Triple
T9169150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JOD |
E220039
|
entity |
| Predicate | languageScriptOnNotes |
P16462
|
FINISHED |
| Object | Arabic |
—
|
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 | Statement: [JOD, languageScriptOnNotes, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageScriptOnNotes Context triple: [JOD, languageScriptOnNotes, Arabic]
-
A.
primaryLanguageOnNotes
Indicates the main language used in the written notes associated with an entity or resource.
-
B.
scriptOfNotes
Indicates that one entity is the written or notated script (e.g., musical, theatrical, or instructional notes) that documents, guides, or underlies another entity.
-
C.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
-
D.
associatedLanguageScript
chosen
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
E.
hasLanguageUsageNote
Indicates that there is an associated note describing specific usage guidance, nuances, or restrictions for a language element.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaae0f3148190b111b22902cdb86c |
completed | April 1, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69cc660761d88190ab6134b43b376964 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:22 p.m.