def stemming_stopword(self, word):
"""
Analyze word morphologically as noun
@param word: the input word.
@type word: unicode.
@return: list of dictionaries of analyzed words with tags.
@rtype: list.
"""
# the detailled stemmming result
detailed_result=[];
# search the sw in the dictionary
# we can return the tashkeel
#list of IDs of found stopwords in dictionary
swIdList = [];
# search in database by word, and return all ids
#word = araby.stripTashkeel(word);
swIdList = self.swDictionary.lookup(word);
for sw_tuple in swIdList:
# sw_tuple = self.swDictionary.getEntryById(id);
detailed_result.append(wordCase.wordCase({
'word': word,
'affix': (sw_tuple['procletic'],
'',
'',
sw_tuple['encletic']),
'stem': sw_tuple['stem'],
'original': sw_tuple['original'],
'vocalized': sw_tuple['vocalized'],
'tags': sw_tuple['tags'],
'type': sw_tuple['type'],
'freq':'freqstopword',
'originaltags':sw_tuple['tags'],
'syntax':'',
}));
return detailed_result;
def check_word(self,word, guessedTag=""):
"""
Analyze one word morphologically as verbs
@param word: the input word.
@type word: unicode.
@return: list of dictionaries of analyzed words with tags.
@rtype: list.
"""
word=araby.stripTatweel(word);
word_vocalised=word;
word_nm=araby.stripTashkeel(word);
resulted_text=u"";
resulted_data=[];
# if word is a pounctuation
resulted_data+=self.check_word_as_pounct(word_nm);
# Done: if the word is a stop word we have some problems,
# the stop word can also be another normal word (verb or noun),
# we must consider it in future works
# if word is stopword allow stop words analysis
resulted_data+=self.check_word_as_stopword(word_nm);
#if word is verb
# مشكلة بعض الكلمات المستبعدة تعتبر أفعلا أو اسماء
if self.tagger.hasVerbTag(guessedTag) or self.tagger.isStopWordTag(guessedTag):
resulted_data+=self.check_word_as_verb(word_nm);
#print "is verb", rabti,len(resulted_data);
#if word is noun
if self.tagger.hasNounTag(guessedTag) or self.tagger.isStopWordTag(guessedTag):
resulted_data+=self.check_word_as_noun(word_nm);
if len(resulted_data)==0:
#check the word as unkonwn
resulted_data+=self.check_word_as_unknown(word_nm);
#check if the word is nomralized and solution are equivalent
resulted_data = self.check_normalized(word_vocalised, resulted_data)
#check if the word is shadda like
resulted_data = self.check_shadda(word_vocalised, resulted_data)
#check if the word is vocalized like results
if self.partial_vocalization_support:
resulted_data=self.check_partial_vocalized(word_vocalised, resulted_data);
# add word frequency information in tags
resulted_data = self.addWordFrequency(resulted_data);
if len(resulted_data)==0:
resulted_data.append(wordCase.wordCase({
'word':word,
'affix': ('' , '', '', ''),
'stem':'',
'original':word,
'vocalized':word,
'tags':u'',
'type':'unknown',
'root':'',
'template':'',
'freq':self.wordfreq.getFreq(word, 'unknown'),
'syntax':'',
})
);
return resulted_data;
def check_word_as_pounct(self, word):
"""
Check if the word is a pounctuation,
@param word: the input word.
@type word: unicode.
@return: list of dictionaries of analyzed words with tags.
@rtype: list.
"""
detailed_result = []
# ToDo : fix it to isdigit, by moatz saad
if word.isnumeric():
detailed_result.append(
wordCase.wordCase({
'word': word,
'affix': ('', '', '', ''),
'stem': '',
'original': word,
'vocalized': word,
'tags': self.get_number_tags(word),
'type': 'NUMBER',
'freq': 0,
'syntax': '',
}))
if word in stem_pounct_const.POUNCTUATION:
detailed_result.append(
wordCase.wordCase({
'word':
word,
'affix': ('', '', '', ''),
'stem':
'',
'original':
word,
'vocalized':
word,
'tags':
stem_pounct_const.POUNCTUATION[word]['tags'],
'type':
'POUNCT',
'freq':
0,
'syntax':
'',
}))
return detailed_result
def check_word_as_pounct(self, word):
"""
Check if the word is a pounctuation,
@param word: the input word.
