Triple

T7593100
Position Surface form Disambiguated ID Type / Status
Subject Hepburn E179787 entity
Predicate alternativeLongVowelNotation P57346 FINISHED
Object doubling vowels in some practical contexts LITERAL 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: doubling vowels in some practical contexts | Statement: [Hepburn, alternativeLongVowelNotation, doubling vowels in some practical contexts]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: alternativeLongVowelNotation
Context triple: [Hepburn, alternativeLongVowelNotation, doubling vowels in some practical contexts]
  • A. hasVowelNotationSystem
    Indicates that a writing or transcription system for a language includes a method for explicitly representing vowel sounds.
  • B. hasAlternativeVocalization
    Indicates that an entity has another valid way it can be vocalized or pronounced, distinct from its primary or standard vocalization.
  • C. hasAlternativeNotation chosen
    Indicates that an entity can be represented or written in a different, equivalent form or notation.
  • D. hasVowelHarmony
    Indicates that the phonological vowels in a word or morpheme conform to a systematic harmony pattern (e.g., all front or all back vowels) according to the language’s vowel harmony rules.
  • E. hasVowelLengthContrast
    Indicates that a language distinguishes word meanings based on differences in the length (duration) of vowel sounds.
  • F. None of above.

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_69c69f3487ec8190bf7acdf2dd91e6d6 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9b92c348190b547f0aacfb8d6be completed March 27, 2026, 9:42 p.m.
PD Predicate disambiguation batch_69c6f4e2e42c8190afc802c4796c9cc2 completed March 27, 2026, 9:21 p.m.
Created at: March 27, 2026, 3:53 p.m.