Triple

T6471271
Position Surface form Disambiguated ID Type / Status
Subject Kim E142356 entity
Predicate transliterationSystem P5923 FINISHED
Object McCune–Reischauer E216724 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: McCune–Reischauer | Statement: [Kim, transliterationSystem, McCune–Reischauer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: McCune–Reischauer
Context triple: [Kim, transliterationSystem, McCune–Reischauer]
  • A. McCune–Reischauer chosen
    McCune–Reischauer is a widely used system for romanizing the Korean language, designed to represent Korean pronunciation accurately using the Latin alphabet.
  • B. Hepburn romanization
    Hepburn romanization is a widely used system for transcribing Japanese sounds into the Latin alphabet, designed to be intuitive for English speakers.
  • 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. Taiwanese Romanization System
    The Taiwanese Romanization System is a standardized Latin-based orthography used to phonetically represent Taiwanese Hokkien.
  • E. 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.
  • 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_69c008d3bf4c8190bcf798c5ba9d6fb3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06a2fd4248190a789bf0301e2860a completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6539c93c481909bed35b68ce420d8 completed March 27, 2026, 9:53 a.m.
Created at: March 22, 2026, 4:50 p.m.