 Input format for a BertTokenClassification task
# ❓ Questions & Help
https://stackoverflow.com/questions/61168882/processing-and-handling-input-ids-when-using-bert-for-token-classification

So i want to use BERT for semantic entity extraction. This is not quite the same as NER or POS tagging.

for example eg- Given a sentence:
```
A=The leak could have been stopped the same hour it was discovered if the well had a working shut-off valve
```
it returns two separate phrases
```
B= if the well had a working shut-off valve, and C= The leak could have been stopped the same hour it was discovered.
```
thus i pd read a three column csv file of  A, B, C, similar data. and BERTtokenised them and all, so my question, whats the appropriate way to load the data for training, does it have to be converted into a CONLL format? 

```
from torch.utils.data import TensorDataset, random_split
dataset = TensorDataset(input_ids, attention_masks, labels)
```
How do i put the data into input_ids

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