Triple

T7824994
Position Surface form Disambiguated ID Type / Status
Subject Pha̍k-fa-sṳ E181223 entity
Predicate influencedBy P9 FINISHED
Object Pe̍h-ōe-jī E228708 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: Pe̍h-ōe-jī | Statement: [Pha̍k-fa-sṳ, influencedBy, Pe̍h-ōe-jī]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pe̍h-ōe-jī
Context triple: [Pha̍k-fa-sṳ, influencedBy, Pe̍h-ōe-jī]
  • A. Pe̍h-ōe-jī chosen
    Pe̍h-ōe-jī is a Latin-based orthography developed by Western missionaries for writing Southern Min (Hokkien) and related Chinese dialects.
  • B. Zhuyin
    Zhuyin is a phonetic writing system for transcribing the sounds of Mandarin Chinese, primarily used in Taiwan for teaching pronunciation and literacy.
  • C. Taiwanese Romanization System
    The Taiwanese Romanization System is a standardized Latin-based orthography used to phonetically represent Taiwanese Hokkien.
  • D. 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.
  • 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_69ca8282ccec819083c48efb72d21cf9 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cafa0c1f5c8190b16db20daad159a1 completed March 30, 2026, 10:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb14aefd4881908ffa5825f4ba6eff completed March 31, 2026, 12:26 a.m.
Created at: March 30, 2026, 4:42 p.m.