+ h>Rt^RIt^RI5^RI5!RR]]4tR#)a CorpusReader for the Pros and Cons dataset. - Pros and Cons dataset information - Contact: Bing Liu, liub@cs.uic.edu https://www.cs.uic.edu/~liub Distributed with permission. Related papers: - Murthy Ganapathibhotla and Bing Liu. "Mining Opinions in Comparative Sentences". Proceedings of the 22nd International Conference on Computational Linguistics (Coling-2008), Manchester, 18-22 August, 2008. - Bing Liu, Minqing Hu and Junsheng Cheng. "Opinion Observer: Analyzing and Comparing Opinions on the Web". Proceedings of the 14th international World Wide Web conference (WWW-2005), May 10-14, 2005, in Chiba, Japan. N)*c`a]tRt^"toRt]t]!4R3RltR Rlt R Rlt Rt Rt R t VtR#) ProsConsCorpusReadera Reader for the Pros and Cons sentence dataset. >>> from nltk.corpus import pros_cons >>> pros_cons.sents(categories='Cons') # doctest: +NORMALIZE_WHITESPACE [['East', 'batteries', '!', 'On', '-', 'off', 'switch', 'too', 'easy', 'to', 'maneuver', '.'], ['Eats', '...', 'no', ',', 'GULPS', 'batteries'], ...] >>> pros_cons.words('IntegratedPros.txt') ['Easy', 'to', 'use', ',', 'economical', '!', ...] utf8c h\PWW$4\PW4W0nR#)a} :param root: The root directory for the corpus. :param fileids: a list or regexp specifying the fileids in the corpus. :param word_tokenizer: a tokenizer for breaking sentences or paragraphs into words. Default: `WhitespaceTokenizer` :param encoding: the encoding that should be used to read the corpus. :param kwargs: additional parameters passed to CategorizedCorpusReader. N) CorpusReader__init__CategorizedCorpusReader_word_tokenizer)selfrootfileidsword_tokenizerencodingkwargss&&&&&,>/usr/lib/python3/dist-packages/nltk/corpus/reader/pros_cons.pyrProsConsCorpusReader.__init__1s(" d'<((6-Nc  "VPW4pVfVPpM\V\4'dV.p\ VP VRR4UUUu.uF#wr4pVP W0PVR7NK% uppp4#uupppi)a Return all sentences in the corpus or in the specified files/categories. :param fileids: a list or regexp specifying the ids of the files whose sentences have to be returned. :param categories: a list specifying the categories whose sentences have to be returned. :return: the given file(s) as a list of sentences. Each sentence is tokenized using the specified word_tokenizer. :rtype: list(list(str)) Tr)_resolve_fileids isinstancestrconcatabspaths CorpusView_read_sent_blockr r categoriespathencfileids&&& rsentsProsConsCorpusReader.sentsF--4 ?mmG  % %iG,0==$+M +M'T&;&;cJ+M    )B c  "VPW4pVfVPpM\V\4'dV.p\ VP VRR4UUUu.uF#wr4pVP W0PVR7NK% uppp4#uupppi)aw Return all words and punctuation symbols in the corpus or in the specified files/categories. :param fileids: a list or regexp specifying the ids of the files whose words have to be returned. :param categories: a list specifying the categories whose words have to be returned. :return: the given file(s) as a list of words and punctuation symbols. :rtype: list(str) Tr)rrrrrrr_read_word_blockrs&&& rwordsProsConsCorpusReader.words^r%r&c2.p\^4FpVP4pV'gK\P!RV4pV'gK>VP VP P VP^4P444K V#)z+^(?!\n)\s*<(Pros|Cons)>(.*)) rangereadlinerematchappendr tokenizegroupstrip)r streamr#ilinesents&& rr%ProsConsCorpusReader._read_sent_blockvsrrA??$D88JDQDt T11::4::a=;N;N;PQR  rc\.pVPV4FpVPV4K V#)N)rextend)r r5r)r8s&& rr(%ProsConsCorpusReader._read_word_blocks-))&1D LL 2 r)r )NN)__name__ __module__ __qualname____firstlineno____doc__StreamBackedCorpusViewrWordPunctTokenizerrr#r)rr(__static_attributes____classdictcell__) __classdict__s@rrr"s: (J *+ .* 0 0 rr)rAr/nltk.corpus.reader.api nltk.tokenizer rrrrrJs&( $c2Lcr