@type word: unicode.
@return: list of dictionaries of analyzed words with tags.
@rtype: list.
"""
detailed_result = []
# ToDo : fix it to isdigit, by moatz saad
if word.isnumeric():
detailed_result.append(
wordCase.wordCase(
{
"word": word,
"affix": ("", "", "", ""),
"stem": "",
"original": word,
"vocalized": word,
"tags": self.get_number_tags(word),
"type": "NUMBER",
"freq": 0,
"syntax": "",
}
)
)
if word in stem_pounct_const.POUNCTUATION:
detailed_result.append(
wordCase.wordCase(
{
"word": word,
"affix": ("", "", "", ""),
"stem": "",
"original": word,
"vocalized": word,
"tags": stem_pounct_const.POUNCTUATION[word]["tags"],
"type": "POUNCT",
"freq": 0,
"syntax": "",
}
)
)
return detailed_result
def check_word_as_pounct(self,word):
"""
Check if the word is a pounctuation,
@param word: the input word.
@type word: unicode.
@return: list of dictionaries of analyzed words with tags.
@rtype: list.
"""
detailed_result=[]
# ToDo : fix it to isdigit, by moatz saad
if word.isnumeric():
detailed_result.append(wordCase.wordCase({
'word':word,
'affix': ('', '', '', ''),
'stem':'',
'original':word,
'vocalized':word,
'tags':self.get_number_tags(word),
'type':'NUMBER',
'freq':0,
'syntax':'',
}));
if word in stem_pounct_const.POUNCTUATION:
detailed_result.append(wordCase.wordCase({
'word':word,
'affix': ('', '', '', ''),
'stem':'',
'original':word,
'vocalized':word,
'tags':stem_pounct_const.POUNCTUATION[word]['tags'],
'type':'POUNCT',
'freq':0,
'syntax':'',
}));
return detailed_result;
def stemming_stopword(self, word):
"""
Analyze word morphologically as noun
@param word: the input word.
@type word: unicode.
@return: list of dictionaries of analyzed words with tags.
@rtype: list.
"""
# the detailled stemmming result
detailed_result = []
# search the sw in the dictionary
# we can return the tashkeel
# list of IDs of found stopwords in dictionary
swIdList = []
# search in database by word, and return all ids
# word = araby.stripTashkeel(word);
swIdList = self.swDictionary.lookup(word)
for sw_tuple in swIdList:
# sw_tuple = self.swDictionary.getEntryById(id);
detailed_result.append(
wordCase.wordCase(
{
"word": word,
"affix": (sw_tuple["procletic"], "", "", sw_tuple["encletic"]),
"stem": sw_tuple["stem"],
"original": sw_tuple["original"],
"vocalized": sw_tuple["vocalized"],
"tags": sw_tuple["tags"],
"type": sw_tuple["type"],
"freq": "freqstopword",
"originaltags": sw_tuple["tags"],
"syntax": "",
}
)
)
return detailed_result
def steming_second_level(self, noun, noun2, procletic, encletic):
"""
Analyze word morphologically by stemming the conjugation affixes.
@param noun: the input noun.
@type noun: unicode.
@param noun2: the noun stemed from syntaxic affixes.
@type noun2: unicode.
@param procletic: the syntaxic prefixe extracted in the fisrt stage.
@type procletic: unicode.
@param encletic: the syntaxic suffixe extracted in the fisrt stage.
@type encletic: unicode.
@return: list of dictionaries of analyzed words with tags.
@rtype: list.
