Triple
T16827077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harsh Jain |
E409046
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Harsh Jain |
E409046
|
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: Harsh Jain | Statement: [Harsh Jain, name, Harsh Jain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harsh Jain Context triple: [Harsh Jain, name, Harsh Jain]
-
A.
Harsh Jain
chosen
Harsh Jain is an Indian entrepreneur best known as the co-founder and CEO of Dream Sports, the parent company of fantasy sports platform Dream11.
-
B.
Sanjay Jain
Sanjay Jain is an economist recognized for his academic contributions and scholarship associated with the Delhi School of Economics.
-
C.
Raj Jain
Raj Jain is a prominent computer scientist known for his influential contributions to computer networking and performance analysis.
-
D.
Prashant Damle
Prashant Damle is a renowned Indian actor and comedian celebrated for his prolific work in Marathi theatre, television, and films.
-
E.
Rajeev Misra
Rajeev Misra is an Indian-born financier and executive best known for leading SoftBank’s Vision Fund, one of the world’s largest technology investment funds.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b31404c88190a3b2802842ca77eb |
completed | April 18, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfc366bc819084406ee88ddffe44 |
completed | May 10, 2026, 6:34 p.m. |
Created at: April 10, 2026, 5:23 a.m.