Triple
T22599346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saans |
E574769
|
entity |
| Predicate | vocalist |
P2000
|
FINISHED |
| Object | Mohit Chauhan |
—
|
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: Mohit Chauhan | Statement: [Saans, vocalist, Mohit Chauhan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mohit Chauhan Context triple: [Saans, vocalist, Mohit Chauhan]
-
A.
Mohit Chauhan
chosen
Mohit Chauhan is an Indian playback singer renowned for his soulful voice and popular Bollywood songs such as "Tum Se Hi" and "Masakali."
-
B.
Prateek Kuhad
Prateek Kuhad is an Indian singer-songwriter known for his mellow, introspective indie-folk music and widespread acclaim both in India and internationally.
-
C.
Sachit Mehra
Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
-
D.
Shantanu Thakur
Shantanu Thakur is an Indian politician from the Bharatiya Janata Party who serves as a Minister of State in the central government and represents the Bangaon constituency in the Lok Sabha.
-
E.
Mohit Iyyer
Mohit Iyyer is a computer scientist and natural language processing researcher known for his work on deep learning models for language understanding and generation.
- 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1626b5f5481909a104088d1c96720 |
completed | April 29, 2026, 1:44 a.m. |
Created at: April 17, 2026, 2:50 p.m.