Triple
T33403997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winx Club (Nickelodeon dub) |
E855387
|
entity |
| Predicate | hasTypeOfLocalization |
P198765
|
FINISHED |
| Object | script adaptation |
—
|
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: script adaptation | Statement: [Winx Club (Nickelodeon dub), hasTypeOfLocalization, script adaptation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfLocalization Context triple: [Winx Club (Nickelodeon dub), hasTypeOfLocalization, script adaptation]
-
A.
isLocalizable
Indicates that something can be adapted or translated to different languages or locales without losing its intended function or meaning.
-
B.
hasLanguageType
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
C.
hasTypeOfLocalities
Indicates that an entity is associated with, or classified by, specific types or categories of localities (e.g., urban, rural, suburban).
-
D.
localizationBy
Indicates a relationship where one entity determines, specifies, or constrains the spatial or contextual location of another entity.
-
E.
languageOfLocalization
Indicates the language into which something (such as software, content, or an interface) has been localized for use or display.
- F. None of above. chosen
Provenance (4 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_69f3496e3f1c8190bcecfa82aa9d17ff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff0491409c8190be40f633a58da0b1 |
completed | May 9, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69ff040bb5cc81909534c7eee85d5e90 |
completed | May 9, 2026, 9:53 a.m. |
| PDg | Predicate description generation | batch_69ff04901ab081908b68563836fcdc99 |
completed | May 9, 2026, 9:55 a.m. |
Created at: May 1, 2026, 1:36 a.m.