Triple
T20417611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apna Sapna Money Money |
E500752
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Anant Chaturvedi
Anant Chaturvedi is an Indian cinematographer known for his work on Bollywood films, including the comedy "Apna Sapna Money Money."
|
E1443521
|
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: Anant Chaturvedi | Statement: [Apna Sapna Money Money, cinematographyBy, Anant Chaturvedi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anant Chaturvedi Context triple: [Apna Sapna Money Money, cinematographyBy, Anant Chaturvedi]
-
A.
Ashok Mishra
Ashok Mishra is an Indian screenwriter known for his work on films such as "Welcome to Sajjanpur."
-
B.
Veerendra Saxena
Veerendra Saxena is an Indian actor known for his character roles in Hindi films and television.
-
C.
Raghuveer Chaudhari
Raghuveer Chaudhari is an acclaimed Indian Gujarati writer and scholar renowned for his influential novels, poetry, and literary criticism.
-
D.
Vinod Dikshit
Vinod Dikshit was an Indian civil servant and the husband of longtime Delhi Chief Minister Sheila Dikshit.
-
E.
Ajit Bhawan
Ajit Bhawan is a historic royal residence in Jodhpur that has been converted into a luxury heritage hotel associated with the Jodhpur royal family.
- 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: Anant Chaturvedi Triple: [Apna Sapna Money Money, cinematographyBy, Anant Chaturvedi]
Generated description
Anant Chaturvedi is an Indian cinematographer known for his work on Bollywood films, including the comedy "Apna Sapna Money Money."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anant Chaturvedi Target entity description: Anant Chaturvedi is an Indian cinematographer known for his work on Bollywood films, including the comedy "Apna Sapna Money Money."
-
A.
Ashok Mishra
Ashok Mishra is an Indian screenwriter known for his work on films such as "Welcome to Sajjanpur."
-
B.
Veerendra Saxena
Veerendra Saxena is an Indian actor known for his character roles in Hindi films and television.
-
C.
Raghuveer Chaudhari
Raghuveer Chaudhari is an acclaimed Indian Gujarati writer and scholar renowned for his influential novels, poetry, and literary criticism.
-
D.
Vinod Dikshit
Vinod Dikshit was an Indian civil servant and the husband of longtime Delhi Chief Minister Sheila Dikshit.
-
E.
Ajit Bhawan
Ajit Bhawan is a historic royal residence in Jodhpur that has been converted into a luxury heritage hotel associated with the Jodhpur royal family.
- 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_6a08cd474d488190936ea776ee43f50c |
completed | May 16, 2026, 8:02 p.m. |
| NEDg | Description generation | batch_6a08d174278481909db394da2a7ff969 |
completed | May 16, 2026, 8:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08d28e02fc8190ab694673156ab0c0 |
completed | May 16, 2026, 8:24 p.m. |
Created at: April 16, 2026, 11:30 a.m.