Return token span from NerPipeline
# 🚀 Feature request

I would like to suggest that NerPipeline should return the span in the original text where the matched entity exists. 

Instead of:
```python
[
    {"word": "New", "score": 0.9995751976966858, "entity": "LOC"}, 
    {"word": "York", "score": 0.9996403455734253, "entity": "LOC"}
]
```

I would like to see this:
```python
[
    {"word": "New", "score": 0.9995751976966858, "entity": "LOC", "span": (0, 3)}, 
    {"word": "York", "score": 0.9996403455734253, "entity": "LOC", "span": (4, 8)}
]
```

## Motivation

I'm trying to use transformers for NER, and I specifically want to return multi word entities as one phrase. 

With the above example, I would like to return "New York". With spans added, I would be able to merge nearby tokens into one. 

This makes it possible to differentiate the result of "A place called New, and a place called York" from "A place called New York". With the current scheme, they both return the same thing.

## Your contribution

I think I understand NerPipeline enough to make a PR, if this is something you would be open to.
Oh, I guess a workaround is to pass in `ignore_labels=[]` when creating the pipeline. This makes the nlp call return all tokens, including the ones that are not part of NER. Then I can just chunk two tokens together if their label is the same and they are nearby. Does this make sense, or am I missing something fundamental?<|||||>Hi again, would you be open to a PR fixing this?<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
