and tones.
  • C. Pe̍h-ōe-jī
    Pe̍h-ōe-jī is a Latin-based orthography developed by Western missionaries for writing Southern Min (Hokkien) and related Chinese dialects.
  • 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. McCune–Reischauer
    McCune–Reischauer is a widely used system for romanizing the Korean language, designed to represent Korean pronunciation accurately using the Latin alphabet.
  • 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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cf2899608190a6bacdce9d4ceb84 completed April 18, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfe2d4f48190b965b6c0a3cc0125 completed May 10, 2026, 6:35 p.m.
Created at: April 10, 2026, 5:30 a.m.