Triple
T1614127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sama–Bajaw languages subgroup |
E34674
|
entity |
| Predicate | historicallyUsedScript |
P16462
|
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: [Sama–Bajaw languages subgroup, historicallyUsedScript, Arabic script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicallyUsedScript Context triple: [Sama–Bajaw languages subgroup, historicallyUsedScript, Arabic script]
-
A.
historicalScript
Indicates that an entity is or was written in, or otherwise associated with, a particular historical writing system or script.
-
B.
formerScript
Indicates that an entity previously served as the script or writing system for another entity, but is no longer used in that role.
-
C.
associatedLanguageScript
chosen
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
D.
writingSystemUsedSince
Indicates that a particular writing system has been in use starting from a specified point in time or period.
-
E.
historicallyUsedFor
Indicates that something served a particular function or purpose at some point in the past, even if it may no longer be used that way now.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fef600c819080fe75c42c8e6dac |
completed | March 5, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69a907c52a548190b648a31ea306dd5b |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.