def batch_parse(text_dir, stanford_dir):
"""Function to parse multi-sentence input using StanfordNLP in batch mode.
The function parses the input, and performs pronoun coreferencing where
appropriate. Coreferences are linked across sentences.
Parameters
----------
text_dir: String.
Directory of text files to parse using StanfordNLP.
stanford_dir: String.
Directory that contains the StanfordNLP files.
Returns
--------
output_dict : Dictionary.
Parsed and formated output for each input event or news
story. This dictionary contains the info that should pass
to the event coder and other postprocessing utilites.
Output dictionary format is of the following form. The
main level has story IDs, e.g., story1.txt, as keys
with values dictionaries as values. At this stage, the
value dictionary has one key, `sent_info`, which has
another dictionary as the value. Within the `sent_info`
dictionary are keys `sents` and `coref_info`. Each has
dictionaries as their values. The `sents` dictionary has
integers as keys, which represent the different sentences
within a text input. Each individual sentence dictionary
contains the keys `parse_tree` (nltk.tree),
`dependencies` (list), `np_words` (list),
`word_info` (list), `verb_phrases` (list),
`vp_words` (list), and `noun_phrases` (list).
The `coref_info` dictionary has a
similar structure, with each sentence having its own
individual dictionary with keys `shift` (integer) and
`corefs` (list). Given this, the final structure of the
output resembles:
{'event_id': {'sent_info': {'sents': {0: {'parse_tree': tree
'dependencies': list}
1: {...}}
'coref_info': {0: {'shift': 0
'corefs': []}}
}}}
"""
output_dict = dict()
results = corenlp.batch_parse(text_dir, stanford_dir)
for index in xrange(len(results)):
parsed = results[index]
name = parsed['file_name']
output = parse_sents(name, parsed)
output_dict.update(output)
for article in output_dict:
utilities.coref_replace(output_dict, article)
return output_dict
def parse(event_dict, stanford_dir):
"""Function to parse single-sentence input using StanfordNLP. The function
parses the input, and performs pronoun coreferencing where appropriate. If
the input is longer than one setence as determined by StanfordNLP, the
program will pass on that input.
Parameters
----------
event_dict : Dictionary
Dictionary of that contains the events and text. Excepts story
IDs as keys with an additional dictionary as the value. Within
each story ID value dictionary should be an item named 'story'.
stanford_dir: String.
Directory that contains the StanfordNLP files.
Returns
--------
output_dict : Dictionary
Parsed and formated output for each input event or news
story. This dictionary contains the info that should pass
to the event coder and other postprocessing utilites.
Output dictionary format is of the following form. The
main level has story IDs, e.g., story1.txt, as keys
with values dictionaries as values. At this stage, the
value dictionary has one key, `sent_info`, which has
another dictionary as the value. Within the `sent_info`
dictionary are keys `sents` and `coref_info`. Each has
dictionaries as their values. The `sents` dictionary has
integers as keys, which represent the different sentences
within a text input. Each individual sentence dictionary
contains the keys `parse_tree` (nltk.tree),
`dependencies` (list), `np_words` (list),
`word_info` (list), `verb_phrases` (list),
`vp_words` (list), and `noun_phrases` (list).
The `coref_info` dictionary has a
similar structure, with each sentence having its own
individual dictionary with keys `shift` (integer) and
`corefs` (list). Given this, the final structure of the
output resembles:
{'event_id': {'sent_info': {'sents': {0: {'parse_tree': tree
'dependencies': list}
1: {...}}
'coref_info': {0: {'shift': 0
'corefs': []}}
}}}
"""
output_dict = dict()
corenlp_dir = stanford_dir
core = corenlp.StanfordCoreNLP(corenlp_dir)
for key in event_dict:
result = core.raw_parse(event_dict[key]['story'])
if len(result['sentences']) == 1:
output = parse_sents(key, result)
output_dict.update(output)
if 'coref' in result:
utilities.coref_replace(output_dict, key)
else:
print """Key {} is longer than one sentence, passing. Please check
the input format if you would like this key to be parsed!""".format(key)
pass
return output_dict