Triple
T7937497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Hat End User License Agreement |
E184319
|
entity |
| Predicate | mayBeTranslatedInto |
P45244
|
FINISHED |
| Object | other 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: other languages | Statement: [Red Hat End User License Agreement, mayBeTranslatedInto, other languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeTranslatedInto Context triple: [Red Hat End User License Agreement, mayBeTranslatedInto, other languages]
-
A.
hasWorkTranslatedInto
chosen
Indicates that a work has been translated into a specified language or target work.
-
B.
hasTranslated
Indicates that one entity has rendered the content of another entity from one language into a different language.
-
C.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
D.
laterTranslatedAs
Indicates that something was translated at a later time into a different language, form, or version under a specified title or expression.
-
E.
languageTranslatedFrom
Indicates that a language is the source/original language from which content has been translated into another language.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aef2394819086eea1f6ab117aed |
completed | March 31, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69cae9335f288190ba96781fd6576a2b |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:08 p.m.