Triple
T2007981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flying Down to Rio |
E43627
|
entity |
| Predicate | languageSubtitles |
P11498
|
FINISHED |
| Object | none originally |
—
|
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: none originally | Statement: [Flying Down to Rio, languageSubtitles, none originally]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageSubtitles Context triple: [Flying Down to Rio, languageSubtitles, none originally]
-
A.
hasIntertitlesLanguage
Indicates that the intertitles of a film or audiovisual work are presented in a specified language.
-
B.
languageOfSignage
Indicates the language used on signs or written displays associated with an entity.
-
C.
languageOfReleases
chosen
Indicates the language in which the releases associated with an entity are produced or published.
-
D.
languageBranch
Indicates that one language belongs to, or is classified under, a broader linguistic branch or subgroup.
-
E.
languagePair
Indicates a relationship that associates two specific languages as a paired combination, typically for translation, comparison, or mapping between them.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb89aca908190b8b659af65afdf6f |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb79e63c08190982c8b44a557266f |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.