"""
detailed_result = []
#segment the coinjugated verb
list_seg_conj = self.conjStemmer.segment(noun2)
# verify affix compatibility
list_seg_conj = self.verify_affix(
noun2, list_seg_conj, stem_noun_const.NOMINAL_CONJUGATION_AFFIX)
# add vocalized forms of suffixes
list_seg_conj_voc = []
for seg_conj in list_seg_conj:
prefix_conj = noun2[:seg_conj[0]]
stem_conj = noun2[seg_conj[0]:seg_conj[1]]
suffix_conj = noun2[seg_conj[1]:]
affix_conj = prefix_conj + '-' + suffix_conj
# get all vocalized form of suffixes
for vocalized_suffix in stem_noun_const.CONJ_SUFFIX_LIST_TAGS[
suffix_conj]['vocalized']:
seg_conj_voc = {
'prefix': '',
'suffix': vocalized_suffix,
'stem': stem_conj
}
# verify compatibility between procletics and afix
if (self.is_compatible_proaffix_affix(procletic, encletic,
vocalized_suffix)):
# verify the existing of a noun stamp in the dictionary
# if self.NOUN_DICTIONARY_STAMP.has_key(stamp):
# list_seg_conj2.append(seg_conj)
list_seg_conj_voc.append(seg_conj_voc)
list_seg_conj = list_seg_conj_voc
for seg_conj in list_seg_conj:
prefix_conj = seg_conj['prefix']
stem_conj = seg_conj['stem']
suffix_conj = seg_conj['suffix']
has_plural_suffix = (
(u"جمع"
in stem_noun_const.CONJ_SUFFIX_LIST_TAGS[suffix_conj]['tags'])
or
(u"مثنى"
in stem_noun_const.CONJ_SUFFIX_LIST_TAGS[suffix_conj]['tags'])
)
#print "has_plural", has_plural_suffix;
affix_conj = '-'.join([prefix_conj, suffix_conj])
# noirmalize hamza before gessing deffirents origines
stem_conj = tashaphyne.normalize.normalize_hamza(stem_conj)
if self.debug:
print "*\t", "-".join(
[str(len(stem_conj)), prefix_conj, stem_conj,
suffix_conj]).encode("utf8")
# generate possible stems
# add stripped letters to the stem to constitute possible noun list
possible_noun_list = self.getStemVariants(stem_conj, prefix_conj,
suffix_conj)
if self.debug:
print "\tpossible original nouns: ", "\t".join(
possible_noun_list).encode('utf8')
# search the noun in the dictionary
# we can return the tashkeel
infnoun_form_list = []
for infnoun in possible_noun_list:
# get the noun and get all its forms from the dict
# if the noun has plural suffix, don't look up in broken plural dictionary
infnoun_foundL = self.nounDictionary.lookup(
infnoun, 'unknown')
#infnoun_found=self.find_nouns_in_dictionary(infnoun,has_plural_suffix);
## listsingle=self.find_broken_plural(infnoun);
## print ' *****','-'.join(listsingle).encode('utf8')
if len(infnoun_foundL) > 0:
if self.debug: print "\t in dict", infnoun.encode('utf8')
else:
if self.debug:
print infnoun.encode('utf8'), "not found in dictionary"
infnoun_form_list += infnoun_foundL
for noun_tuple in infnoun_form_list:
# noun_tuple=self.nounDictionary.getEntryById(id);
infnoun = noun_tuple['vocalized']
originalTags = ()
original = noun_tuple['vocalized']
wordtype = noun_tuple['word_type']
detailed_result.append(
wordCase.wordCase({
'word':
noun,
'affix':
(procletic, prefix_conj, suffix_conj, encletic),
#~ 'procletic':procletic,
#~ 'encletic':encletic,
#~ 'prefix':prefix_conj,
#~ 'suffix':suffix_conj,
'stem':
stem_conj,
'original':
infnoun, #original,
'vocalized':
self.vocalize(infnoun, procletic, prefix_conj,
suffix_conj, encletic),
'tags':
u':'.join(stem_noun_const.
COMP_PREFIX_LIST_TAGS[procletic]['tags'] +
stem_noun_const.
COMP_SUFFIX_LIST_TAGS[encletic]['tags'] +
stem_noun_const.
