Triple
T22082610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vahcuengh |
E545688
|
entity |
| Predicate | hasPhonemicOrthography |
P75920
|
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: [Vahcuengh, hasPhonemicOrthography, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhonemicOrthography Context triple: [Vahcuengh, hasPhonemicOrthography, yes]
-
A.
hasPhonemicPrinciple
chosen
Indicates that one entity employs or is based on a phonemic principle in relation to another entity (such as a writing system reflecting distinct phonemes of a language).
-
B.
hasPhonemicVowels
Indicates that a language or linguistic system distinguishes vowel sounds as separate phonemes that can change word meaning.
-
C.
hasPhonologicalStandard
Indicates that one entity serves as the accepted or prescribed phonological norm or standard for the pronunciation system of another entity.
-
D.
hasPhoneme
Indicates that a linguistic unit (such as a word or morpheme) contains or includes a particular phoneme as part of its sound structure.
-
E.
usesPhoneticSystem
Indicates that one entity employs or is based on a particular phonetic system for representing or encoding 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b706288190945c0c37e5ff2756 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e71b20ec50819096ac196c798f8e3c |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:28 p.m.