Triple
T16528211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ravi Basrur |
E401493
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ravi Basrur |
E401493
|
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: Ravi Basrur | Statement: [Ravi Basrur, name, Ravi Basrur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ravi Basrur Context triple: [Ravi Basrur, name, Ravi Basrur]
-
A.
Ravi Basrur
chosen
Ravi Basrur is an Indian film music composer and sound designer best known for his work on high-profile Kannada films such as the K.G.F series.
-
B.
Dileep Rao
Dileep Rao is an American actor known for his supporting roles in major films such as Avatar, Drag Me to Hell, and Inception.
-
C.
Sanjay Reddy
Sanjay Reddy is an Indian economist known for his work in development economics, poverty measurement, and global justice.
-
D.
Vikas Sivaraman
Vikas Sivaraman is an Indian cinematographer known for his work on acclaimed Hindi films, including the 1999 action drama "Sarfarosh."
-
E.
Ravi Jhankal
Ravi Jhankal is an Indian film, television, and theatre actor known for his character roles in critically acclaimed Hindi productions.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed57be481908625d4c5aab0940c |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00758d82748190acfb8bbc3047d5a5 |
completed | May 10, 2026, 12:09 p.m. |
Created at: April 10, 2026, 5:14 a.m.