Triple
T25753806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kajal Aggarwal |
E648535
|
entity |
| Predicate | filmDebutLanguage |
P159231
|
FINISHED |
| Object | Hindi |
—
|
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: Hindi | Statement: [Kajal Aggarwal, filmDebutLanguage, Hindi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmDebutLanguage Context triple: [Kajal Aggarwal, filmDebutLanguage, Hindi]
-
A.
filmDebutIn
Indicates the first film in which a person appeared or participated, marking their debut in cinema.
-
B.
filmDebut
Indicates the first film in which an entity (typically a person) appeared or participated, marking their initial entry into film work.
-
C.
soundFilmDebutDate
Indicates the date on which an entity first appeared in a sound film.
-
D.
filmIndustryDebut
Indicates the event or point in time when an entity first appears or participates in the film industry, such as through a first film role, production, or related professional activity.
-
E.
featureFilmDebut
Indicates that a work marks an entity’s first appearance or role in a feature-length film.
- 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_69e7ab314d788190b3abe19e114080e1 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fd80a93081909fa651bc57d26884 |
completed | May 2, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69f4938262ac8190b41f922d0407d272 |
completed | May 1, 2026, 11:50 a.m. |
| PDg | Predicate description generation | batch_69f497b8abb88190bb672cf6907c4b8d |
completed | May 1, 2026, 12:08 p.m. |
Created at: April 22, 2026, 4:37 a.m.