Triple
T23174485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Never Have I Ever |
E578956
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Mohan Vishwakumar
Mohan Vishwakumar is a loving, supportive father whose death deeply shapes the emotional journey of protagonist Devi in the coming-of-age series "Never Have I Ever."
|
E1572358
|
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: Mohan Vishwakumar | Statement: [Never Have I Ever, character, Mohan Vishwakumar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mohan Vishwakumar Context triple: [Never Have I Ever, character, Mohan Vishwakumar]
-
A.
Sunil Lahri
Sunil Lahri is an Indian television actor best known for portraying Lakshman in Ramanand Sagar’s iconic mythological series "Ramayan."
-
B.
Rohit Ghai
Rohit Ghai is a technology executive best known for serving as the CEO of cybersecurity company RSA Security.
-
C.
Sunil Perkash
Sunil Perkash is a film producer best known for his work on major Hollywood movies such as "Salt" and "Enchanted."
-
D.
Amitabh Bora
Amitabh Bora is a film editor best known for his work on the Assamese film "Maj Rati Keteki."
-
E.
Jabbar Patel
Jabbar Patel is an acclaimed Indian theatre and film director known for his influential work in Marathi parallel cinema and politically charged stage productions.
- 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: Mohan Vishwakumar Triple: [Never Have I Ever, character, Mohan Vishwakumar]
Generated description
Mohan Vishwakumar is a loving, supportive father whose death deeply shapes the emotional journey of protagonist Devi in the coming-of-age series "Never Have I Ever."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mohan Vishwakumar Target entity description: Mohan Vishwakumar is a loving, supportive father whose death deeply shapes the emotional journey of protagonist Devi in the coming-of-age series "Never Have I Ever."
-
A.
Sunil Lahri
Sunil Lahri is an Indian television actor best known for portraying Lakshman in Ramanand Sagar’s iconic mythological series "Ramayan."
-
B.
Rohit Ghai
Rohit Ghai is a technology executive best known for serving as the CEO of cybersecurity company RSA Security.
-
C.
Sunil Perkash
Sunil Perkash is a film producer best known for his work on major Hollywood movies such as "Salt" and "Enchanted."
-
D.
Amitabh Bora
Amitabh Bora is a film editor best known for his work on the Assamese film "Maj Rati Keteki."
-
E.
Jabbar Patel
Jabbar Patel is an acclaimed Indian theatre and film director known for his influential work in Marathi parallel cinema and politically charged stage productions.
- 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_69e245fd2a388190b814c0dfa15f7148 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f69cb1881909e0f47d3b32e2cb1 |
completed | April 29, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c30ac8cb0819095ab0c5cec85f0f1 |
completed | May 19, 2026, 9:43 a.m. |
| NEDg | Description generation | batch_6a0c320879dc8190aa5852baf01a822e |
completed | May 19, 2026, 9:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c32b1115081909b5e6b554807b8e1 |
completed | May 19, 2026, 9:51 a.m. |
Created at: April 17, 2026, 4:04 p.m.