Adding Qanta (Quizbowl) Dataset
Hi @EntilZha - sorry for waiting so long until taking action here. We created a new command and a new recipe of how to add dummy_data. Can you maybe rebase to `master` as explained in 7. of https://github.com/huggingface/nlp/blob/master/CONTRIBUTING.md#how-to-contribute-to-nlp and check that your dummy data is correct following the instructions here: https://github.com/huggingface/nlp/blob/master/CONTRIBUTING.md#how-to-add-a-dataset ? 

If the tests described in 5. of https://github.com/huggingface/nlp/blob/master/CONTRIBUTING.md#how-to-add-a-dataset pass we can merge the PR :-)  I updated to the most recent master and followed the steps, but still having the similar error where it can't find the correct file since the path to the directory is given, rather than the individual files within them. This still something wrong about how I'm inputting the data or how the tests are reading it? It's the dummy_data structure. You actually have to call the dummy data file name `dummy_data` (not .json anything). So there should not be a `dummy_data` folder but for each config only a `dummy_data` which contains your json dummy data. Can you maybe try once more - if it doesn't work I do it for you :-).  Would that work if there are multiple files? In my case, I'm including something similar to squad 1.0/2.0 where we have the main dataset + an additional challenge set in different files. Would I have the zip decompress to two files in that case? This dataset was actually a special case. It helped us improve the  dummy data instructions :-), see #195 .Close this PR and merge #194.
This PR adds the qanta question answering datasets from [Quizbowl: The Case for Incremental Question Answering](https://arxiv.org/abs/1904.04792) and [Trick Me If You Can: Human-in-the-loop Generation of Adversarial Question Answering Examples](https://www.aclweb.org/anthology/Q19-1029/) (adversarial fold)

This partially continues a discussion around fixing dummy data from https://github.com/huggingface/nlp/issues/161

I ran the following code to double check that it works and did some sanity checks on the output. The majority of the code itself is from our `allennlp` version of the dataset reader.

```python
import nlp
# Default is full question
data = nlp.load_dataset('./datasets/qanta') 
# Four configs
# Primarily useful for training
data = nlp.load_dataset('./datasets/qanta', 'mode=sentences,char_skip=25')  
# Primarily used in evaluation
data = nlp.load_dataset('./datasets/qanta', 'mode=first,char_skip=25')  
data = nlp.load_dataset('./datasets/qanta', 'mode=full,char_skip=25')  
# Primarily useful in evaluation and "live" play
data = nlp.load_dataset('./datasets/qanta', 'mode=runs,char_skip=25')  
```