Triple
T26909383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naser |
E677345
|
entity |
| Predicate | typicalScriptInOriginLanguage |
P199100
|
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: [Naser, typicalScriptInOriginLanguage, Arabic script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalScriptInOriginLanguage Context triple: [Naser, typicalScriptInOriginLanguage, Arabic script]
-
A.
scriptOriginLanguage
Indicates the original language in which a script was written or first created.
-
B.
scriptOfOrigin
Indicates that one entity is the original writing system or script from which another script is derived or historically originates.
-
C.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
-
D.
scriptNameLanguage
Indicates that a script’s name is expressed or written in a particular language.
-
E.
hasScriptOfOfficialLanguage
Indicates that one entity is the writing system (script) used for the official language of another entity.
- F. None of above. chosen
Provenance (4 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_69eee9bcef1c8190be88586bb902bb9b |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69ff1f3f94fc819095955299f50ab4ce |
completed | May 9, 2026, 11:49 a.m. |
| PD | Predicate disambiguation | batch_69ff1ea47748819082f63d9b9d9c3e65 |
completed | May 9, 2026, 11:46 a.m. |
| PDg | Predicate description generation | batch_69ff1f3ee3588190a857d1504c93be8b |
completed | May 9, 2026, 11:49 a.m. |
Created at: April 27, 2026, 6:01 a.m.