Triple
T13061791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jitendra Malik |
E329214
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object |
Abhinav Gupta
Abhinav Gupta is a prominent computer vision and machine learning researcher known for his influential work in visual recognition and deep learning.
|
E1017404
|
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: Abhinav Gupta | Statement: [Jitendra Malik, notableStudent, Abhinav Gupta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abhinav Gupta Context triple: [Jitendra Malik, notableStudent, Abhinav Gupta]
-
A.
Abhishek Verma
Abhishek Verma is a computer scientist best known as a co-creator of Google Borg, the large-scale cluster management and scheduling system that inspired Kubernetes.
-
B.
Arjun Raina
Arjun Raina is an Indian actor and theatre artist known for his work in film, television, and stage, often associated with experimental and parallel cinema.
-
C.
Sachit Mehra
Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
-
D.
Gautam Kumar
Gautam Kumar is known as the son of legendary Indian Bengali actor Uttam Kumar.
-
E.
Gautam Krishna
Gautam Krishna is the son of prominent Telugu film actor Mahesh Babu and is known primarily as a celebrity child in the Indian entertainment industry.
- 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: Abhinav Gupta Triple: [Jitendra Malik, notableStudent, Abhinav Gupta]
Generated description
Abhinav Gupta is a prominent computer vision and machine learning researcher known for his influential work in visual recognition and deep learning.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Abhinav Gupta Target entity description: Abhinav Gupta is a prominent computer vision and machine learning researcher known for his influential work in visual recognition and deep learning.
-
A.
Abhishek Verma
Abhishek Verma is a computer scientist best known as a co-creator of Google Borg, the large-scale cluster management and scheduling system that inspired Kubernetes.
-
B.
Arjun Raina
Arjun Raina is an Indian actor and theatre artist known for his work in film, television, and stage, often associated with experimental and parallel cinema.
-
C.
Sachit Mehra
Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
-
D.
Gautam Kumar
Gautam Kumar is known as the son of legendary Indian Bengali actor Uttam Kumar.
-
E.
Gautam Krishna
Gautam Krishna is the son of prominent Telugu film actor Mahesh Babu and is known primarily as a celebrity child in the Indian entertainment industry.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980e7ee548190b4b18bdb1357c359 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbe45c8c819080fbdf1d94376feb |
completed | May 3, 2026, 4:15 a.m. |
| NEDg | Description generation | batch_69f6cd3d5090819091b65f544ad139fd |
completed | May 3, 2026, 4:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6cdc8d52c819083717a455d589646 |
completed | May 3, 2026, 4:23 a.m. |
Created at: April 9, 2026, 8:59 p.m.