CONJ_SUFFIX_LIST_TAGS[suffix_conj]['tags']),
'type':
u':'.join(['Noun', wordtype]), #'Noun',
#~ 'root':'',
#~ 'template':'',
'freq':
noun_tuple[
'freq'], #self.wordfreq.getFreq(infnoun,'noun'),
'originaltags':
u':'.join(originalTags),
'syntax':
'',
}))
return detailed_result
def stemming_verb(self, verb):
list_found = [];
display_conj_result=False;
detailed_result = [];
verb = verb.strip();
verb_list = [verb];
if verb.startswith(araby.ALEF_MADDA):
verb_list.append(araby.ALEF_HAMZA_ABOVE + araby.ALEF_HAMZA_ABOVE+verb[1:])
verb_list.append(araby.HAMZA+araby.ALEF+verb[1:])
for verb in verb_list:
list_seg_comp=self.compStemmer.segment(verb);
for seg in list_seg_comp:
procletic=verb[:seg[0]];
stem=verb[seg[0]:seg[1]]
encletic=verb[seg[1]:]
secondsuffix=u'';
# حالة الفعل المتعدي لمفعولين
if stem_verb_const.TableDoubleTransitiveSuffix.has_key(encletic ):
firstsuffix=stem_verb_const.TableDoubleTransitiveSuffix[encletic]['first'];
secondsuffix=stem_verb_const.TableDoubleTransitiveSuffix[encletic]['second'];
encletic=firstsuffix;
affix = u'-'.join([procletic, encletic])
#if self.debug: print "\t", "-".join([procletic, stem, encletic]).encode("utf8") ;
# ajusting verbs variant
list_stem=[stem];
if encletic: #!="":
transitive=True;
if stem.endswith(araby.TEH + araby.MEEM + araby.WAW):
list_stem.append(stem[:-1]);
elif stem.endswith(araby.WAW):
list_stem.append(stem+ araby.ALEF);
elif stem.endswith( araby.ALEF):
list_stem.append(stem[:-1]+ araby.ALEF_MAKSURA);
else: transitive=False;
if verb.startswith(araby.ALEF_MADDA):
# االبداية بألف مد
list_stem.append(araby.ALEF_HAMZA_ABOVE + araby.ALEF_HAMZA_ABOVE+verb[1:])
list_stem.append(araby.HAMZA+ araby.ALEF+verb[1:])
# stem reduced verb : level two
result=[];
for verb2 in list_stem:
#segment the coinjugated verb
list_seg_conj=self.conjStemmer.segment(verb2);
# verify affix compatibility
list_seg_conj = self.verify_affix(verb2, list_seg_conj, stem_verb_const.VERBAL_CONJUGATION_AFFIX);
# verify procletics and enclitecs
# verify length pof stem
list_seg_conj2=[];
for seg_conj in list_seg_conj:
if (seg_conj[1] - seg_conj[0])<=6 :
prefix_conj = verb2[:seg_conj[0]];
stem_conj = verb2[seg_conj[0]:seg_conj[1]]
suffix_conj = verb2[seg_conj[1]:]
affix_conj = prefix_conj+'-'+suffix_conj;
# verify compatibility between procletics and afix
if (self.is_compatible_proaffix_affix(procletic, encletic, affix_conj)):
# verify the existing of a verb stamp in the dictionary
if self.verbDictionary.existsAsStamp(stem_conj):
list_seg_conj2.append(seg_conj)
list_seg_conj = list_seg_conj2;
list_correct_conj = [];
for seg_conj in list_seg_conj:
prefix_conj = verb2[:seg_conj[0]];
stem_conj = verb2[seg_conj[0]:seg_conj[1]]
suffix_conj = verb2[seg_conj[1]:]
affix_conj = '-'.join([prefix_conj, suffix_conj])
# search the verb in the dictionary by stamp
# if the verb exists in dictionary,
# The transitivity is consedered
# if is trilateral return its forms and Tashkeel
# if not return forms without tashkeel, because the conjugator can vocalized it,
# we can return the tashkeel if we don't need the conjugation step
infverb_dict=self.getInfinitiveVerbByStem(stem_conj, transitive);
infverb_dict = self.verifyInfinitiveVerbs(stem_conj, infverb_dict);
for item in infverb_dict:
#The haraka from is given from the dict
inf_verb = item['verb'];
haraka = item['haraka'];
transtag = item['transitive'] #=='y'or not item['transitive']);
transitive = (item['transitive']=='y'or not item['transitive']);
originalTags = transtag;
# dict tag is used to mention word dictionary tags: the original word tags like transitive attribute
unstemed_verb= verb2;
# conjugation step
# ToDo, conjugate the verb with affix,
# if exists one verb which match, return it
# تصريف الفعل مع الزوائد
# إذا توافق التصريف مع الكلمة الناتجة
# تعرض النتيجة
onelist_correct_conj = [];
onelist_correct_conj = self.generate_possible_conjug(inf_verb, unstemed_verb, affix_conj, haraka, procletic, encletic, transitive);
if len(onelist_correct_conj)>0:
list_correct_conj+=onelist_correct_conj;
# if not list_correct_conj : print "No Verb Found ";
for conj in list_correct_conj:
result.append(conj['verb'])
detailed_result.append(wordCase.wordCase({
'word':verb,
'affix': ( procletic, prefix_conj, suffix_conj, encletic),
#~ 'procletic':procletic,
#~ 'encletic':encletic,
#~ 'prefix':prefix_conj,
#~ 'suffix':suffix_conj,
'stem':stem_conj,
'original':conj['verb'],
'vocalized':self.vocalize(conj['vocalized'], procletic, encletic),
'tags':u':'.join((conj['tense'], conj['pronoun'])+stem_verb_const.COMP_PREFIX_LIST_TAGS[procletic]['tags']+stem_verb_const.COMP_SUFFIX_LIST_TAGS[encletic]['tags']),
'type':'Verb',
#~ 'root':'',
#~ 'template':'',
'freq':'freqverb',
'originaltags':originalTags,
'syntax':'',
}));
## result+=detect_arabic_verb(verb2, transitive, prefix_conj, suffix_conj, debug);
list_found+=result;
list_found=set(list_found);
return detailed_result
def steming_second_level(self,noun,noun2,procletic,encletic):
"""
Analyze word morphologically by stemming the conjugation affixes.
