Triple
T25235833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oo Antava Oo Oo Antava |
E632333
|
entity |
| Predicate | basedInFilmLanguage |
P162088
|
FINISHED |
| Object | Telugu cinema |
—
|
NE NERFINISHED |
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: Telugu cinema | Statement: [Oo Antava Oo Oo Antava, basedInFilmLanguage, Telugu cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedInFilmLanguage Context triple: [Oo Antava Oo Oo Antava, basedInFilmLanguage, Telugu cinema]
-
A.
filmedInLanguage
Indicates that a film or video work was originally recorded using a particular spoken or signed language.
-
B.
primaryFilmingLanguage
Indicates the main language in which a film or audiovisual work was originally filmed or recorded.
-
C.
areSpokenIn
Indicates that a particular language is used as a spoken means of communication within a specified region, community, or context.
-
D.
originalLanguageOfFilmOrTVShow
Indicates the language in which a film or TV show was originally produced and released.
-
E.
languageSpokenOnScreen
Indicates that a particular language is used in spoken dialogue or audible communication within an on-screen work (such as a film, show, or video).
- 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_69e75a8ec5f88190b9eba06ae42b413a |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f622abdfac8190988421c946411d7e |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f621fbfc2c8190bfa802d7dc0f6aa4 |
completed | May 2, 2026, 4:10 p.m. |
Created at: April 21, 2026, 1:07 p.m.