Triple
T16351333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakh languages |
E397067
|
entity |
| Predicate | historicalWritingSystemUsed |
P38424
|
FINISHED |
| Object | Arabic script |
—
|
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: Arabic script | Statement: [Nakh languages, historicalWritingSystemUsed, Arabic script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalWritingSystemUsed Context triple: [Nakh languages, historicalWritingSystemUsed, Arabic script]
-
A.
writingSystemHistorically
chosen
Indicates that one writing system was historically used for, associated with, or served as a predecessor to another writing system.
-
B.
writingSystemDevelopedFrom
Indicates that one writing system originated, evolved, or was derived from another earlier writing system.
-
C.
writingSystemUsedSince
Indicates that a particular writing system has been in use starting from a specified point in time or period.
-
D.
introducedWritingSystem
Indicates that an entity is responsible for originating or bringing a particular writing system into use.
-
E.
writingSystemUsedIn
Indicates that a particular writing system is employed for written communication within a given language, region, or context.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2facb37d0819093fe45446f1e79c1 |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.