Triple
T8379824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirza Ghalib (TV series) |
E197660
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Neena Gupta
Neena Gupta is an acclaimed Indian film, television, and theatre actress and director known for her versatile performances across parallel and mainstream cinema.
|
E735413
|
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: Neena Gupta | Statement: [Mirza Ghalib (TV series), starring, Neena Gupta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neena Gupta Context triple: [Mirza Ghalib (TV series), starring, Neena Gupta]
-
A.
Neha Kapur
Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
-
B.
Anu Khosla
Anu Khosla is one of the children of Indian-American billionaire venture capitalist and Sun Microsystems co-founder Vinod Khosla.
-
C.
Juhi Chawla
Juhi Chawla is a popular Indian actress and film producer known for her work in Hindi cinema since the late 1980s.
-
D.
Anuradha Paudwal
Anuradha Paudwal is a renowned Indian playback and devotional singer celebrated for her extensive work in Hindi cinema and bhajans since the 1970s.
-
E.
Seema Kapoor
Seema Kapoor is an Indian television and film actress and director, known for her work in Hindi entertainment and her marriage to the late actor Om Puri.
- 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: Neena Gupta Triple: [Mirza Ghalib (TV series), starring, Neena Gupta]
Generated description
Neena Gupta is an acclaimed Indian film, television, and theatre actress and director known for her versatile performances across parallel and mainstream cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Neena Gupta Target entity description: Neena Gupta is an acclaimed Indian film, television, and theatre actress and director known for her versatile performances across parallel and mainstream cinema.
-
A.
Neha Kapur
Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
-
B.
Anu Khosla
Anu Khosla is one of the children of Indian-American billionaire venture capitalist and Sun Microsystems co-founder Vinod Khosla.
-
C.
Juhi Chawla
Juhi Chawla is a popular Indian actress and film producer known for her work in Hindi cinema since the late 1980s.
-
D.
Anuradha Paudwal
Anuradha Paudwal is a renowned Indian playback and devotional singer celebrated for her extensive work in Hindi cinema and bhajans since the 1970s.
-
E.
Seema Kapoor
Seema Kapoor is an Indian television and film actress and director, known for her work in Hindi entertainment and her marriage to the late actor Om Puri.
- 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_69ca82f64c188190af4e1608036b865d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80c3dc1881908081c6a2829deb5a |
completed | March 31, 2026, 8:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d14baf88190bc260efda7d0fc0d |
completed | April 2, 2026, 7:39 a.m. |
| NEDg | Description generation | batch_69ce20e2506081908d53ec4ff3861551 |
completed | April 2, 2026, 7:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce2267cdd88190a8fdb44fd65a694a |
completed | April 2, 2026, 8:01 a.m. |
Created at: March 30, 2026, 6:02 p.m.