nltk.corpus.reader.nps_chat module

class nltk.corpus.reader.nps_chat.NPSChatCorpusReader[source]

Bases: nltk.corpus.reader.xmldocs.XMLCorpusReader

__init__(root, fileids, wrap_etree=False, tagset=None)[source]
Parameters
  • root (PathPointer or str) – A path pointer identifying the root directory for this corpus. If a string is specified, then it will be converted to a PathPointer automatically.

  • fileids – A list of the files that make up this corpus. This list can either be specified explicitly, as a list of strings; or implicitly, as a regular expression over file paths. The absolute path for each file will be constructed by joining the reader’s root to each file name.

  • encoding

    The default unicode encoding for the files that make up the corpus. The value of encoding can be any of the following:

    • A string: encoding is the encoding name for all files.

    • A dictionary: encoding[file_id] is the encoding name for the file whose identifier is file_id. If file_id is not in encoding, then the file contents will be processed using non-unicode byte strings.

    • A list: encoding should be a list of (regexp, encoding) tuples. The encoding for a file whose identifier is file_id will be the encoding value for the first tuple whose regexp matches the file_id. If no tuple’s regexp matches the file_id, the file contents will be processed using non-unicode byte strings.

    • None: the file contents of all files will be processed using non-unicode byte strings.

  • tagset – The name of the tagset used by this corpus, to be used for normalizing or converting the POS tags returned by the tagged_...() methods.

xml_posts(fileids=None)[source]
posts(fileids=None)[source]
tagged_posts(fileids=None, tagset=None)[source]
words(fileids=None)[source]

Returns all of the words and punctuation symbols in the specified file that were in text nodes – ie, tags are ignored. Like the xml() method, fileid can only specify one file.

Returns

the given file’s text nodes as a list of words and punctuation symbols

Return type

list(str)

tagged_words(fileids=None, tagset=None)[source]