Triple
T29332939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahar (1951 film) |
E743827
|
entity |
| Predicate | leadActressDebutInHindi |
P172826
|
FINISHED |
| Object | Vyjayanthimala |
—
|
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: Vyjayanthimala | Statement: [Bahar (1951 film), leadActressDebutInHindi, Vyjayanthimala]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActressDebutInHindi Context triple: [Bahar (1951 film), leadActressDebutInHindi, Vyjayanthimala]
-
A.
debutAsLeadActressYear
Indicates the year in which an entity first made her debut as a lead actress.
-
B.
tamilFilmDebut
Indicates the film in which a person first appeared or debuted in the Tamil-language film industry.
-
C.
debutInTeluguCinema
Indicates the event or relationship in which an entity makes its first appearance or acting role in Telugu-language cinema.
-
D.
bengaliFilmDebut
Indicates the film in which a person first appeared or debuted in Bengali cinema.
-
E.
leadActorDebutFilmFor
Indicates that a person’s first film as a lead actor is the specified movie.
- 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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6b0d21dd08190a9883ff71c94c71c |
completed | May 3, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6afeaaef88190aefa97e83f8db906 |
completed | May 3, 2026, 2:16 a.m. |
Created at: April 28, 2026, 1:30 p.m.