Triple

T29754656
Position Surface form Disambiguated ID Type / Status
Subject Meʼphaa languages E752996 entity
Predicate haveNasalizationContrast P7439 FINISHED
Object true 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: true | Statement: [Meʼphaa languages, haveNasalizationContrast, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: haveNasalizationContrast
Context triple: [Meʼphaa languages, haveNasalizationContrast, true]
  • A. hasNasalConsonants
    Indicates that the subject language or word includes one or more nasal consonant sounds in its phonological inventory or pronunciation.
  • B. hasNasalVowels chosen
    Indicates that the subject language or phonological system includes vowels that are produced with nasal airflow (nasalized vowels).
  • 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. hasPalatalizationContrast
    Indicates that a language distinguishes meaning between sounds based on whether or not they are palatalized, treating palatalization as a contrastive phonological feature.
  • E. hasPhonationContrast
    Indicates that a language or system distinguishes sounds based on different phonation types (e.g., voiced vs. voiceless) as a meaningful contrast.
  • 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_69f0d62c84cc8190846f80ae04fdf8ec completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f673c9d2a88190965075607fc73061 completed May 2, 2026, 9:59 p.m.
PD Predicate disambiguation batch_69f66ac1a4fc81909740d2e52fbe6970 completed May 2, 2026, 9:21 p.m.
Created at: April 28, 2026, 7:56 p.m.