Example #1
0
def main(senna_path="",
         sent="",
         dep_model="",
         batch=False,
         stp_dir="",
         init=False):

    annotator = Annotator(senna_path, stp_dir, dep_model)

    if not sent and batch:

        sent = [
            "He killed the man with a knife and murdered"
            "him with a dagger.",
            "He is a good boy.",
            "He created the robot and broke it after making it.",
        ]

    elif not sent:

        sent = "He created the robot and broke it after making it."

    if not batch:

        click.echo("\n", sent, "\n")

        sent = sent.split()
        args = "-srl -pos".strip().split()

        click.echo("conll:\n", annotator.get_conll_format(sent, args))

        temp = annotator.get_annoations(sent, dep_parse=True)

        click.echo("dep_parse:\n", temp["dep_parse"])

        click.echo("chunk:\n", temp["chunk"])

        click.echo("pos:\n", temp["pos"])

        click.echo("ner:\n", temp["ner"])

        click.echo("srl:\n", temp["srl"])

        click.echo("syntaxTree:\n", temp["syntax_tree"])

        click.echo("words:\n", temp["words"])

        click.echo("skip gram\n", list(skipgrams(sent, n=3, k=2)))

    else:

        click.echo("\n\nrunning batch process", "\n", "=" * 20, "\n", sent,
                   "\n")

        args = "-srl -pos".strip().split()

        click.echo("conll:\n", annotator.get_conll_format(sent, args))

        click.echo(Fore.BLUE + "CoNLL format is recommented for batch process")
class SemanticRoleLabeler:
    def __init__(self, senna_path, stanford_parser_path):
        self.senna_path = os.path.abspath(senna_path)
        self.stanford_parser_path = os.path.abspath(stanford_parser_path)

        self.annotator = Annotator(senna_dir=self.senna_path,
                                   stp_dir=self.stanford_parser_path)

    def get_srl(self, sentence):
        if isinstance(sentence, str):
            sentence = sentence.split()

        return self.annotator.get_annoations(sentence)['srl']
Example #3
0
class TestAnnotator:
    def setup(self):

        self.sent = "PgAdmin is the leading Open Source management tool for Postgres, the world’s most advanced Open Source database."
        args = {"senna_dir": self.get_senna_path("pntl", "senna"), "save_all": True}
        self.annotator = Annotator(**args)
        self.process = self.annotator.get_annoations(self.sent, dep_parse=True)
        print(self.process["chumk"])

    def get_senna_path(self, *value):

        temp = getcwd()

        return join(temp, *value)
Example #4
0
def main(senna_path='',
         sent='',
         dep_model='',
         batch=False,
         stp_dir='',
         init=False):

    annotator = Annotator(senna_path, stp_dir, dep_model)
    if not sent and batch:
        sent = [
            "He killed the man with a knife and murdered"
            "him with a dagger.", "He is a good boy.",
            "He created the robot and broke it after making it."
        ]
    elif not sent:
        sent = "He created the robot and broke it after making it."
    if not batch:
        print("\n", sent, "\n")
        sent = sent.split()
        args = '-srl -pos'.strip().split()
        print("conll:\n", annotator.get_conll_format(sent, args))
        temp = annotator.get_annoations(sent, dep_parse=True)['dep_parse']
        print('dep_parse:\n', temp)
        temp = annotator.get_annoations(sent, dep_parse=True)['chunk']
        print('chunk:\n', temp)
        temp = annotator.get_annoations(sent, dep_parse=True)['pos']
        print('pos:\n', temp)
        temp = annotator.get_annoations(sent, dep_parse=True)['ner']
        print('ner:\n', temp)
        temp = annotator.get_annoations(sent, dep_parse=True)['srl']
        print('srl:\n', temp)
        temp = annotator.get_annoations(sent, dep_parse=True)['syntax_tree']
        print('syntaxTree:\n', temp)
        temp = annotator.get_annoations(sent, dep_parse=True)['words']
        print('words:\n', temp)
        print('skip gram\n', list(skipgrams(sent, n=3, k=2)))

