Triple
T16659892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neil K. Garg |
E404827
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Neil K. Garg |
E404827
|
NE FINISHED |
How this triple was built (2 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: Neil K. Garg | Statement: [Neil K. Garg, name, Neil K. Garg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neil K. Garg Context triple: [Neil K. Garg, name, Neil K. Garg]
-
A.
Neil K. Garg
chosen
Neil K. Garg is an American organic chemist and UCLA professor renowned for his innovative work in synthetic methodology and chemistry education.
-
B.
Satish K. Tripathi
Satish K. Tripathi is an Indian-American computer scientist and academic leader who serves as the president of the University at Buffalo, a flagship institution of the State University of New York system.
-
C.
Jainendra K. Jain
Jainendra K. Jain is a theoretical physicist best known for formulating the composite fermion theory that explains the fractional quantum Hall effect.
-
D.
Sanjay Jain
Sanjay Jain is an economist recognized for his academic contributions and scholarship associated with the Delhi School of Economics.
-
E.
Vikram Adve
Vikram Adve is a computer scientist best known as a co-creator of the LLVM compiler infrastructure and a professor at the University of Illinois at Urbana-Champaign.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37bfe0fb081909f2de38df0ed59d7 |
completed | April 18, 2026, 12:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084ce7cf0819091e7a4de2cc010ea |
completed | May 10, 2026, 1:14 p.m. |
Created at: April 10, 2026, 5:18 a.m.