Triple
T27974711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | جلال آلاحمد |
E706454
|
entity |
| Predicate | زبان ترجمه |
P71670
|
FINISHED |
| Object | از زبان فرانسه به فارسی |
—
|
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: از زبان فرانسه به فارسی | Statement: [جلال آلاحمد, زبان ترجمه, از زبان فرانسه به فارسی]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: زبان ترجمه Context triple: [جلال آلاحمد, زبان ترجمه, از زبان فرانسه به فارسی]
-
A.
languageTranslatedFrom
chosen
Indicates that a language is the source/original language from which content has been translated into another language.
-
B.
translator
Indicates that one entity serves to convert or render content from one language or form into another for a second entity.
-
C.
textTranslation
Indicates a relationship where one text is rendered into another language or form while preserving its original meaning.
-
D.
translationTargetLanguage
Indicates the language into which content is being or has been translated.
-
E.
translationActivity
Indicates that an entity is engaged in the process of translating content from one language or form into another.
- 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_69ef96b7f330819090f315318ba6977e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63fd79e4c8190af9263b679e5ff07 |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6a8474819091b8c6fe98e3862d |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 7:40 p.m.