Triple
T20417403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jhankaar Beats |
E500748
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Rangita Pritish Nandy
Rangita Pritish Nandy is an Indian film and web-series producer known for her work in contemporary Hindi cinema and digital content.
|
E1441271
|
NE FINISHED |
How this triple was built (4 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: Rangita Pritish Nandy | Statement: [Jhankaar Beats, producer, Rangita Pritish Nandy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rangita Pritish Nandy Context triple: [Jhankaar Beats, producer, Rangita Pritish Nandy]
-
A.
Sutapa Sikdar
Sutapa Sikdar is an Indian dialogue and screenplay writer best known as the wife of acclaimed actor Irrfan Khan.
-
B.
Sutapa Dasgupta
Sutapa Dasgupta is known as the wife of acclaimed Indian poet and National Award–winning filmmaker Buddhadeb Dasgupta.
-
C.
Sutapa Basu
Sutapa Basu is an Indian author and poet known for her historical fiction and contemporary novels.
-
D.
Supriya Dasgupta
Supriya Dasgupta is the daughter of acclaimed Indian filmmaker and actress Aparna Sen.
-
E.
Anuradha Banerjee
Anuradha Banerjee is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Banerjee.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rangita Pritish Nandy Triple: [Jhankaar Beats, producer, Rangita Pritish Nandy]
Generated description
Rangita Pritish Nandy is an Indian film and web-series producer known for her work in contemporary Hindi cinema and digital content.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rangita Pritish Nandy Target entity description: Rangita Pritish Nandy is an Indian film and web-series producer known for her work in contemporary Hindi cinema and digital content.
-
A.
Sutapa Sikdar
Sutapa Sikdar is an Indian dialogue and screenplay writer best known as the wife of acclaimed actor Irrfan Khan.
-
B.
Sutapa Dasgupta
Sutapa Dasgupta is known as the wife of acclaimed Indian poet and National Award–winning filmmaker Buddhadeb Dasgupta.
-
C.
Sutapa Basu
Sutapa Basu is an Indian author and poet known for her historical fiction and contemporary novels.
-
D.
Supriya Dasgupta
Supriya Dasgupta is the daughter of acclaimed Indian filmmaker and actress Aparna Sen.
-
E.
Anuradha Banerjee
Anuradha Banerjee is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Banerjee.
- F. None of above. chosen
Provenance (5 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a44ecf48190ba5a3872af500dc8 |
completed | April 20, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08bafeede88190be35cac9cce47e21 |
completed | May 16, 2026, 6:44 p.m. |
| NEDg | Description generation | batch_6a08bbc5d9dc8190a6c58039a27ba9ae |
completed | May 16, 2026, 6:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08bcbfc45881909af82e14f84ecd23 |
completed | May 16, 2026, 6:51 p.m. |
Created at: April 16, 2026, 11:30 a.m.