@param noun: the input noun.
@type noun: unicode.
@param noun2: the noun stemed from syntaxic affixes.
@type noun2: unicode.
@param procletic: the syntaxic prefixe extracted in the fisrt stage.
@type procletic: unicode.
@param encletic: the syntaxic suffixe extracted in the fisrt stage.
@type encletic: unicode.
@return: list of dictionaries of analyzed words with tags.
@rtype: list.
"""
detailed_result=[];
#segment the coinjugated verb
list_seg_conj=self.conjStemmer.segment(noun2);
# verify affix compatibility
list_seg_conj=self.verify_affix(noun2,list_seg_conj,stem_noun_const.NOMINAL_CONJUGATION_AFFIX);
# add vocalized forms of suffixes
list_seg_conj_voc=[];
for seg_conj in list_seg_conj:
prefix_conj=noun2[:seg_conj[0]];
stem_conj=noun2[seg_conj[0]:seg_conj[1]]
suffix_conj=noun2[seg_conj[1]:]
affix_conj=prefix_conj+'-'+suffix_conj;
# get all vocalized form of suffixes
for vocalized_suffix in stem_noun_const.CONJ_SUFFIX_LIST_TAGS[suffix_conj]['vocalized']:
seg_conj_voc={'prefix':'','suffix':vocalized_suffix,'stem':stem_conj}
# verify compatibility between procletics and afix
if (self.is_compatible_proaffix_affix(procletic, encletic, vocalized_suffix)):
# verify the existing of a noun stamp in the dictionary
# if self.NOUN_DICTIONARY_STAMP.has_key(stamp):
# list_seg_conj2.append(seg_conj)
list_seg_conj_voc.append(seg_conj_voc)
list_seg_conj=list_seg_conj_voc;
for seg_conj in list_seg_conj:
prefix_conj=seg_conj['prefix'];
stem_conj=seg_conj['stem']
suffix_conj=seg_conj['suffix']
has_plural_suffix=((u"جمع" in stem_noun_const.CONJ_SUFFIX_LIST_TAGS[suffix_conj]['tags']) or( u"مثنى" in stem_noun_const.CONJ_SUFFIX_LIST_TAGS[suffix_conj]['tags']))
#print "has_plural", has_plural_suffix;
affix_conj='-'.join([prefix_conj,suffix_conj])
# noirmalize hamza before gessing deffirents origines
stem_conj=tashaphyne.normalize.normalize_hamza(stem_conj)
if self.debug:
print "*\t", "-".join([str(len(stem_conj)),prefix_conj,stem_conj,suffix_conj]).encode("utf8") ;
# generate possible stems
# add stripped letters to the stem to constitute possible noun list
possible_noun_list=self.getStemVariants(stem_conj,prefix_conj,suffix_conj);
if self.debug:
print "\tpossible original nouns: ","\t".join(possible_noun_list).encode('utf8');
# search the noun in the dictionary
# we can return the tashkeel
infnoun_form_list=[];
for infnoun in possible_noun_list:
# get the noun and get all its forms from the dict
# if the noun has plural suffix, don't look up in broken plural dictionary
infnoun_foundL=self.nounDictionary.lookup(infnoun,'unknown');
#infnoun_found=self.find_nouns_in_dictionary(infnoun,has_plural_suffix);
## listsingle=self.find_broken_plural(infnoun);
## print ' *****','-'.join(listsingle).encode('utf8')
if len(infnoun_foundL)>0:
if self.debug: print "\t in dict",infnoun.encode('utf8');
else:
if self.debug: print infnoun.encode('utf8'),"not found in dictionary"
infnoun_form_list+=infnoun_foundL;
for noun_tuple in infnoun_form_list:
# noun_tuple=self.nounDictionary.getEntryById(id);
infnoun=noun_tuple['vocalized'];
originalTags=()
original=noun_tuple['vocalized'];
wordtype=noun_tuple['word_type'];
