This is a Python binding to the tokenizer Ucto. Tokenisation is one of the first step in almost any Natural Language Processing task, yet it is not always as trivial a task as it appears to be. This binding makes the power of the ucto tokeniser available to Python. Ucto itself is regular-expression based, extensible, and advanced tokeniser writt…
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README.rst

http://applejack.science.ru.nl/lamabadge.php/python-ucto

Ucto for Python

This is a Python binding to the tokeniser Ucto. Tokenisation is one of the first step in almost any Natural Language Processing task, yet it is not always as trivial a task as it appears to be. This binding makes the power of the ucto tokeniser available to Python. Ucto itself is a regular-expression based, extensible, and advanced tokeniser written in C++ (https://languagemachines.github.io/ucto).

Installation

Easy

Manual (Advanced)

  • Make sure to first install ucto itself (https://languagemachines.github.io/ucto) and all its dependencies.
  • Install Cython if not yet available on your system: $ sudo apt-get cython cython3 (Debian/Ubuntu, may differ for others)
  • Clone this repository and run: $ sudo python setup.py install (Make sure to use the desired version of python)

Advanced note: If the ucto libraries and includes are installed in a non-standard location, you can set environment variables INCLUDE_DIRS and LIBRARY_DIRS to point to them prior to invocation of setup.py install.

Usage

Import and instantiate the Tokenizer class with a configuration file.

import ucto
configurationfile = "tokconfig-eng"
tokenizer = ucto.Tokenizer(configurationfile)

The configuration files supplied with ucto are named tokconfig-xxx where xxx corresponds to a three letter iso-639-3 language code. There is also a tokconfig-generic one that has no language-specific rules. Alternatively, you can make and supply your own configuration file. Note that for older versions of ucto you may need to provide the absolute path, but the latest versions will find the configurations supplied with ucto automatically. See here for a list of available configuration in the latest version.

The constructor for the Tokenizer class takes the following keyword arguments:

  • lowercase (defaults to False) -- Lowercase all text
  • uppercase (defaults to False) -- Uppercase all text
  • sentenceperlineinput (defaults to False) -- Set this to True if each sentence in your input is on one line already and you do not require further sentence boundary detection from ucto.
  • sentenceperlineoutput (defaults to False) -- Set this if you want each sentence to be outputted on one line. Has not much effect within the context of Python.
  • sentencedetection (defaults to True) -- Do sentence boundary detection.
  • paragraphdetection (defaults to True) -- Do paragraph detection. Paragraphs are simply delimited by an empty line.
  • quotedetection (defaults to False) -- Set this if you want to enable the experimental quote detection, to detect quoted text (enclosed within some sort of single/double quote)
  • debug (defaults to False) -- Enable verbose debug output

Text is passed to the tokeniser using the process() method, this method returns the number of tokens rather than the tokens itself. It may be called multiple times in sequence. The tokens themselves will be buffered in the Tokenizer instance and can be obtained by iterating over it, after which the buffer will be cleared:

#pass the text (a str) (may be called multiple times),
tokenizer.process(text)

#read the tokenised data
for token in tokenizer:
    #token is an instance of ucto.Token, serialise to string using str()
    print(str(token))

    #tokens remember whether they are followed by a space
    if token.isendofsentence():
        print()
    elif not token.nospace():
        print(" ",end="")

The process() method takes a single string (str in Python 3, unicode in Python 2), as parameter. The string may contain newlines, and newlines are not necessary sentence bounds unless you instantiated the tokenizer with sentenceperlineinput=True.

Each token is an instance of ucto.Token. It can be serialised to string using str() (Python 3), as shown in the example above. In Python 2, use unicode() instead.

The following methods are available on ucto.Token instances: * isendofsentence() -- Returns a boolean indicating whether this is the last token of a sentence. * nospace() -- Returns a boolean, if True there is no space following this token in the original input text. * isnewparagraph() -- Returns True if this token is the start of a new paragraph. * isbeginofquote() * isendofquote() * tokentype -- This is an attribute, not a method. It contains the type or class of the token (e.g. a string like WORD, ABBREVIATION, PUNCTUATION, URL, EMAIL, SMILEY, etc..)

In addition to the low-level process() method, the tokenizer can also read an input file and produce an output file, in the same fashion as ucto itself does when invoked from the command line. This is achieved using the tokenize(inputfilename, outputfilename) method:

tokenizer.tokenize("input.txt","output.txt")

Input and output files may be either plain text, or in the FoLiA XML format. Upon instantiation of the Tokenizer class, there are two keyword arguments to indicate this:

  • xmlinput or foliainput -- A boolean that indicates whether the input is FoLiA XML (True) or plain text (False). Defaults to False.
  • xmloutput or foliaoutput -- A boolean that indicates whether the input is FoLiA XML (True) or plain text (False). Defaults to False.

An example for plain text input and FoLiA output:

tokenizer = ucto.Tokenizer(configurationfile, foliaoutput=True)
tokenizer.tokenize("input.txt", "ucto_output.folia.xml")

FoLiA documents retain all the information ucto can output, unlike the plain text representation. These documents can be read and manipulated from Python using the pynlpl.formats.folia module, part of PyNLPl. FoLiA is especially recommended if you intend to further enrich the document with linguistic annotation. A small example of reading ucto's FoLiA output using this library follows, but consult the documentation for more:

import pynlpl.formats.folia
doc = folia.Document(file="ucto_output.folia.xml")
for paragraph in doc.paragraphs():
    for sentence in paragraph.sentence():
        for word in sentence.words()
            print(word.text(), end="")
            if word.space:
                print(" ", end="")
        print()
    print()

Test and Example

Run and inspect example.py (Python 3) or example2.py (Python 2) for examples.