Triple
T21428721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krantiveer |
E528626
|
entity |
| Predicate | awardReceivedBy |
P11
|
FINISHED |
| Object | Dimple Kapadia |
—
|
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: Dimple Kapadia | Statement: [Krantiveer, awardReceivedBy, Dimple Kapadia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dimple Kapadia Context triple: [Krantiveer, awardReceivedBy, Dimple Kapadia]
-
A.
Dimple Kapadia
chosen
Dimple Kapadia is a renowned Indian film actress known for her work in Hindi cinema since the 1970s, acclaimed for both mainstream and critically lauded roles.
-
B.
Asha Parekh
Asha Parekh is a celebrated Indian film actress and former Bollywood star of the 1960s and 1970s, renowned for her versatile performances and significant contributions to Hindi cinema.
-
C.
Shanta Apte
Shanta Apte was a prominent Indian film actress and playback singer of the 1930s and 1940s, known for her powerful performances in Marathi and Hindi cinema.
-
D.
Smita Patil
Smita Patil was a critically acclaimed Indian actress known for her powerful performances in parallel cinema during the 1970s and 1980s.
-
E.
Shobha Kapoor
Shobha Kapoor is an Indian television and film producer and the co-founder of Balaji Telefilms, one of India’s leading entertainment production companies.
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee813db52c8190ac933bc6ec4dbf77 |
completed | April 26, 2026, 9:18 p.m. |
Created at: April 16, 2026, 5:49 p.m.