Triple
T22111585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buniyaad |
E546429
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Sippy Films |
—
|
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: Sippy Films | Statement: [Buniyaad, productionCompany, Sippy Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sippy Films Context triple: [Buniyaad, productionCompany, Sippy Films]
-
A.
Sippy Films
chosen
Sippy Films is an Indian film production and distribution company best known for backing several classic and influential Bollywood movies.
-
B.
See-Saw Films
See-Saw Films is a British-Australian film and television production company known for acclaimed works such as the Academy Award–winning drama "The King’s Speech."
-
C.
Sister Pictures
Sister Pictures is a British television production company known for creating high-profile, critically acclaimed drama series.
-
D.
Milkshake Films
Milkshake Films is a film production company known for producing the movie "Goal II: Living the Dream."
-
E.
Sketch Films
Sketch Films is a television production company best known for its work on the supernatural drama series "Sleepy Hollow."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12949cc7881908898ca7dc130f57f |
completed | April 28, 2026, 9:40 p.m. |
Created at: April 16, 2026, 8:31 p.m.