Triple
T7931419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zscaler |
E184196
|
entity |
| Predicate | hasKeyPerson |
P256
|
FINISHED |
| Object | Jay Chaudhry |
E697124
|
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: Jay Chaudhry | Statement: [Zscaler, hasKeyPerson, Jay Chaudhry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Chaudhry Context triple: [Zscaler, hasKeyPerson, Jay Chaudhry]
-
A.
Jay Chaudhry
chosen
Jay Chaudhry is an Indian-American entrepreneur and billionaire best known as the founder and CEO of the cloud security company Zscaler.
-
B.
Asheem Chandna
Asheem Chandna is a prominent venture capitalist known for investing in and advising leading enterprise technology and cybersecurity startups.
-
C.
Naveen Andrews
Naveen Andrews is a British actor best known for his roles in the television series "Lost" and films such as "The English Patient."
-
D.
Sam Joshi
Sam Joshi is an American politician who serves as the mayor of Edison Township, New Jersey.
-
E.
Jay Mehta
Jay Mehta is an Indian businessman and industrialist, known for his interests in cement and other industries and for being married to actress Juhi Chawla.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3accc388819087065ebe7d5d9591 |
completed | March 31, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe011ccec8190ab60d18b761666af |
completed | March 31, 2026, 2:54 p.m. |
Created at: March 30, 2026, 5:07 p.m.