Triple
T8628423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neel Sethi |
E204336
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Neel Sethi |
E204336
|
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: Neel Sethi | Statement: [Neel Sethi, name, Neel Sethi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neel Sethi Context triple: [Neel Sethi, name, Neel Sethi]
-
A.
Neel Sethi
chosen
Neel Sethi is an American actor best known for playing Mowgli in Disney’s 2016 live-action adaptation of The Jungle Book.
-
B.
Sachit Mehra
Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
-
C.
Zaab Sethna
Zaab Sethna is a public relations and communications professional best known as the husband of actress Gina Bellman.
-
D.
Nick Mehta
Nick Mehta is a technology executive best known as the CEO of Gainsight and a prominent advocate and thought leader in the field of customer success.
-
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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc473f6b888190ae40d65f24122c88 |
completed | March 31, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebc02b4008190a70ca8eb6f43926d |
completed | April 2, 2026, 6:57 p.m. |
Created at: March 30, 2026, 6:27 p.m.