Triple
T11022925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamal Bose |
E260534
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | Shakti Samanta |
E694859
|
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: Shakti Samanta | Statement: [Kamal Bose, workedWith, Shakti Samanta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shakti Samanta Context triple: [Kamal Bose, workedWith, Shakti Samanta]
-
A.
Shakti Samanta
chosen
Shakti Samanta was a prominent Indian film director and producer known for classic Hindi films such as "Aradhana," "Kashmir Ki Kali," and "Amar Prem."
-
B.
Ashok Dinda
Ashok Dinda is an Indian fast bowler who played domestic cricket for Bengal and represented India in both One Day Internationals and Twenty20 Internationals.
-
C.
Hill Kharia
Hill Kharia is a dialect of the Kharia language spoken by Kharia communities in hilly regions of eastern India.
-
D.
Ashok Chandra
Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
-
E.
Vinai Kumar Saxena
Vinai Kumar Saxena is an Indian administrator and former chairman of the Khadi and Village Industries Commission who serves as the Lieutenant Governor of Delhi.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797bd88188190a644adc9283cabb8 |
completed | April 9, 2026, 12:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3750917d481909e73de0bfae27827 |
completed | April 18, 2026, 12:11 p.m. |
Created at: April 8, 2026, 9:25 p.m.