Triple
T5738124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pyar Kiya To Darna Kya |
E126547
|
entity |
| Predicate | filmicFunction |
P65544
|
FINISHED |
| Object | expresses heroine’s open defiance of emperor |
—
|
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: expresses heroine’s open defiance of emperor | Statement: [Pyar Kiya To Darna Kya, filmicFunction, expresses heroine’s open defiance of emperor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmicFunction Context triple: [Pyar Kiya To Darna Kya, filmicFunction, expresses heroine’s open defiance of emperor]
-
A.
film
Indicates that an entity is a movie or cinematic work, or that a relationship involves such a movie.
-
B.
filmWithinFilm
Indicates that one film is depicted, referenced, or shown as existing within the narrative of another film.
-
C.
filmDirection
Indicates that one entity is the director responsible for overseeing the creative and practical aspects of producing the film represented by the other entity.
-
D.
filmType
Indicates the specific category or genre that a film belongs to.
-
E.
filmSetting
Indicates the place, time, or environment in which the events of a film are set or take place.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255c8c308190821f968ec41c5078 |
completed | March 22, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69c021c8195481909419808b002628aa |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c022a50c048190aff24c63e7039dd6 |
completed | March 22, 2026, 5:11 p.m. |
Created at: March 22, 2026, 3:47 p.m.