Triple
T11792398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pankaj Kapur |
E280419
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Sanah Kapur
Sanah Kapur is an Indian actress known for her supporting role in the film "Shaandaar" and for being part of the Kapur film family.
|
E951376
|
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: Sanah Kapur | Statement: [Pankaj Kapur, child, Sanah Kapur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanah Kapur Context triple: [Pankaj Kapur, child, Sanah Kapur]
-
A.
Rhea Kapoor
Rhea Kapoor is an Indian film producer and fashion stylist known for producing Bollywood films like "Aisha" and "Veere Di Wedding" and for her work in celebrity styling.
-
B.
Kajal Aggarwal
Kajal Aggarwal is a popular Indian actress best known for her leading roles in Telugu and Tamil cinema, as well as appearances in Hindi films.
-
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.
Divya Katdare
Divya Katdare is a central character on the television series "Royal Pains," known as a skilled and poised physician assistant who works closely with concierge doctor Hank Lawson in the Hamptons.
-
E.
Neha Kapur
Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
- 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: Sanah Kapur Triple: [Pankaj Kapur, child, Sanah Kapur]
Generated description
Sanah Kapur is an Indian actress known for her supporting role in the film "Shaandaar" and for being part of the Kapur film family.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sanah Kapur Target entity description: Sanah Kapur is an Indian actress known for her supporting role in the film "Shaandaar" and for being part of the Kapur film family.
-
A.
Rhea Kapoor
Rhea Kapoor is an Indian film producer and fashion stylist known for producing Bollywood films like "Aisha" and "Veere Di Wedding" and for her work in celebrity styling.
-
B.
Kajal Aggarwal
Kajal Aggarwal is a popular Indian actress best known for her leading roles in Telugu and Tamil cinema, as well as appearances in Hindi films.
-
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.
Divya Katdare
Divya Katdare is a central character on the television series "Royal Pains," known as a skilled and poised physician assistant who works closely with concierge doctor Hank Lawson in the Hamptons.
-
E.
Neha Kapur
Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a588d2c881909783c2d678c2a474 |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f280fe1b2881908c32b920cdaf04df |
completed | April 29, 2026, 10:06 p.m. |
| NEDg | Description generation | batch_69f28a8e64ac8190ba7637fd00e024bd |
completed | April 29, 2026, 10:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f28d4e341c8190abc8febc3b26a617 |
completed | April 29, 2026, 10:59 p.m. |
Created at: April 8, 2026, 9:42 p.m.