Triple
T20351315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akaler Sandhane |
E496016
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Smita Patil |
—
|
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: Smita Patil | Statement: [Akaler Sandhane, stars, Smita Patil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smita Patil Context triple: [Akaler Sandhane, stars, Smita Patil]
-
A.
Smita Patil
chosen
Smita Patil was a critically acclaimed Indian actress known for her powerful performances in parallel cinema during the 1970s and 1980s.
-
B.
Vyjayanthimala
Vyjayanthimala is a legendary Indian film actress and Bharatanatyam dancer, celebrated as one of the foremost stars of Hindi cinema’s golden age.
-
C.
Sharmila Basu
Sharmila Basu is a relatively obscure individual about whom no widely known public or biographical information is readily available.
-
D.
Dimple Kapadia
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.
-
E.
Sharmila Tagore
Sharmila Tagore is an acclaimed Indian actress known for her influential work in both Bengali art cinema and mainstream Hindi films since the 1960s.
- 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_69e0b4a3320881909495ae8bc30bc2dc |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6784f8ff48190a070888786f6a989 |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:24 a.m.