def hazmtoalpheios(word,uri):
wordslist = etree.Element("words")
normalizer = Normalizer()
data = normalizer.normalize(word)
sentences = sent_tokenize(data)
words = []
for sentence in sentences:
if words:
words = words.append(word_tokenize(sentence))
else:
words = word_tokenize(sentence)
analyses = []
for item in words:
stemmer = Stemmer()
wordstem = stemmer.stem(item)
lemmatizer = Lemmatizer()
wordlema = lemmatizer.lemmatize(item)
if '#' in wordlema:
worldleam, garbage = wordlema.split("#")
tagger = POSTagger(model=os.path.join(model_path,"postagger.model"))
wordtagged = tagger.tag(item)
wordpofs = wordtagged[0][1]
wordpofs = maptohazm(wordpofs)
# a better way to do this would be to create a Python class
# to formalize the abstraction
analysis = {}
analysis['engine'] = 'hazm'
analysis['uri'] = uri
analysis['form'] = {}
analysis['form']['text'] = item
analysis['form']['lang'] = 'per'
analysis['entries'] = []
entry = {}
entry['dict'] = {}
entry['dict']['hdwd'] = {}
entry['dict']['hdwd']['lang'] = 'per'
entry['dict']['hdwd']['text'] = wordstem
entry['infls'] = []
infl = {}
infl['stem'] = {}
infl['stem']['text'] = wordstem
infl['stem']['lang'] = 'per'
infl['pofs'] = {}
if wordpofs:
infl['pofs']['order'] = str(wordpofs[1])
infl['pofs']['text'] = wordpofs[0]
entry['infls'].append(infl)
analysis['entries'].append(entry)
analyses.append(analysis)
return analyses
def lookup(self,
word=None,
word_uri=None,
language=None,
request_args=None,
**kwargs):
""" Word Lookup Function
:param word: the word to lookup
:type word: str
:param word_uri: a uri for the word
:type word_uri: str
:param language: the language code for the word
:type language: str
:param request_args: dict of engine specific request arguments
:type request_args: dict
:return: the analysis
:rtype: str
"""
normalizer = Normalizer()
item = normalizer.normalize(word)
analyses = []
stemmer = Stemmer()
wordstem = stemmer.stem(item)
wordtagged = self.tagger.tag(word_tokenize(item))
wordpofs = wordtagged[0][1]
wordpofs = self.maptohazm(wordpofs)
analysis = {}
analysis['entries'] = []
entry = {}
entry['dict'] = {}
entry['dict']['hdwd'] = {}
entry['dict']['hdwd']['lang'] = 'per'
entry['dict']['hdwd']['text'] = wordstem
entry['infls'] = []
infl = {}
infl['stem'] = {}
infl['stem']['text'] = wordstem
infl['stem']['lang'] = 'per'
infl['pofs'] = {}
if wordpofs:
infl['pofs']['order'] = str(wordpofs[1])
infl['pofs']['text'] = wordpofs[0]
entry['infls'].append(infl)
analysis['entries'].append(entry)
analyses.append(analysis)
return self.toalpheiosxml(analyses)
def hazmtoalpheios(word,uri):
wordslist = etree.Element("words")
normalizer = Normalizer()
item = normalizer.normalize(word)
analyses = []
stemmer = Stemmer()
wordstem = stemmer.stem(item)
lemmatizer = Lemmatizer()
wordlema = lemmatizer.lemmatize(item)
if '#' in wordlema:
worldleam, garbage = wordlema.split("#")
tagger = POSTagger(model=os.path.join(model_path,"postagger.model"))
wordtagged = tagger.tag(word_tokenize(item))
wordpofs = wordtagged[0][1]
wordpofs = maptohazm(wordpofs)
# a better way to do this would be to create a Python class
# to formalize the abstraction
analysis = {}
analysis['engine'] = 'hazm'
analysis['uri'] = uri
analysis['form'] = {}
analysis['form']['text'] = item
analysis['form']['lang'] = 'per'
analysis['entries'] = []
entry = {}
entry['dict'] = {}
entry['dict']['hdwd'] = {}
entry['dict']['hdwd']['lang'] = 'per'
entry['dict']['hdwd']['text'] = wordstem
entry['infls'] = []
infl = {}
infl['stem'] = {}
infl['stem']['text'] = wordstem
infl['stem']['lang'] = 'per'
infl['pofs'] = {}
if wordpofs:
infl['pofs']['order'] = str(wordpofs[1])
infl['pofs']['text'] = wordpofs[0]
entry['infls'].append(infl)
analysis['entries'].append(entry)
analyses.append(analysis)
return analyses
def hazmtoalpheiosfile(data,uri):
root = etree.Element("{http://www.w3.org/1999/02/22-rdf-syntax-ns#}RDF")
oaannotation = etree.SubElement(root,'{http://www.w3.org/ns/oa#}Annotation',{'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}about':'http://services.projectbamboo.org/morphology'+uri})
