Triple
T22433243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lootera |
E554548
|
entity |
| Predicate | cinematographer |
P1953
|
FINISHED |
| Object |
Mahendra J. Shetty
Mahendra J. Shetty is an Indian cinematographer known for his visually rich and atmospheric work in Hindi cinema.
|
E1536427
|
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: Mahendra J. Shetty | Statement: [Lootera, cinematographer, Mahendra J. Shetty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahendra J. Shetty Context triple: [Lootera, cinematographer, Mahendra J. Shetty]
-
A.
Arun Shridhar Vaidya
Arun Shridhar Vaidya was an Indian Army general who served as Chief of Army Staff and played a central role in major counterinsurgency operations in the 1980s.
-
B.
Ranjan Raghu Shetty
Ranjan Raghu Shetty is a prominent film director known for his influential work in Tulu-language cinema.
-
C.
Ravi D. Mehta
Ravi D. Mehta is a film producer known for his work on projects such as the 2017 movie "Unforgettable."
-
D.
Jayant Jathar
Jayant Jathar is a film editor best known for his work on the acclaimed Marathi musical drama "Katyar Kaljat Ghusali."
-
E.
Mangubhai C. Patel
Mangubhai C. Patel is an Indian politician and member of the Bharatiya Janata Party who has served in various legislative and leadership roles, including as a state governor.
- 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: Mahendra J. Shetty Triple: [Lootera, cinematographer, Mahendra J. Shetty]
Generated description
Mahendra J. Shetty is an Indian cinematographer known for his visually rich and atmospheric work in Hindi cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mahendra J. Shetty Target entity description: Mahendra J. Shetty is an Indian cinematographer known for his visually rich and atmospheric work in Hindi cinema.
-
A.
Arun Shridhar Vaidya
Arun Shridhar Vaidya was an Indian Army general who served as Chief of Army Staff and played a central role in major counterinsurgency operations in the 1980s.
-
B.
Ranjan Raghu Shetty
Ranjan Raghu Shetty is a prominent film director known for his influential work in Tulu-language cinema.
-
C.
Ravi D. Mehta
Ravi D. Mehta is a film producer known for his work on projects such as the 2017 movie "Unforgettable."
-
D.
Jayant Jathar
Jayant Jathar is a film editor best known for his work on the acclaimed Marathi musical drama "Katyar Kaljat Ghusali."
-
E.
Mangubhai C. Patel
Mangubhai C. Patel is an Indian politician and member of the Bharatiya Janata Party who has served in various legislative and leadership roles, including as a state governor.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a3320448190ae3931062599116e |
completed | April 29, 2026, 1:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0af0f90f5881908f0011690cb0f1e4 |
completed | May 18, 2026, 10:59 a.m. |
| NEDg | Description generation | batch_6a0af268db2881908706641ad1e41f79 |
completed | May 18, 2026, 11:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b08e411048190a368214c57c35d5e |
completed | May 18, 2026, 12:41 p.m. |
Created at: April 16, 2026, 8:47 p.m.