Triple
T24546291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marimar |
E607235
|
entity |
| Predicate | hasDubbedVersionsIn |
P83674
|
FINISHED |
| Object | multiple countries |
—
|
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: multiple countries | Statement: [Marimar, hasDubbedVersionsIn, multiple countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDubbedVersionsIn Context triple: [Marimar, hasDubbedVersionsIn, multiple countries]
-
A.
dubbedFor
Indicates that one media work has been voice-dubbed to create a version suitable for another language, region, or audience.
-
B.
languageDubbedIn
chosen
Indicates that the content’s audio has been dubbed into the specified language.
-
C.
hasBilingualVersions
Indicates that something exists in two different language versions or forms.
-
D.
adaptedInLanguage
Indicates that a work or content has been modified or translated so it can be presented or understood in a specified language.
-
E.
hasKoreanVersion
Indicates that something has a corresponding version or counterpart that is in the Korean 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_69e2c4c9bf94819082d05da6f5c29907 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8c9ab9c81909ff56f707e3fd27b |
completed | April 30, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.