Triple
T19273757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Welcome to Sajjanpur |
E481993
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Ashok Mishra
Ashok Mishra is an Indian screenwriter known for his work on films such as "Welcome to Sajjanpur."
|
E1384989
|
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: Ashok Mishra | Statement: [Welcome to Sajjanpur, screenwriter, Ashok Mishra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashok Mishra Context triple: [Welcome to Sajjanpur, screenwriter, Ashok Mishra]
-
A.
Kailashpati Mishra
Kailashpati Mishra was an Indian politician and leader of the Bharatiya Janata Party who served in various governmental and organizational roles.
-
B.
Pramod Kumar Mishra
Pramod Kumar Mishra is a senior Indian Administrative Service officer who serves as a key bureaucratic advisor and top aide to the Prime Minister of India.
-
C.
Vijay Maurya
Vijay Maurya is an Indian actor, writer, and director known for his work in Hindi cinema and web series.
-
D.
Akhilendra Mishra
Akhilendra Mishra is an Indian film and television actor known for his character roles in Hindi cinema and TV, including notable performances in movies like Lagaan and Sarfarosh.
-
E.
Virendra Sharma
Virendra Sharma is a British Labour Party politician who has served as the Member of Parliament for the London constituency of Ealing Southall.
- 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: Ashok Mishra Triple: [Welcome to Sajjanpur, screenwriter, Ashok Mishra]
Generated description
Ashok Mishra is an Indian screenwriter known for his work on films such as "Welcome to Sajjanpur."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ashok Mishra Target entity description: Ashok Mishra is an Indian screenwriter known for his work on films such as "Welcome to Sajjanpur."
-
A.
Kailashpati Mishra
Kailashpati Mishra was an Indian politician and leader of the Bharatiya Janata Party who served in various governmental and organizational roles.
-
B.
Pramod Kumar Mishra
Pramod Kumar Mishra is a senior Indian Administrative Service officer who serves as a key bureaucratic advisor and top aide to the Prime Minister of India.
-
C.
Vijay Maurya
Vijay Maurya is an Indian actor, writer, and director known for his work in Hindi cinema and web series.
-
D.
Akhilendra Mishra
Akhilendra Mishra is an Indian film and television actor known for his character roles in Hindi cinema and TV, including notable performances in movies like Lagaan and Sarfarosh.
-
E.
Virendra Sharma
Virendra Sharma is a British Labour Party politician who has served as the Member of Parliament for the London constituency of Ealing Southall.
- 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_6a075ef735bc8190b7fdebafd73f9f90 |
completed | May 15, 2026, 5:59 p.m. |
| NEDg | Description generation | batch_6a075f8c106481908e6fd7631ae69842 |
completed | May 15, 2026, 6:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a076070784c81908d28306344363c53 |
completed | May 15, 2026, 6:05 p.m. |
Created at: April 10, 2026, 1:29 p.m.