Triple
T5805928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Turkic script |
E128743
|
entity |
| Predicate | writingDirectionDetail |
P2264
|
FINISHED |
| Object | horizontally right-to-left |
—
|
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: horizontally right-to-left | Statement: [Old Turkic script, writingDirectionDetail, horizontally right-to-left]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingDirectionDetail Context triple: [Old Turkic script, writingDirectionDetail, horizontally right-to-left]
-
A.
hasWritingDirection
chosen
Indicates the direction in which writing or text is read or written for a given script, language, or text system.
-
B.
translationDirection
Indicates the source and target languages involved in a translation, specifying the direction from the original language to the translated language.
-
C.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
-
D.
writingSystemFeatures
Indicates the specific structural or functional characteristics that define how a particular writing system represents language.
-
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_69c00846a0d881909e46841f8e156b64 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b15d8108190b434da42631c4e0c |
completed | March 22, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69c021d477008190946113f9859eeb90 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:52 p.m.