Triple
T1745527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabic alphabet |
E38326
|
entity |
| Predicate | vowelRepresentation |
P9875
|
FINISHED |
| Object | optional diacritics |
—
|
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: optional diacritics | Statement: [Arabic alphabet, vowelRepresentation, optional diacritics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vowelRepresentation Context triple: [Arabic alphabet, vowelRepresentation, optional diacritics]
-
A.
hasVowelNotationSystem
chosen
Indicates that a writing or transcription system for a language includes a method for explicitly representing vowel sounds.
-
B.
hasVowelSystem
Indicates that an entity possesses a particular system or pattern of vowel sounds (a structured set of vowel phonemes or contrasts).
-
C.
hasVowelFeature
Indicates that an entity possesses a specific vowel-related phonological or articulatory feature.
-
D.
hasNumberOfVowelLetters
Indicates that an entity is associated with a specific count of vowel letters it contains.
-
E.
vocalizationMethod
Indicates the manner or technique by which an entity produces a sound or vocal expression.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.