Triple
T22102965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daddy (1989 film) |
E546214
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Dimpy Bahl
Dimpy Bahl is a film editor known for working on Hindi cinema, including editing the 1989 film "Daddy."
|
E1518037
|
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: Dimpy Bahl | Statement: [Daddy (1989 film), editedBy, Dimpy Bahl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dimpy Bahl Context triple: [Daddy (1989 film), editedBy, Dimpy Bahl]
-
A.
Shaan Hathiramani
Shaan Hathiramani is an entrepreneur best known as a co-founder of the mobile video-sharing app Socialcam.
-
B.
Aseem Kishore
Aseem Kishore is a technology writer and blogger known for creating practical guides and tutorials on software, web development, and digital tools.
-
C.
Muktha Srinivasan
Muktha Srinivasan was a prominent Indian film producer and director in Tamil cinema, known for backing influential and critically acclaimed films.
-
D.
Janhavi Nilekani
Janhavi Nilekani is an Indian writer and environmentalist known for her work on water conservation and for being the daughter of Infosys co-founder Nandan Nilekani.
-
E.
Rinke Khanna
Rinke Khanna is an Indian former film actress and the younger daughter of Bollywood stars Rajesh Khanna and Dimple Kapadia.
- 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: Dimpy Bahl Triple: [Daddy (1989 film), editedBy, Dimpy Bahl]
Generated description
Dimpy Bahl is a film editor known for working on Hindi cinema, including editing the 1989 film "Daddy."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dimpy Bahl Target entity description: Dimpy Bahl is a film editor known for working on Hindi cinema, including editing the 1989 film "Daddy."
-
A.
Shaan Hathiramani
Shaan Hathiramani is an entrepreneur best known as a co-founder of the mobile video-sharing app Socialcam.
-
B.
Aseem Kishore
Aseem Kishore is a technology writer and blogger known for creating practical guides and tutorials on software, web development, and digital tools.
-
C.
Muktha Srinivasan
Muktha Srinivasan was a prominent Indian film producer and director in Tamil cinema, known for backing influential and critically acclaimed films.
-
D.
Janhavi Nilekani
Janhavi Nilekani is an Indian writer and environmentalist known for her work on water conservation and for being the daughter of Infosys co-founder Nandan Nilekani.
-
E.
Rinke Khanna
Rinke Khanna is an Indian former film actress and the younger daughter of Bollywood stars Rajesh Khanna and Dimple Kapadia.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129175a7881909549883f23c53dca |
completed | April 28, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a87a70bd881909ba61f007a3fe0d9 |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a895ef5288190a0390f96efd33d44 |
completed | May 18, 2026, 3:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a89c9c35081909c874c659d4a084f |
completed | May 18, 2026, 3:38 a.m. |
Created at: April 16, 2026, 8:30 p.m.