Triple

T35248914
Position Surface form Disambiguated ID Type / Status
Subject Akure dialect of Yoruba E1018041 entity
Predicate usesNasalVowels P7439 FINISHED
Object yes 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: yes | Statement: [Akure dialect of Yoruba, usesNasalVowels, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesNasalVowels
Context triple: [Akure dialect of Yoruba, usesNasalVowels, yes]
  • A. hasNasalVowels chosen
    Indicates that the subject language or phonological system includes vowels that are produced with nasal airflow (nasalized vowels).
  • B. hasNasalConsonants
    Indicates that the subject language or word includes one or more nasal consonant sounds in its phonological inventory or pronunciation.
  • C. hasNasalHarmony
    Indicates that a phonological process causes nasality in one segment to spread to or be shared with other segments within a word or domain.
  • D. hasVoicelessNasals
    Indicates that the subject possesses or exhibits voiceless nasal sounds (nasal consonants produced without vocal fold vibration).
  • E. 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.
  • 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_69f76de407d081909dfc3c419817ae93 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78f63c8788190b253a18de5ca1312 completed May 3, 2026, 6:09 p.m.
PD Predicate disambiguation batch_69f78e2d71248190b850c2802ec170c0 completed May 3, 2026, 6:04 p.m.
Created at: May 3, 2026, 4:02 p.m.