Triple
T7252663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longgu language |
E157641
|
entity |
| Predicate | hasVowelInventoryType |
P22962
|
FINISHED |
| Object | five-vowel system |
—
|
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: five-vowel system | Statement: [Longgu language, hasVowelInventoryType, five-vowel system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVowelInventoryType Context triple: [Longgu language, hasVowelInventoryType, five-vowel system]
-
A.
hasVowelSystem
chosen
Indicates that an entity possesses a particular system or pattern of vowel sounds (a structured set of vowel phonemes or contrasts).
-
B.
hasVowelFeature
Indicates that an entity possesses a specific vowel-related phonological or articulatory feature.
-
C.
hasConsonantInventoryType
Indicates that an entity is characterized by a specific type or classification of consonant inventory in its phonological system.
-
D.
hasVowelNotationSystem
Indicates that a writing or transcription system for a language includes a method for explicitly representing vowel sounds.
-
E.
hasNasalVowels
Indicates that the subject language or phonological system includes vowels that are produced with nasal airflow (nasalized vowels).
- 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea9d41908190bb76c6a5b9d5b1a2 |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:56 p.m.