Triple
T15801301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | دلالة الحائرين |
E383103
|
entity |
| Predicate | لغة_أصلية |
P5459
|
FINISHED |
| Object | اللغة العربية |
—
|
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: اللغة العربية | Statement: [دلالة الحائرين, لغة_أصلية, اللغة العربية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: لغة_أصلية Context triple: [دلالة الحائرين, لغة_أصلية, اللغة العربية]
-
A.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
B.
languageOfOriginalDescription
Indicates that something is expressed or documented in its initial or source language version.
-
C.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
D.
originalLanguagePhrase
Indicates that one phrase is the original-language version from which another phrase (typically a translation or adaptation) is derived.
-
E.
originalTextLanguage
chosen
Indicates the language in which a text was originally written or created before any translation or adaptation.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b522a2988190b2a2bde2da31b21e |
completed | April 16, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:48 a.m.