detailed_result.append(wordCase.wordCase({
'word':noun,
'affix': ( procletic,
prefix_conj,
suffix_conj,
encletic),
#~ 'procletic':procletic,
#~ 'encletic':encletic,
#~ 'prefix':prefix_conj,
#~ 'suffix':suffix_conj,
'stem':stem_conj,
'original':infnoun,#original,
'vocalized':self.vocalize(infnoun,procletic,prefix_conj,suffix_conj,encletic),
'tags':u':'.join(stem_noun_const.COMP_PREFIX_LIST_TAGS[procletic]['tags']+stem_noun_const.COMP_SUFFIX_LIST_TAGS[encletic]['tags']+stem_noun_const.CONJ_SUFFIX_LIST_TAGS[suffix_conj]['tags']),
'type':u':'.join(['Noun',wordtype]),#'Noun',
#~ 'root':'',
#~ 'template':'',
'freq':noun_tuple['freq'],#self.wordfreq.getFreq(infnoun,'noun'),
'originaltags':u':'.join(originalTags),
'syntax':'',
}));
return detailed_result;
def steming_second_level(self, noun, noun2, procletic, encletic, encletic_nm):
"""
Analyze word morphologically by stemming the conjugation affixes.
@param noun: the input noun.
@type noun: unicode.
@param noun2: the noun stemed from syntaxic affixes.
@type noun2: unicode.
@param procletic: the syntaxic prefixe extracted in the fisrt stage.
@type procletic: unicode.
@param encletic: the syntaxic suffixe extracted in the fisrt stage.
@type encletic: unicode.
@param encletic_nm: the syntaxic suffixe extracted in the fisrt stage (not vocalized).
@type encletic_nm: unicode.
@return: list of dictionaries of analyzed words with tags.
@rtype: list.
"""
detailed_result=[];
#segment the coinjugated verb
list_seg_conj = self.conjStemmer.segment(noun2);
# verify affix compatibility
list_seg_conj = self.verify_affix(noun2, list_seg_conj, stem_noun_const.NOMINAL_CONJUGATION_AFFIX);
# add vocalized forms of suffixes
# and create the real affixes from the word
list_seg_conj_voc=[];
for seg_conj in list_seg_conj:
stem_conj = noun2[seg_conj[0]:seg_conj[1]]
suffix_conj_nm = noun2[seg_conj[1]:]
# noirmalize hamza before gessing differents origines
stem_conj = araby.normalizeHamza(stem_conj)
# generate possible stems
# add stripped letters to the stem to constitute possible noun list
possible_noun_list=self.getStemVariants(stem_conj, suffix_conj_nm);
# search the noun in the dictionary
# we can return the tashkeel
infnoun_form_list=[];
for infnoun in set(possible_noun_list):
# get the noun and get all its forms from the dict
# if the noun has plural suffix, don't look up in broken plural dictionary
if not self.CacheDictSearch.has_key(infnoun):
infnoun_foundL = self.nounDictionary.lookup(infnoun);
self.CacheDictSearch[infnoun] = self.createDictWord(infnoun_foundL);
else:
infnoun_foundL = self.CacheDictSearch[infnoun] ;
infnoun_form_list.extend(infnoun_foundL);
#print "len loooked up noun in dictionnary ",len(infnoun_form_list), len(set(infnoun_form_list));
for noun_tuple in infnoun_form_list:
# noun_tuple=self.nounDictionary.getEntryById(id);
infnoun = noun_tuple['vocalized'];
# affixes tags contains prefixes and suffixes tags
affix_tags = stem_noun_const.COMP_PREFIX_LIST_TAGS[procletic]['tags'] \
+stem_noun_const.COMP_SUFFIX_LIST_TAGS[encletic_nm]['tags'] \
+stem_noun_const.CONJ_SUFFIX_LIST_TAGS[suffix_conj_nm]['tags']
