Triple
T6505727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ميرامار |
E150000
|
entity |
| Predicate | ترجمت_إلى |
P21151
|
FINISHED |
| Object | اللغة الإنجليزية |
—
|
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 الإنجليزية | Statement: [ميرامار, ترجمت_إلى, اللغة الإنجليزية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ترجمت_إلى Context triple: [ميرامار, ترجمت_إلى, اللغة الإنجليزية]
-
A.
translationTargetLanguage
chosen
Indicates the language into which content is being or has been translated.
-
B.
translationDirection
Indicates the source and target languages involved in a translation, specifying the direction from the original language to the translated language.
-
C.
translationApproximate
Indicates that one entity is an inexact or approximate translation of another, preserving general meaning but not precise wording or full detail.
-
D.
translationOn
Indicates that one entity is a translation of another entity, typically expressing the same content in a different language or linguistic form.
-
E.
translator
Indicates that one entity serves to convert or render content from one language or form into another for a second entity.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f386aa08190bfc8592a92ec6339 |
completed | March 27, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69c68ab714908190aa7c2fbf64078e15 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:43 p.m.