    else:
        print("\n\nrunning batch process", "\n", "=" * 20, "\n", sent, "\n")
        args = '-srl -pos'.strip().split()
        print("conll:\n", annotator.get_conll_format(sent, args))
        print(Fore.BLUE + "CoNLL format is recommented for batch process")
Example #5
0
class ShallowParser:
    def __init__(self):
        print("Shallow Parser Initializing")
        self.annotator = Annotator(senna_dir="./senna/")
        self.stop_words = [
            "a", "as", "able", "about", "above", "according", "accordingly",
            "across", "actually", "after", "afterwards", "again", "against",
            "aint", "all", "allow", "allows", "almost", "alone", "along",
            "already", "also", "although", "always", "am", "among", "amongst",
            "an", "and", "another", "any", "anybody", "anyhow", "anyone",
            "anything", "anyway", "anyways", "anywhere", "apart", "appear",
            "appreciate", "appropriate", "are", "arent", "around", "as",
            "aside", "ask", "asking", "associated", "at", "available", "away",
            "awfully", "be", "became", "because", "become", "becomes",
            "becoming", "been", "before", "beforehand", "behind", "being",
            "believe", "below", "beside", "besides", "best", "better",
            "between", "beyond", "both", "brief", "but", "by", "cmon", "cs",
            "came", "can", "cant", "cannot", "cant", "cause", "causes",
            "certain", "certainly", "changes", "clearly", "co", "com", "come",
            "comes", "concerning", "consequently", "consider", "considering",
            "contain", "containing", "contains", "corresponding", "could",
            "couldnt", "course", "currently", "definitely", "described",
            "despite", "did", "didnt", "different", "do", "does", "doesnt",
            "doing", "dont", "done", "down", "downwards", "during", "each",
            "edu", "eg", "eight", "either", "else", "elsewhere", "enough",
            "entirely", "especially", "et", "etc", "even", "ever", "every",
            "everybody", "everyone", "everything", "everywhere", "ex",
            "exactly", "example", "except", "far", "few", "ff", "fifth",
            "first", "five", "followed", "following", "follows", "for",
            "former", "formerly", "forth", "four", "from", "further",
            "furthermore", "get", "gets", "getting", "given", "gives", "go",
            "goes", "going", "gone", "got", "gotten", "greetings", "had",
            "hadnt", "happens", "hardly", "has", "hasnt", "have", "havent",
            "having", "he", "hes", "hello", "help", "hence", "her", "here",
            "heres", "hereafter", "hereby", "herein", "hereupon", "hers",
            "herself", "hi", "him", "himself", "his", "hither", "hopefully",
            "how", "howbeit", "however", "i", "id", "ill", "im", "ive", "ie",
            "if", "ignored", "immediate", "in", "inasmuch", "inc", "indeed",
            "indicate", "indicated", "indicates", "inner", "insofar",
            "instead", "into", "inward", "is", "isnt", "it", "itd", "itll",
            "its", "its", "itself", "just", "keep", "keeps", "kept", "know",
            "knows", "known", "last", "lately", "later", "latter", "latterly",
            "least", "less", "lest", "let", "lets", "like", "liked", "list",
            "likely", "little", "look", "looking", "looks", "ltd", "mainly",
            "many", "may", "maybe", "me", "mean", "meanwhile", "merely",
            "might", "more", "moreover", "most", "mostly", "much", "must",
            "my", "myself", "name", "namely", "nd", "near", "nearly",
            "necessary", "need", "needs", "neither", "never", "nevertheless",
            "new", "next", "nine", "no", "nobody", "non", "none", "noone",
            "nor", "normally", "not", "nothing", "novel", "now", "nowhere",
            "obviously", "of", "off", "often", "oh", "ok", "okay", "old", "on",
            "once", "one", "ones", "only", "onto", "or", "other", "others",
            "otherwise", "ought", "our", "ours", "ourselves", "out", "outside",
            "over", "overall", "own", "particular", "particularly", "per",
            "perhaps", "placed", "please", "plus", "possible", "presumably",
            "probably", "provides", "que", "quite", "qv", "rather", "rd", "re",
            "really", "reasonably", "regarding", "regardless", "regards",
            "relatively", "respectively", "right", "said", "same", "saw",
            "say", "saying", "says", "second", "secondly", "see", "seeing",
            "seem", "seemed", "seeming", "seems", "seen", "self", "selves",
            "sensible", "sent", "serious", "seriously", "seven", "several",
            "shall", "she", "should", "shouldnt", "since", "six", "so", "some",
            "somebody", "somehow", "someone", "something", "sometime",
            "sometimes", "somewhat", "somewhere", "soon", "sorry", "specified",
            "specify", "specifying", "still", "sub", "such", "sup", "sure",
            "ts", "take", "taken", "tell", "tends", "th", "than", "thank",
            "thanks", "thanx", "that", "thats", "thats", "the", "their",
            "theirs", "them", "themselves", "then", "thence", "there",
            "theres", "thereafter", "thereby", "therefore", "therein",
            "theres", "thereupon", "these", "they", "theyd", "theyll",
            "theyre", "theyve", "think", "third", "this", "thorough",
            "thoroughly", "those", "though", "three", "through", "throughout",
            "thru", "thus", "to", "together", "too", "took", "toward",
            "towards", "tried", "tries", "truly", "try", "trying", "twice",
            "two", "un", "under", "unfortunately", "unless", "unlikely",
            "until", "unto", "up", "upon", "us", "use", "used", "useful",
            "uses", "using", "usually", "value", "various", "very", "via",
            "viz", "vs", "want", "wants", "was", "wasnt", "way", "we", "wed",
            "well", "were", "weve", "welcome", "well", "went", "were",
            "werent", "what", "whats", "whatever", "when", "whence",
            "whenever", "where", "wheres", "whereafter", "whereas", "whereby",
            "wherein", "whereupon", "wherever", "whether", "which", "while",
            "whither", "who", "whos", "whoever", "whole", "whom", "whose",
            "why", "will", "willing", "wish", "with", "within", "without",
            "wont", "wonder", "would", "would", "wouldnt", "yes", "yet", "you",
            "youd", "youll", "youre", "youve", "your", "yours", "yourself",
            "yourselves", "zero", "whose", "which", "is", ", ", "\\\\", "?",
            "\\"
        ]
        print("Shallow Parser Initialized")

