Triple
T5699063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kazakh Arabic alphabet |
E125612
|
entity |
| Predicate | includesAdditionalLettersFor |
P9187
|
FINISHED |
| Object | Kazakh vowels |
—
|
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: Kazakh vowels | Statement: [Kazakh Arabic alphabet, includesAdditionalLettersFor, Kazakh vowels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesAdditionalLettersFor Context triple: [Kazakh Arabic alphabet, includesAdditionalLettersFor, Kazakh vowels]
-
A.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
B.
hasAdditionalLetters
chosen
Indicates that one entity contains extra or more letters than another entity, beyond a specified base set or reference.
-
C.
hasLetter
Indicates that one entity contains, includes, or is associated with a specific letter or character.
-
D.
hasBasicLetters
Indicates that an entity contains or is composed of fundamental alphabetic characters, without additional symbols or diacritics.
-
E.
hasLetterBy
Indicates that an entity possesses or is associated with a letter authored or sent by another entity.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0240ecef48190bdef10b38ecb2bd0 |
completed | March 22, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.