def test_chunker(): G = kb_services.load_semantic_network() #print G.nodes() sentence = "find the door on the right" compound_words = kb_services.compound_words(G) #print "compound nons : ", compound_words for each in compound_words: test = re.sub('_', ' ', each) sentence = re.sub(test, each, sentence) words, ranked_tags = pos_tagger(G, sentence) print words print ranked_tags[0] pp_interpretation = constituent_chunker(grammar_np_simple, words, ranked_tags[0]) print "chunked words: ", pp_interpretation[1] print "noun phrases: ", pp_interpretation[2] #test_ontology_word_mapping() #test_pos() #test_disambiguity() #test_cyk() #test_chunker()
def ontology_words_mapping(sentence): # simple preprocessing of utterance substitution of key words, phrases and compound words G = kb_services.load_semantic_network() language_info = kb_services.language_info() sentence = sentence.lower() # substitutes pronoun me for speaker (later should use contextual info of robot, who is talking?) sentence = re.sub(' me ', ' speaker ', sentence) sentence = re.sub('\?', ' ?', sentence) sentence = re.sub('pick up ', 'take ', sentence) sentence = re.sub(' ', ' ', sentence) sentence = re.sub('\.', '', sentence) sentence = re.sub(', ', ' ', sentence) sentence = re.sub(' $', '', sentence) sentence = re.sub(' one ', ' 1 ', sentence) sentence = re.sub(' two ', ' 2 ', sentence) sentence = re.sub(' three ', ' 3 ', sentence) sentence = re.sub(' four ', ' 4 ', sentence) sentence = re.sub(' five ', ' 5 ', sentence) sentence = re.sub(' other ', ' ', sentence) sentence = re.sub(' that is ', ' that_is ', sentence) sentence = re.sub(' from ', ' that_is above ', sentence) sentence = re.sub(' from top of ', ' that_is above ', sentence) sentence = re.sub(' placed on ', ' that_is above ', sentence) sentence = re.sub(' off ', ' that_is above ', sentence) sentence = re.sub(' which is ', ' that_is ', sentence) sentence = re.sub(' exactly down', ' down', sentence) sentence = re.sub(' most left ', ' leftmost ', sentence) # declaration of classes and objects sentence = re.sub('((is)|(are)) ((an object of)|(an instance of)|(an adjetive of))( a)? ', 'is is_object_of ', sentence) sentence = re.sub('((is)|(are)) ((a kind of)|(a sort of)) ', 'is is_kind_of ', sentence) # simple from of verbs sentence = re.sub(' ((is)|(are)) ', ' is ', sentence) # transform plural into singular #for each in language_info['noun']: # plural = derive_plural(each) # sentence = re.sub(plural, each, sentence) # unite compound words compound_words = kb_services.compound_words(G) for each in compound_words: test = re.sub('_', ' ', each) sentence = re.sub(test, each, sentence) #print "de aqui debo sustituir aka: ", sentence words = sentence.split(' ') new_sentence = [] for each in words: new_sentence.append(kb_services.find_original_aka(G, each)) new_sentence = " ".join(new_sentence) return new_sentence
def ontology_words_mapping(sentence): # simple preprocessing of utterance substitution of key words, phrases and compound words G = kb_services.load_semantic_network() language_info = kb_services.language_info() sentence = sentence.lower() # substitutes pronoun me for speaker (later should use contextual info of robot, who is talking?) sentence = re.sub(' me ', ' speaker ', sentence) sentence = re.sub('\?', ' ?', sentence) sentence = re.sub('pick up ', 'take ', sentence) sentence = re.sub(' ', ' ', sentence) sentence = re.sub('\.', '', sentence) sentence = re.sub(', ', ' ', sentence) sentence = re.sub(' $', '', sentence) sentence = re.sub(' one ', ' 1 ', sentence) sentence = re.sub(' two ', ' 2 ', sentence) sentence = re.sub(' three ', ' 3 ', sentence) sentence = re.sub(' four ', ' 4 ', sentence) sentence = re.sub(' five ', ' 5 ', sentence) sentence = re.sub(' other ', ' ', sentence) sentence = re.sub(' that is ', ' that_is ', sentence) sentence = re.sub(' from ', ' that_is above ', sentence) sentence = re.sub(' from top of ', ' that_is above ', sentence) sentence = re.sub(' placed on ', ' that_is above ', sentence) sentence = re.sub(' off ', ' that_is above ', sentence) sentence = re.sub(' which is ', ' that_is ', sentence) sentence = re.sub(' exactly down', ' down', sentence) sentence = re.sub(' most left ', ' leftmost ', sentence) # declaration of classes and objects sentence = re.sub( '((is)|(are)) ((an object of)|(an instance of)|(an adjetive of))( a)? ', 'is is_object_of ', sentence) sentence = re.sub('((is)|(are)) ((a kind of)|(a sort of)) ', 'is is_kind_of ', sentence) # simple from of verbs sentence = re.sub(' ((is)|(are)) ', ' is ', sentence) # transform plural into singular #for each in language_info['noun']: # plural = derive_plural(each) # sentence = re.sub(plural, each, sentence) # unite compound words compound_words = kb_services.compound_words(G) for each in compound_words: test = re.sub('_', ' ', each) sentence = re.sub(test, each, sentence) #print "de aqui debo sustituir aka: ", sentence words = sentence.split(' ') new_sentence = [] for each in words: new_sentence.append(kb_services.find_original_aka(G, each)) new_sentence = " ".join(new_sentence) return new_sentence
def ontology_words_mapping(sentence): # simple preprocessing of utterance substitution of key words, phrases and compound words G = kb_services.load_semantic_network() language_info = kb_services.language_info() sentence = sentence.lower() # substitutes pronoun me for speaker (later should use contextual info of robot, who is talking?) #sentence = re.sub(' me ', ' speaker ', sentence) sentence = re.sub('\?', ' ?', sentence) sentence = re.sub('pick up ', 'take ', sentence) sentence = re.sub('-', '_', sentence) sentence = re.sub(' ', ' ', sentence) sentence = re.sub('\.', '', sentence) sentence = re.sub(', ', ' ', sentence) sentence = re.sub(' $', '', sentence) sentence = re.sub("'", ' ', sentence) sentence = re.sub(' one ', ' 1 ', sentence) sentence = re.sub(' two ', ' 2 ', sentence) sentence = re.sub(' three ', ' 3 ', sentence) sentence = re.sub(' four ', ' 4 ', sentence) sentence = re.sub(' five ', ' 5 ', sentence) sentence = re.sub(' other ', ' ', sentence) sentence = re.sub(' person ', ' man ', sentence) sentence = re.sub(' which is ', ' that_is ', sentence) sentence = re.sub(' exactly down', ' down', sentence) sentence = re.sub('search for ', 'search_for ', sentence) sentence = re.sub('look for', 'look_for', sentence) sentence = re.sub('middle bottom', 'middle_bottom', sentence) #Montral special objects names sentence = re.sub('bathroom s cabinet', 'bathroom_s_cabinet', sentence) sentence = re.sub('(could|can|would) you (please )?(robot )?', '', sentence) sentence = re.sub('please (robot )?', '', sentence) # declaration of classes and objects sentence = re.sub('((is)|(are)) ((an object of)|(an instance of)|(an adjetive of))( a)? ', 'is is_object_of ', sentence) sentence = re.sub('((is)|(are)) ((a kind of)|(a sort of)) ', 'is is_kind_of ', sentence) # simple from of verbs sentence = re.sub(' ((is)|(are)) ', ' is ', sentence) # transform plural into singular #for each in language_info['noun']: # plural = derive_plural(each) # sentence = re.sub(plural, each, sentence) # unite compound words compound_words = kb_services.compound_words(G) #print "compound nons : ", compound_words for each in compound_words: test = re.sub('_', ' ', each) sentence = re.sub(test, each, sentence) #print "de aqui debo sustituir aka: ", sentence words = sentence.split(' ') new_sentence = [] for each in words: new_sentence.append(kb_services.find_original_aka(G, each)) #print "palabra: ",each, " se sustituye por: ", kb_services.find_original_aka(G, each) new_sentence = " ".join(new_sentence) return new_sentence
