Triple
T15801337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | دلالة الحائرين |
E383103
|
entity |
| Predicate | ترجم_إلى |
P21151
|
FINISHED |
| Object | اللغة العبرية |
—
|
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 العبرية | Statement: [دلالة الحائرين, ترجم_إلى, اللغة العبرية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ترجم_إلى Context triple: [دلالة الحائرين, ترجم_إلى, اللغة العبرية]
-
A.
textTranslation
Indicates a relationship where one text is rendered into another language or form while preserving its original meaning.
-
B.
translator
Indicates that one entity serves to convert or render content from one language or form into another for a second entity.
-
C.
translationActivity
Indicates that an entity is engaged in the process of translating content from one language or form into another.
-
D.
translatedIn
Indicates that a work, text, or content has been rendered from its original language into another specified language or linguistic form.
-
E.
translationTargetLanguage
chosen
Indicates the language into which content is being or has been translated.
- 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.