#test if the given word from dictionary accept those tags given by affixes
# دراسة توافق الزوائد مع خصائص الاسم،
# مثلا هل يقبل الاسم التأنيث.
if self.validateTags(noun_tuple, affix_tags, procletic, encletic_nm, suffix_conj_nm):
## get all vocalized form of suffixes
for vocalized_encletic in stem_noun_const.COMP_SUFFIX_LIST_TAGS[encletic_nm]['vocalized']:
for vocalized_suffix in stem_noun_const.CONJ_SUFFIX_LIST_TAGS[suffix_conj_nm]['vocalized']:
## verify compatibility between procletics and affix
if (self.is_compatible_proaffix_affix(noun_tuple, procletic, vocalized_encletic, vocalized_suffix)):
vocalized, semiVocalized = self.vocalize(infnoun, procletic, vocalized_suffix, vocalized_encletic);
vocalized_affix_tags = stem_noun_const.COMP_PREFIX_LIST_TAGS[procletic]['tags'] \
+stem_noun_const.COMP_SUFFIX_LIST_TAGS[vocalized_encletic]['tags'] \
+stem_noun_const.CONJ_SUFFIX_LIST_TAGS[vocalized_suffix]['tags']
#add some tags from dictionary entry as mamnou3 min sarf and broken plural
originalTags=[];
if noun_tuple['mamnou3_sarf']==u"ممنوع من الصرف":
originalTags.append(u"ممنوع من الصرف");
if noun_tuple['number']==u"جمع تكسير":
originalTags.append(u"جمع تكسير");
# affix_tags+=(, );
detailed_result.append(wordCase.wordCase({
'word':noun,
#~ 'affix': analex_const.AffixTuple((procletic=procletic, encletic=vocalized_encletic, prefix='', suffix=vocalized_suffix)),
'affix': (procletic, '', vocalized_suffix, vocalized_encletic),
#~ 'procletic': ,
#~ 'encletic': ,
#~ 'prefix': '',
#~ 'suffix': vocalized_suffix,
'stem': stem_conj,
'original': infnoun, #original,
'vocalized': vocalized,
'semivocalized':semiVocalized,
'tags': u':'.join(vocalized_affix_tags),
'type': u':'.join(['Noun', noun_tuple['wordtype']]), #'Noun',
#~ 'root': '',
#~ 'template': '',
'freq':'freqnoun', # to note the frequency type
'originaltags':u':'.join(originalTags),
'syntax':'',
}));
return detailed_result;
def stemming_verb(self, verb):
list_found = []
display_conj_result = False
detailed_result = []
verb = verb.strip()
verb_list = [verb]
if verb.startswith(araby.ALEF_MADDA):
verb_list.append(araby.ALEF_HAMZA_ABOVE + araby.ALEF_HAMZA_ABOVE +
verb[1:])
verb_list.append(araby.HAMZA + araby.ALEF + verb[1:])
for verb in verb_list:
list_seg_comp = self.compStemmer.segment(verb)
for seg in list_seg_comp:
procletic = verb[:seg[0]]
stem = verb[seg[0]:seg[1]]
encletic = verb[seg[1]:]
secondsuffix = u''
# حالة الفعل المتعدي لمفعولين
if stem_verb_const.TableDoubleTransitiveSuffix.has_key(
encletic):
firstsuffix = stem_verb_const.TableDoubleTransitiveSuffix[
encletic]['first']
secondsuffix = stem_verb_const.TableDoubleTransitiveSuffix[
encletic]['second']
encletic = firstsuffix
affix = u'-'.join([procletic, encletic])
#if self.debug: print "\t", "-".join([procletic, stem, encletic]).encode("utf8") ;
# ajusting verbs variant
list_stem = [stem]
if encletic: #!="":
transitive = True
if stem.endswith(araby.TEH + araby.MEEM + araby.WAW):
list_stem.append(stem[:-1])
elif stem.endswith(araby.WAW):
list_stem.append(stem + araby.ALEF)
elif stem.endswith(araby.ALEF):
list_stem.append(stem[:-1] + araby.ALEF_MAKSURA)
else:
transitive = False
if verb.startswith(araby.ALEF_MADDA):
# االبداية بألف مد
list_stem.append(araby.ALEF_HAMZA_ABOVE +
araby.ALEF_HAMZA_ABOVE + verb[1:])
