Triple
T21944893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chandni Bar |
E541909
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Anil Pandey
Anil Pandey is an Indian screenwriter known for his work on the critically acclaimed film "Chandni Bar."
|
E1519076
|
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: Anil Pandey | Statement: [Chandni Bar, screenwriter, Anil Pandey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anil Pandey Context triple: [Chandni Bar, screenwriter, Anil Pandey]
-
A.
Kamal Pandey
Kamal Pandey is an Indian screenwriter best known for his work on Hindi films such as the romantic comedy-drama "Qarib Qarib Singlle."
-
B.
Anup Kumar
Anup Kumar is an Indian kabaddi player renowned for his leadership of the national team and his success in the Pro Kabaddi League.
-
C.
Anup Kumar
Anup Kumar was an Indian actor and comedian best known for his work in Hindi cinema, particularly in supporting and character roles.
-
D.
Deepak Kapur
Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
-
E.
Ravi Nandan
Ravi Nandan is a television and film producer known for his executive production work on comedy series such as "Playing House."
- 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: Anil Pandey Triple: [Chandni Bar, screenwriter, Anil Pandey]
Generated description
Anil Pandey is an Indian screenwriter known for his work on the critically acclaimed film "Chandni Bar."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anil Pandey Target entity description: Anil Pandey is an Indian screenwriter known for his work on the critically acclaimed film "Chandni Bar."
-
A.
Kamal Pandey
Kamal Pandey is an Indian screenwriter best known for his work on Hindi films such as the romantic comedy-drama "Qarib Qarib Singlle."
-
B.
Anup Kumar
Anup Kumar is an Indian kabaddi player renowned for his leadership of the national team and his success in the Pro Kabaddi League.
-
C.
Anup Kumar
Anup Kumar was an Indian actor and comedian best known for his work in Hindi cinema, particularly in supporting and character roles.
-
D.
Deepak Kapur
Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
-
E.
Ravi Nandan
Ravi Nandan is a television and film producer known for his executive production work on comedy series such as "Playing House."
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242688988190a7b8f033c49368de |
completed | April 28, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a8787a8d481909637a9c110fd2e67 |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a891eb0708190a4575a01f45b98aa |
completed | May 18, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a89977c8c8190a5c87d1c2b68ed48 |
completed | May 18, 2026, 3:37 a.m. |
Created at: April 16, 2026, 7:56 p.m.