Triple
T1598322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azim Premji University |
E34334
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Azim Premji |
E5073
|
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: Azim Premji | Statement: [Azim Premji University, namedAfter, Azim Premji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azim Premji Context triple: [Azim Premji University, namedAfter, Azim Premji]
-
A.
Azim Premji
chosen
Azim Premji is an Indian business tycoon and philanthropist, best known as the longtime chairman of Wipro and one of the world’s leading charitable donors.
-
B.
Rishad Premji
Rishad Premji is an Indian business executive who serves as the chairman of Wipro Limited, one of India’s leading global IT services companies.
-
C.
Mohamed Premji
Mohamed Premji was an Indian industrialist and entrepreneur best known as the founder of Wipro, which he built into a major business conglomerate.
-
D.
N. R. Narayana Murthy
N. R. Narayana Murthy is an Indian billionaire businessman best known as the co-founder of Infosys, a pioneering global IT services company.
-
E.
Gagan Biyani
Gagan Biyani is an entrepreneur best known as a co-founder of the online learning platform Udemy and for his work in the education technology sector.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9092f5f148190b987bc943e89e29c |
completed | March 5, 2026, 4:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad797d8c68819093fb2bcae0a08698 |
completed | March 8, 2026, 1:28 p.m. |
Created at: March 4, 2026, 7:27 p.m.