Triple
T20351696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uttar Falguni |
E496026
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Kamal Bose |
—
|
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: Kamal Bose | Statement: [Uttar Falguni, cinematographyBy, Kamal Bose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamal Bose Context triple: [Uttar Falguni, cinematographyBy, Kamal Bose]
-
A.
Kamal Bose
chosen
Kamal Bose was a renowned Indian cinematographer celebrated for his work on classic Hindi films, particularly in collaboration with directors like Bimal Roy.
-
B.
Kumar Bose
Kumar Bose is a renowned Indian tabla maestro known for his virtuosity and contributions to Hindustani classical music.
-
C.
Sailesh Kumar Bose
Sailesh Kumar Bose is a notable member of the prominent Bose family of India, recognized for its influential figures in politics, nationalism, and public life.
-
D.
Benoy Bose
Benoy Bose is an individual notable for bearing the surname Bose, which is associated with several prominent figures in Indian history, science, and culture.
-
E.
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.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67850ace48190b19aff5780fef7e8 |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:24 a.m.