Triple
T11228471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benoy Bose |
E265754
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Benoy Bose |
E265754
|
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: Benoy Bose | Statement: [Benoy Bose, name, Benoy Bose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benoy Bose Context triple: [Benoy Bose, name, Benoy Bose]
-
A.
Benoy Bose
chosen
Benoy Bose is an individual notable for bearing the surname Bose, which is associated with several prominent figures in Indian history, science, and culture.
-
B.
Pradip Bose
Pradip Bose is a computer engineer and researcher known for his contributions to microprocessor architecture and performance analysis, particularly at IBM.
-
C.
Bibhu Bhattacharya
Bibhu Bhattacharya was an Indian actor best known for playing the character Jatayu in Satyajit Ray’s Feluda series of films and television adaptations.
-
D.
Kumar Bose
Kumar Bose is a renowned Indian tabla maestro known for his virtuosity and contributions to Hindustani classical music.
-
E.
Jnanesh Mukherjee
Jnanesh Mukherjee is an Indian actor known for his work in Bengali cinema and television.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e900fbcc8190a3177f8a73564433 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e8a4322c8190a30e460892123579 |
completed | April 20, 2026, 8:49 a.m. |
Created at: April 8, 2026, 9:30 p.m.