list_stem.append(araby.HAMZA + araby.ALEF + verb[1:])
# stem reduced verb : level two
result = []
for verb2 in list_stem:
#segment the coinjugated verb
list_seg_conj = self.conjStemmer.segment(verb2)
# verify affix compatibility
list_seg_conj = self.verify_affix(
verb2, list_seg_conj,
stem_verb_const.VERBAL_CONJUGATION_AFFIX)
# verify procletics and enclitecs
# verify length pof stem
list_seg_conj2 = []
for seg_conj in list_seg_conj:
if (seg_conj[1] - seg_conj[0]) <= 6:
prefix_conj = verb2[:seg_conj[0]]
stem_conj = verb2[seg_conj[0]:seg_conj[1]]
suffix_conj = verb2[seg_conj[1]:]
affix_conj = prefix_conj + '-' + suffix_conj
# verify compatibility between procletics and afix
if (self.is_compatible_proaffix_affix(
procletic, encletic, affix_conj)):
# verify the existing of a verb stamp in the dictionary
if self.verbDictionary.existsAsStamp(
stem_conj):
list_seg_conj2.append(seg_conj)
list_seg_conj = list_seg_conj2
list_correct_conj = []
for seg_conj in list_seg_conj:
prefix_conj = verb2[:seg_conj[0]]
stem_conj = verb2[seg_conj[0]:seg_conj[1]]
suffix_conj = verb2[seg_conj[1]:]
affix_conj = '-'.join([prefix_conj, suffix_conj])
# search the verb in the dictionary by stamp
# if the verb exists in dictionary,
# The transitivity is consedered
# if is trilateral return its forms and Tashkeel
# if not return forms without tashkeel, because the conjugator can vocalized it,
# we can return the tashkeel if we don't need the conjugation step
infverb_dict = self.getInfinitiveVerbByStem(
stem_conj, transitive)
infverb_dict = self.verifyInfinitiveVerbs(
stem_conj, infverb_dict)
for item in infverb_dict:
#The haraka from is given from the dict
inf_verb = item['verb']
haraka = item['haraka']
transtag = item[
'transitive'] #=='y'or not item['transitive']);
transitive = (item['transitive'] == 'y'
or not item['transitive'])
originalTags = transtag
# dict tag is used to mention word dictionary tags: the original word tags like transitive attribute
unstemed_verb = verb2
# conjugation step
# ToDo, conjugate the verb with affix,
# if exists one verb which match, return it
# تصريف الفعل مع الزوائد
# إذا توافق التصريف مع الكلمة الناتجة
# تعرض النتيجة
onelist_correct_conj = []
onelist_correct_conj = self.generate_possible_conjug(
inf_verb, unstemed_verb, affix_conj, haraka,
procletic, encletic, transitive)
if len(onelist_correct_conj) > 0:
list_correct_conj += onelist_correct_conj
# if not list_correct_conj : print "No Verb Found ";
for conj in list_correct_conj:
result.append(conj['verb'])
detailed_result.append(
wordCase.wordCase({
'word':
verb,
'affix': (procletic, prefix_conj, suffix_conj,
encletic),
#~ 'procletic':procletic,
#~ 'encletic':encletic,
#~ 'prefix':prefix_conj,
#~ 'suffix':suffix_conj,
'stem':
stem_conj,
'original':
conj['verb'],
'vocalized':
self.vocalize(conj['vocalized'], procletic,
encletic),
'tags':
u':'.join(
(conj['tense'], conj['pronoun']) +
stem_verb_const.
COMP_PREFIX_LIST_TAGS[procletic]['tags'] +
stem_verb_const.
COMP_SUFFIX_LIST_TAGS[encletic]['tags']),
'type':
'Verb',
#~ 'root':'',
#~ 'template':'',
'freq':
'freqverb',
'originaltags':
originalTags,
'syntax':
'',
}))
## result+=detect_arabic_verb(verb2, transitive, prefix_conj, suffix_conj, debug);
list_found += result
list_found = set(list_found)
return detailed_result
