Triple
T20083941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thapar |
E500073
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Sanjay K. Thapar |
—
|
NE NERFINISHED |
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: Sanjay K. Thapar | Statement: [Thapar, usedBy, Sanjay K. Thapar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanjay K. Thapar Context triple: [Thapar, usedBy, Sanjay K. Thapar]
-
A.
Sanjay Thapar
chosen
Sanjay Thapar is an individual associated with the use or application of something created or provided by Thapar, though specific public details about him are limited.
-
B.
Sanjay Bhalla
Sanjay Bhalla is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Bhalla.
-
C.
Neil K. Garg
Neil K. Garg is an American organic chemist and UCLA professor renowned for his innovative work in synthetic methodology and chemistry education.
-
D.
Ravi D. Mehta
Ravi D. Mehta is a film producer known for his work on projects such as the 2017 movie "Unforgettable."
-
E.
Ravi Thapar
Ravi Thapar is an Indian politician who has served as a member of the Indian National Congress and held various public offices.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655a2d2c81908a6b8fd2f209a825 |
completed | April 20, 2026, 5:41 p.m. |
Created at: April 11, 2026, 3:41 p.m.