Triple
T33202401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaaro Sun Lo Zara |
E849935
|
entity |
| Predicate | featuredInFilmIndustry |
P101250
|
FINISHED |
| Object | Bollywood |
—
|
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: Bollywood | Statement: [Yaaro Sun Lo Zara, featuredInFilmIndustry, Bollywood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredInFilmIndustry Context triple: [Yaaro Sun Lo Zara, featuredInFilmIndustry, Bollywood]
-
A.
featuredInFilmBy
Indicates that an entity is prominently included or showcased within a film that is created, directed, or produced by a specified person or organization.
-
B.
originatesInFilmIndustry
chosen
Indicates that something has its source, development, or primary origin within the film industry.
-
C.
sangForFilmIndustry
Indicates that a person performed singing specifically for use in the film industry, such as in movies or film soundtracks.
-
D.
visitedInFilm
Indicates that a location or place is depicted as being visited by a character within the events of a film.
-
E.
occupationInFilm
Indicates that an entity has a specific occupation or role within the context of a particular film.
- 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a017590e01c8190b985bb50cc6cd605 |
completed | May 11, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_6a0175406b348190a5809b5f3497d46f |
completed | May 11, 2026, 6:20 a.m. |
Created at: May 1, 2026, 1:30 a.m.