Triple
T2169600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edmund M. Clarke |
E46990
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object |
Somesh Jha
Somesh Jha is a computer scientist known for his research in formal methods, security, and software verification.
|
E239163
|
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: Somesh Jha | Statement: [Edmund M. Clarke, notableStudent, Somesh Jha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Somesh Jha Context triple: [Edmund M. Clarke, notableStudent, Somesh Jha]
-
A.
Anurag Behar
Anurag Behar is an Indian educationist and social sector leader best known for heading the Azim Premji Foundation and contributing to large-scale education reform in India.
-
B.
Anupam Tripathi
Anupam Tripathi is an Indian actor best known internationally for his breakout role as Ali Abdul in the South Korean Netflix series "Squid Game."
-
C.
Sachit Mehra
Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
-
D.
Kunal Nayyar
Kunal Nayyar is a British-Indian actor best known for playing the socially awkward astrophysicist Rajesh Koothrappali on the hit sitcom "The Big Bang Theory."
-
E.
Rajat Monga
Rajat Monga is a computer scientist and engineer best known as a co-creator and early lead of TensorFlow at Google Brain.
- 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: Somesh Jha Triple: [Edmund M. Clarke, notableStudent, Somesh Jha]
Generated description
Somesh Jha is a computer scientist known for his research in formal methods, security, and software verification.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Somesh Jha Target entity description: Somesh Jha is a computer scientist known for his research in formal methods, security, and software verification.
-
A.
Anurag Behar
Anurag Behar is an Indian educationist and social sector leader best known for heading the Azim Premji Foundation and contributing to large-scale education reform in India.
-
B.
Anupam Tripathi
Anupam Tripathi is an Indian actor best known internationally for his breakout role as Ali Abdul in the South Korean Netflix series "Squid Game."
-
C.
Sachit Mehra
Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
-
D.
Kunal Nayyar
Kunal Nayyar is a British-Indian actor best known for playing the socially awkward astrophysicist Rajesh Koothrappali on the hit sitcom "The Big Bang Theory."
-
E.
Rajat Monga
Rajat Monga is a computer scientist and engineer best known as a co-creator and early lead of TensorFlow at Google Brain.
- 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_69a88a184cbc8190877791f6552c2484 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbeaeb58881908ad34f7b253bac2a |
completed | March 7, 2026, 5:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58f511a08190880fbde8900d59df |
completed | March 9, 2026, 5:21 a.m. |
| NEDg | Description generation | batch_69ae59a9b010819081491e988184b386 |
completed | March 9, 2026, 5:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5a12f11c81908cc345905f0a485e |
completed | March 9, 2026, 5:26 a.m. |
Created at: March 4, 2026, 7:45 p.m.