def ontology_words_mapping(sentence): # simple preprocessing of utterance substitution of key words, phrases and compound words G = kb_services.load_semantic_network() language_info = kb_services.language_info() sentence = sentence.lower() # substitutes pronoun me for speaker (later should use contextual info of robot, who is talking?) #sentence = re.sub(' me ', ' speaker ', sentence) sentence = re.sub('\?', ' ?', sentence) sentence = re.sub('pick up ', 'take ', sentence) sentence = re.sub('robot ', '', sentence) sentence = re.sub(' ', ' ', sentence) sentence = re.sub('\.', '', sentence) sentence = re.sub(', ', ' ', sentence) sentence = re.sub(' $', '', sentence) sentence = re.sub(' one ', ' 1 ', sentence) sentence = re.sub(' two ', ' 2 ', sentence) sentence = re.sub(' three ', ' 3 ', sentence) sentence = re.sub(' four ', ' 4 ', sentence) sentence = re.sub(' five ', ' 5 ', sentence) sentence = re.sub(' other ', ' ', sentence) sentence = re.sub(' person ', ' man ', sentence) sentence = re.sub(' which is ', ' that_is ', sentence) sentence = re.sub(' exactly down', ' down', sentence) sentence = re.sub('search for', 'search_for', sentence) sentence = re.sub('look for', 'look_for', sentence) sentence = re.sub('go out', 'go_out', sentence) sentence = re.sub('get into', "get_into", sentence) sentence = re.sub("searches for", "searches_for", sentence) sentence = re.sub("pick up", "pick_up", sentence) sentence = re.sub("right of", "right_of", sentence) sentence = re.sub("left of", "left_of", sentence) sentence = re.sub("bring up", "bring_up", sentence) sentence = re.sub("right of", "right_of", sentence) sentence = re.sub("right of the", "right_of", sentence) sentence = re.sub("near of", "near_of", sentence) sentence = re.sub("near of the", "near_of", sentence) sentence = re.sub("left of", "left_of", sentence) sentence = re.sub("left of the", "left_of", sentence) sentence = re.sub("in front of", "in_front_of", sentence) sentence = re.sub("in front of the", "in_front_of", sentence) sentence = re.sub("in front", "in_front", sentence) sentence = re.sub("to the front of", "in_front_of", sentence) sentence = re.sub("to the front of the", "in_front_of", sentence) sentence = re.sub("behind of", "behind_of", sentence) sentence = re.sub("behind of the", "behind_of", sentence) sentence = re.sub("next to", "next_to", sentence) sentence = re.sub("next to the", "next_to", sentence) sentence = re.sub("i want", "next_to", sentence) sentence = re.sub("i need", "next_to", sentence) sentence = re.sub("next to the", "next_to", sentence) sentence = re.sub("bottle of", "bottle", sentence) #sentence = re.sub("follow me", "follow_me", sentence) sentence = re.sub("at corner", "at_corner", sentence) sentence = re.sub("at corner of", "at_corner_of", sentence) sentence = re.sub("at end", "at_end", sentence) sentence = re.sub("at end of", "at_end_of", sentence) sentence = re.sub('(could|can|would) you (please )?(robot )?', '', sentence) #sentence = re.sub('', '', sentence) sentence = re.sub('please (robot )?', '', sentence) # declaration of classes and objects sentence = re.sub('((is)|(are)) ((an object of)|(an instance of)|(an adjetive of))( a)? ', 'is is_object_of ', sentence) sentence = re.sub('((is)|(are)) ((a kind of)|(a sort of)) ', 'is is_kind_of ', sentence) # simple from of verbs sentence = re.sub(' ((is)|(are)) ', ' is ', sentence) # transform plural into singular #for each in language_info['noun']: # plural = derive_plural(each) # sentence = re.sub(plural, each, sentence) # unite compound words compound_words = kb_services.compound_words(G) #print "compound nons : ", compound_words for each in compound_words: test = re.sub('_', ' ', each) sentence = re.sub(test, each, sentence) #print "de aqui debo sustituir aka: ", sentence words = sentence.split(' ') new_sentence = [] for each in words: new_sentence.append(kb_services.find_original_aka(G, each)) #print "palabra: ",each, " se sustituye por: ", kb_services.find_original_aka(G, each) new_sentence = " ".join(new_sentence) return new_sentence
