Triple
T20359308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smallfoot (Spanish dub) |
E496733
|
entity |
| Predicate | hasDubbedDialogue |
P83674
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Smallfoot (Spanish dub), hasDubbedDialogue, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDubbedDialogue Context triple: [Smallfoot (Spanish dub), hasDubbedDialogue, yes]
-
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.
hasMultilingualDialogue
Indicates that an interaction or work contains dialogue expressed in more than one language.
-
D.
hasSubtitles
Indicates that one media item provides subtitle text or tracks that accompany another media item or its audio content.
-
E.
hasDialogueIn
Indicates that an entity participates in or contains spoken or written dialogue within a specified context, such as a scene, work, or medium.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678573fc481908bf257e6ed41d750 |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:25 a.m.