Triple

T1055271
Position Surface form Disambiguated ID Type / Status
Subject Tosk E22786 entity
Predicate hasVowelSystem P22962 FINISHED
Object seven-vowel system in standard form 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: seven-vowel system in standard form | Statement: [Tosk, hasVowelSystem, seven-vowel system in standard form]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasVowelSystem
Context triple: [Tosk, hasVowelSystem, seven-vowel system in standard form]
  • A. hasVowelNotationSystem
    Indicates that a writing or transcription system for a language includes a method for explicitly representing vowel sounds.
  • B. hasVowelFeature
    Indicates that an entity possesses a specific vowel-related phonological or articulatory feature.
  • C. 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.
  • D. hasNasalVowels
    Indicates that the subject language or phonological system includes vowels that are produced with nasal airflow (nasalized vowels).
  • E. hasVowelLengthContrast
    Indicates that a language distinguishes word meanings based on differences in the length (duration) of vowel sounds.
  • F. None of above. chosen

Provenance (4 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8d79268819080f3f3f497e91c58 completed March 1, 2026, 10:08 p.m.
PD Predicate disambiguation batch_69a4b731e25c8190b5ea8466648c2c9a completed March 1, 2026, 10:01 p.m.
PDg Predicate description generation batch_69a4b7da38888190a118ef20ce4ae9aa completed March 1, 2026, 10:04 p.m.
Created at: March 1, 2026, 7:42 p.m.