def ontology_words_mapping(sentence): # simple preprocessing of utterance substitution of key words, phrases and compound words G = kb_services.load_semantic_network() language_info = kb_services.language_info() sentence = sentence.lower() # substitutes pronoun me for speaker (later should use contextual info of robot, who is talking?) #sentence = re.sub(' me ', ' speaker ', sentence) sentence = re.sub('\?', ' ?', sentence) sentence = re.sub('pick up ', 'take ', sentence) sentence = re.sub('robot ', '', sentence) sentence = re.sub(' ', ' ', sentence) sentence = re.sub('\.', '', sentence) sentence = re.sub(', ', ' ', sentence) sentence = re.sub(' $', '', sentence) sentence = re.sub(' one ', ' 1 ', sentence) sentence = re.sub(' two ', ' 2 ', sentence) sentence = re.sub(' three ', ' 3 ', sentence) sentence = re.sub(' four ', ' 4 ', sentence) sentence = re.sub(' five ', ' 5 ', sentence) sentence = re.sub(' other ', ' ', sentence) sentence = re.sub(' person ', ' man ', sentence) sentence = re.sub(' which is ', ' that_is ', sentence) sentence = re.sub(' exactly down', ' down', sentence) sentence = re.sub('search for', 'search_for', sentence) sentence = re.sub('look for', 'look_for', sentence) sentence = re.sub('go out', 'go_out', sentence) sentence = re.sub('get into', "get_into", sentence) sentence = re.sub("searches for", "searches_for", sentence) sentence = re.sub("pick up", "pick_up", sentence) sentence = re.sub("right of", "right_of", sentence) sentence = re.sub("left of", "left_of", sentence) sentence = re.sub("bring up", "bring_up", sentence) sentence = re.sub("right of", "right_of", sentence) sentence = re.sub("right of the", "right_of", sentence) sentence = re.sub("near of", "near_of", sentence) sentence = re.sub("near of the", "near_of", sentence) sentence = re.sub("left of", "left_of", sentence) sentence = re.sub("left of the", "left_of", sentence) sentence = re.sub("in front of", "in_front_of", sentence) sentence = re.sub("in front of the", "in_front_of", sentence) sentence = re.sub("in front", "in_front", sentence) sentence = re.sub("to the front of", "in_front_of", sentence) sentence = re.sub("to the front of the", "in_front_of", sentence) sentence = re.sub("behind of", "behind_of", sentence) sentence = re.sub("behind of the", "behind_of", sentence) sentence = re.sub("next to", "next_to", sentence) sentence = re.sub("next to the", "next_to", sentence) sentence = re.sub("i want", "next_to", sentence) sentence = re.sub("i need", "next_to", sentence) sentence = re.sub("next to the", "next_to", sentence) sentence = re.sub("bottle of", "bottle", sentence) #sentence = re.sub("follow me", "follow_me", sentence) sentence = re.sub("at corner", "at_corner", sentence) sentence = re.sub("at corner of", "at_corner_of", sentence) sentence = re.sub("at end", "at_end", sentence) sentence = re.sub("at end of", "at_end_of", sentence) sentence = re.sub('(could|can|would) you (please )?(robot )?', '', sentence) #sentence = re.sub('', '', sentence) sentence = re.sub('please (robot )?', '', sentence) # declaration of classes and objects sentence = re.sub( '((is)|(are)) ((an object of)|(an instance of)|(an adjetive of))( a)? ', 'is is_object_of ', sentence) sentence = re.sub('((is)|(are)) ((a kind of)|(a sort of)) ', 'is is_kind_of ', sentence) # simple from of verbs sentence = re.sub(' ((is)|(are)) ', ' is ', sentence) # transform plural into singular #for each in language_info['noun']: # plural = derive_plural(each) # sentence = re.sub(plural, each, sentence) # unite compound words compound_words = kb_services.compound_words(G) #print "compound nons : ", compound_words for each in compound_words: test = re.sub('_', ' ', each) sentence = re.sub(test, each, sentence) #print "de aqui debo sustituir aka: ", sentence words = sentence.split(' ') new_sentence = [] for each in words: new_sentence.append(kb_services.find_original_aka(G, each)) #print "palabra: ",each, " se sustituye por: ", kb_services.find_original_aka(G, each) new_sentence = " ".join(new_sentence) return new_sentence