def parse(self, corenlppath = False, operations = False, copula_head = True,
speaker_segmentation = False, memory_mb = False, *args, **kwargs):
"""
Parse an unparsed corpus, saving to disk
>>> parsed = corpus.parse(speaker_segmentation = True)
:param corenlppath: folder containing corenlp jar files
:type corenlppath: str
:param operations: which kinds of annotations to do
:type operations: str
:param speaker_segmentation: add speaker name to parser output if your corpus is script-like:
:type speaker_segmentation: bool
:param memory_mb: Amount of memory in MB for parser
:type memory_mb: int
:param copula_head: Make copula head in dependency parse
:type copula_head: bool
:returns: The newly created :class:`corpkit.corpus.Corpus`
"""
from make import make_corpus
from corpus import Corpus
#from process import determine_datatype
#dtype, singlefile = determine_datatype(self.path)
if self.datatype != 'plaintext':
raise ValueError('parse method can only be used on plaintext corpora.')
kwargs.pop('parse', None)
kwargs.pop('tokenise', None)
return Corpus(make_corpus(self.path, parse = True, tokenise = False,
corenlppath = corenlppath, operations = operations, copula_head = copula_head,
speaker_segmentation = speaker_segmentation, memory_mb = memory_mb, *args, **kwargs))
def tokenise(self, *args, **kwargs):
"""
Tokenise a plaintext corpus, saving to disk
:param nltk_data_path: path to tokeniser if not found automatically
:type nltk_data_path: str
:Example:
>>> tok = corpus.tokenise()
>>> tok
<corpkit.corpus.Corpus instance: speeches-tokenised; 9 subcorpora>
:returns: The newly created :class:`corpkit.corpus.Corpus`
"""
from corpkit import make_corpus
from corpus import Corpus
#from process import determine_datatype
#dtype, singlefile = determine_datatype(self.path)
if self.datatype != 'plaintext':
raise ValueError('parse method can only be used on plaintext corpora.')
kwargs.pop('parse', None)
kwargs.pop('tokenise', None)
return Corpus(make_corpus(self.path, parse = False, tokenise = True, *args, **kwargs))
def tokenise(self, *args, **kwargs):
"""
Tokenise a plaintext corpus, saving to disk
:param nltk_data_path: path to tokeniser if not found automatically
:type nltk_data_path: str
:Example:
>>> tok = corpus.tokenise()
>>> tok
<corpkit.corpus.Corpus instance: speeches-tokenised; 9 subcorpora>
:returns: The newly created :class:`corpkit.corpus.Corpus`
"""
from corpkit import make_corpus
from corpus import Corpus
#from process import determine_datatype
#dtype, singlefile = determine_datatype(self.path)
if self.datatype != 'plaintext':
raise ValueError(
'parse method can only be used on plaintext corpora.')
kwargs.pop('parse', None)
kwargs.pop('tokenise', None)
return Corpus(
make_corpus(self.path, parse=False, tokenise=True, *args,
**kwargs))
def parse(self,
corenlppath=False,
operations=False,
copula_head=True,
speaker_segmentation=False,
memory_mb=False,
*args,
**kwargs):
"""
Parse an unparsed corpus, saving to disk
:param corenlppath: folder containing corenlp jar files
:type corenlppath: str
:param operations: which kinds of annotations to do
:type operations: str
:param speaker_segmentation: add speaker name to parser output if your corpus is script-like:
:type speaker_segmentation: bool
:param memory_mb: Amount of memory in MB for parser
:type memory_mb: int
:param copula_head: Make copula head in dependency parse
:type copula_head: bool
:Example:
>>> parsed = corpus.parse(speaker_segmentation = True)
>>> parsed
<corpkit.corpus.Corpus instance: speeches-parsed; 9 subcorpora>
:returns: The newly created :class:`corpkit.corpus.Corpus`
"""
from make import make_corpus
from corpus import Corpus
#from process import determine_datatype
#dtype, singlefile = determine_datatype(self.path)
if self.datatype != 'plaintext':
raise ValueError(
'parse method can only be used on plaintext corpora.')
kwargs.pop('parse', None)
kwargs.pop('tokenise', None)
return Corpus(
make_corpus(self.path,
parse=True,
tokenise=False,
corenlppath=corenlppath,
operations=operations,
copula_head=copula_head,
speaker_segmentation=speaker_segmentation,
memory_mb=memory_mb,
*args,
**kwargs))
def tokenise(self, *args, **kwargs):
"""
Tokenise a plaintext corpus, saving to disk
>>> tok = corpus.tokenise()
:param nltk_data_path: path to tokeniser if not found automatically
:type nltk_data_path: str
:returns: The newly created :class:`corpkit.corpus.Corpus`
"""
from corpkit import make_corpus
from corpus import Corpus
# from process import determine_datatype
# dtype, singlefile = determine_datatype(self.path)
if self.datatype != "plaintext":
raise ValueError("parse method can only be used on plaintext corpora.")
kwargs.pop("parse", None)
kwargs.pop("tokenise", None)
return Corpus(make_corpus(self.path, parse=False, tokenise=True, *args, **kwargs))