oahasbody = etree.SubElement(oaannotation, '{http://www.w3.org/ns/oa#}hasBody',)
oahastarget = etree.SubElement(oaannotation,'{http://www.w3.org/ns/oa#}hasTarget')
hasbodydesc = etree.SubElement(oahastarget,'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}Description',{'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}about':uri})
ispartof = etree.SubElement(hasbodydesc,'{http://purl.org/dc/terms/}isPartOf',{'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}about':uri})
source = etree.SubElement(hasbodydesc,'{http://purl.org/dc/terms/}source',{'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}resource':uri})
title = etree.SubElement(oaannotation, '{http://purl.org/dc/elements/1.1/}title', {'{http://www.w3.org/XML/1998/namespace}lang':'eng'})
title.text = "Morphology of " + uri
wordslist = etree.SubElement("words")
normalizer = Normalizer()
data = normalizer.normalize(data)
sentences = sent_tokenize(data)
words = []
for sentence in sentences:
if words:
words = words.append(word_tokenize(sentence))
else:
words = word_tokenize(sentence)
for item in words:
stemmer = Stemmer()
wordstem = stemmer.stem(item)
lemmatizer = Lemmatizer()
wordlema = lemmatizer.lemmatize(item)
if '#' in wordlema:
worldleam, garbage = wordlema.split("#")
tagger = POSTagger(model=os.path.join(model_path,"postagger.model"))
wordtagged = tagger.tag(item)
wordpofs = wordtagged[0][1]
word = etree.SubElement(wordslist,'word')
form = etree.SubElement(word, 'form', {'{http://www.w3.org/XML/1998/namespace}lang':'per'})
form.text = item
entry = etree.SubElement(word, 'entry')
infl = etree.SubElement(entry,'inlf')
term = etree.SubElement(infl, 'term', {'{http://www.w3.org/XML/1998/namespace}lang':'per'})
stem = etree.SubElement(term, 'stem')
stem.text = wordstem
pofs = etree.SubElement(infl, 'pofs')
pofs.text = wordpofs
return root
def hazmtoalpheiosfile(data,uri):
root = etree.Element("{http://www.w3.org/1999/02/22-rdf-syntax-ns#}RDF")
oaannotation = etree.SubElement(root,'{http://www.w3.org/ns/oa#}Annotation',{'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}about':'http://services.projectbamboo.org/morphology'+uri})
oahasbody = etree.SubElement(oaannotation, '{http://www.w3.org/ns/oa#}hasBody',)
oahastarget = etree.SubElement(oaannotation,'{http://www.w3.org/ns/oa#}hasTarget')
hasbodydesc = etree.SubElement(oahastarget,'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}Description',{'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}about':uri})
ispartof = etree.SubElement(hasbodydesc,'{http://purl.org/dc/terms/}isPartOf',{'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}about':uri})
source = etree.SubElement(hasbodydesc,'{http://purl.org/dc/terms/}source',{'{http://www.w3.org/1999/02/22-rdf-syntax-ns#}resource':uri})
title = etree.SubElement(oaannotation, '{http://purl.org/dc/elements/1.1/}title', {'{http://www.w3.org/XML/1998/namespace}lang':'eng'})
title.text = "Morphology of " + uri
wordslist = etree.SubElement("words")
normalizer = Normalizer()
data = normalizer.normalize(data)
sentences = sent_tokenize(data)
words = []
for sentence in sentences:
if words:
words = words.append(word_tokenize(sentence))
else:
words = word_tokenize(sentence)
for item in words:
stemmer = Stemmer()
wordstem = stemmer.stem(item)
lemmatizer = Lemmatizer()
wordlema = lemmatizer.lemmatize(item)
if '#' in wordlema:
worldleam, garbage = wordlema.split("#")
tagger = POSTagger(model=os.path.join(model_path,"postagger.model"))
wordtagged = tagger.tag(item)
wordpofs = wordtagged[0][1]
word = etree.SubElement(wordslist,'word')
form = etree.SubElement(word, 'form', {'{http://www.w3.org/XML/1998/namespace}lang':'per'})
form.text = item
entry = etree.SubElement(word, 'entry')
infl = etree.SubElement(entry,'inlf')
term = etree.SubElement(infl, 'term', {'{http://www.w3.org/XML/1998/namespace}lang':'per'})
stem = etree.SubElement(term, 'stem')
stem.text = wordstem
pofs = etree.SubElement(infl, 'pofs')
pofs.text = wordpofs
return root