Simplify data fetchers

[alanakbik]

There is a lot of redundant code in the data fetcher helper routines. Simplify by creating a generic 'CoNLL-column' data reader that can be passed the column definition, so it is applicable to CoNLL03, CoNLL2000 and any other sequence labeling data that is formatted in a similar column style.

[alanakbik]

Data fetchers now simplified. You can read any CoNLL column formatted file by passing a dict that specifies what column is what field.

For instance:

from flair.data_fetcher import NLPTaskDataFetcher

sentences = NLPTaskDataFetcher.read_column_data('/path/to/conll03/data', column_name_map={0: 'text', 3: 'ner'})

for sentence in sentences:
    print(sentence.to_tagged_string()) 

Will read a CoNLL-03 formatted file and map the first column (index 0) to the lexical value of each word (i.e. the token text) and column index 3 as the NER tag.