Triple
T5385463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masnavi |
E120190
|
entity |
| Predicate | hasTranslations |
P45244
|
FINISHED |
| Object | translated into many languages |
—
|
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: translated into many languages | Statement: [Masnavi, hasTranslations, translated into many languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTranslations Context triple: [Masnavi, hasTranslations, translated into many languages]
-
A.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasWorkTranslatedInto
chosen
Indicates that a work has been translated into a specified language or target work.
-
C.
languageOfTranslations
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
-
D.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
E.
hasTranslationBooths
Indicates that one entity provides or contains translation booths for use, typically for interpreting spoken communication.
- 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_69bd46354c648190a38b26f107010a96 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd86f5a7388190aa4ba2052afca74e |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd8463a9c88190bd760378f3026180 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:03 p.m.