Triple
T10547197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saba |
E248850
|
entity |
| Predicate | usedScriptDirection |
P3658
|
FINISHED |
| Object | 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: right-to-left | Statement: [Saba, usedScriptDirection, right-to-left]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedScriptDirection Context triple: [Saba, usedScriptDirection, right-to-left]
-
A.
scriptDirection
chosen
Indicates the direction in which a writing system or script is read or written (e.g., left-to-right, right-to-left, top-to-bottom).
-
B.
hasWritingDirection
Indicates the direction in which writing or text is read or written for a given script, language, or text system.
-
C.
scriptDirectionOrigin
Indicates the original writing direction (such as left-to-right or right-to-left) from which a script’s layout or orientation is derived.
-
D.
translationDirection
Indicates the source and target languages involved in a translation, specifying the direction from the original language to the translated language.
-
E.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d52710869c81909b6db1a190825bad |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:33 p.m.