Triple
T5699069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kazakh Arabic alphabet |
E125612
|
entity |
| Predicate | usageStatus |
P65653
|
FINISHED |
| Object | historical |
—
|
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: historical | Statement: [Kazakh Arabic alphabet, usageStatus, historical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usageStatus Context triple: [Kazakh Arabic alphabet, usageStatus, historical]
-
A.
availabilityStatus
Indicates the current state of whether something is obtainable, usable, or accessible at a given time.
-
B.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
C.
platformUsage
Indicates how an entity uses, engages with, or relies on a particular platform for its activities or services.
-
D.
serviceAvailability
Indicates whether a particular service is accessible and operational for use during a given time or under specified conditions.
-
E.
automationStatus
Indicates whether a process, task, or system is being performed automatically or requires manual intervention.
- 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_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. |
| PDg | Predicate description generation | batch_69c023dfec6881909ee6189b874b4348 |
completed | March 22, 2026, 5:16 p.m. |
Created at: March 22, 2026, 3:45 p.m.