Triple
T19273826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Well Done Abba |
E481994
|
entity |
| Predicate | cinematographer |
P1953
|
FINISHED |
| Object |
Rajan Kothari
Rajan Kothari was an Indian cinematographer known for his work on acclaimed films and television projects, including the film "Well Done Abba."
|
E1376142
|
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: Rajan Kothari | Statement: [Well Done Abba, cinematographer, Rajan Kothari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rajan Kothari Context triple: [Well Done Abba, cinematographer, Rajan Kothari]
-
A.
Rajen Kothari
Rajen Kothari was an Indian cinematographer known for his visually expressive work in Hindi cinema, including acclaimed films like "Zubeidaa."
-
B.
Vijay Joshi
Vijay Joshi is an Indian economist known for his influential work on macroeconomic policy and development, particularly in the context of the Indian economy.
-
C.
K. V. Kamath
K. V. Kamath is an Indian banker and former ICICI Bank chief who became the inaugural president of the BRICS-founded New Development Bank.
-
D.
Anil Gupta
Anil Gupta is a British television writer and producer best known for his work on acclaimed comedy series such as "The Office" and "Citizen Khan."
-
E.
Arun Gupta
Arun Gupta is the child of Indian actress and screenwriter Sonali Das Gupta.
- 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: Rajan Kothari Triple: [Well Done Abba, cinematographer, Rajan Kothari]
Generated description
Rajan Kothari was an Indian cinematographer known for his work on acclaimed films and television projects, including the film "Well Done Abba."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rajan Kothari Target entity description: Rajan Kothari was an Indian cinematographer known for his work on acclaimed films and television projects, including the film "Well Done Abba."
-
A.
Rajen Kothari
Rajen Kothari was an Indian cinematographer known for his visually expressive work in Hindi cinema, including acclaimed films like "Zubeidaa."
-
B.
Vijay Joshi
Vijay Joshi is an Indian economist known for his influential work on macroeconomic policy and development, particularly in the context of the Indian economy.
-
C.
K. V. Kamath
K. V. Kamath is an Indian banker and former ICICI Bank chief who became the inaugural president of the BRICS-founded New Development Bank.
-
D.
Anil Gupta
Anil Gupta is a British television writer and producer best known for his work on acclaimed comedy series such as "The Office" and "Citizen Khan."
-
E.
Arun Gupta
Arun Gupta is the child of Indian actress and screenwriter Sonali Das Gupta.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbba7758819081c1c78667c59c5e |
completed | April 20, 2026, 10:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a073b189518819098f8b858f9f03a7b |
completed | May 15, 2026, 3:26 p.m. |
| NEDg | Description generation | batch_6a073b974a448190be416ef4d0574972 |
completed | May 15, 2026, 3:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a073c2defe08190b340ba568b8fd507 |
completed | May 15, 2026, 3:30 p.m. |
Created at: April 10, 2026, 1:29 p.m.