    def shallowParse(self, text):
        if '?' not in text:
            text = text + '?'
        filterednpchunks = []
        result = self.annotator.get_annoations([text])['chunk']
        print(result)
        chunkswithpositions = []  #For calculating surface indices
        searchfrom = 0
        for chunkpair in result:
            position = text.find(chunkpair[0], searchfrom)
            searchfrom = position + 1
            length = len(chunkpair[0])
            chunkswithpositions.append(
                (chunkpair[0], chunkpair[1], position, length))
        phrases = []
        _phrase = []
        for chunk in chunkswithpositions:
            if chunk[1] == 'S-NP':
                phrases.append([chunk])
                continue
            if chunk[1] == 'B-NP' or chunk[1] == 'I-NP':
                _phrase.append(chunk)
                continue
            if chunk[1] == 'E-NP':
                _phrase.append(chunk)
                phrases.append(_phrase)
                _phrase = []
        for chunk in chunkswithpositions:
            if chunk[1] == 'S-VP':
                phrases.append([chunk])
                continue
            if chunk[1] == 'B-VP' or chunk[1] == 'I-VP':
                _phrase.append(chunk)
                continue
            if chunk[1] == 'E-VP':
                _phrase.append(chunk)
                phrases.append(_phrase)
                _phrase = []
        print(phrases)
        for phrase in phrases:
            filteredchunk = []
            filteredchunkstring = []
            for word in phrase:
                if word[0].lower() not in self.stop_words:
                    filteredchunk.append(word)
            if len(filteredchunk) > 0:
                filteredchunkstring = filteredchunk
                filterednpchunks.append(filteredchunkstring)
        print(filterednpchunks)
        return filterednpchunks