Triple
T29491527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billa (2007 film) |
E748091
|
entity |
| Predicate | remakeOfLanguageFilm |
P36901
|
FINISHED |
| Object | Tamil-language film |
—
|
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: Tamil-language film | Statement: [Billa (2007 film), remakeOfLanguageFilm, Tamil-language film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: remakeOfLanguageFilm Context triple: [Billa (2007 film), remakeOfLanguageFilm, Tamil-language film]
-
A.
remakeOfFilmStarring
Indicates that one film is a remake of another film in which a specified actor or set of actors starred.
-
B.
remadeFor
Indicates that one work has been recreated or adapted specifically for another context, audience, or medium.
-
C.
remakeFeature
Indicates that one work is a new version or adaptation created by redoing or updating the features of an earlier work.
-
D.
remakeLanguage
chosen
Indicates that one entity creates a new version or adaptation of another entity in a different language.
-
E.
liveActionRemakeOf
Indicates that one work is a live-action remake adaptation of another, originally non-live-action, work.
- 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_69f0bd448c6881908aa6b475cefd5ddc |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66c0b47188190b65788708bde20d1 |
completed | May 2, 2026, 9:26 p.m. |
| PD | Predicate disambiguation | batch_69f6659b62fc8190b21555d0ba54db2d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 4:14 p.m.