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POWriting a tokenizer in Python
 

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  1. POWriting a tokenizer in Python
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    <p>I want to design a custom tokenizer module in Python that lets users specify what tokenizer(s) to use for the input. For instance, consider the following input:</p> <blockquote> <p>Q: What is a good way to achieve this? A: I am not so sure. I think I will use Python.</p> </blockquote> <p>I want to be able to provide <a href="http://nltk.org/api/nltk.tokenize.html">NLTK's sentence tokenization</a>, <code>sent_tokenize()</code> as an option because it works well in many situations and I don't want to re-invent the wheel. In addition to this, I also want to provide a finer-grained tokenization builder (something along the lines of a rule-engine). Let me explain:</p> <p>Assume that I provider a couple of tokenizers:</p> <pre><code>SENTENCE # Tokenizes the given input by using sent_tokenize() WORD # Tokenizes the given input by using word_tokenize() QA # Tokenizes using a custom regular expression. E.g., Q: (.*?) A: (.*?) </code></pre> <p>I want to support rules as follows:</p> <ol> <li>QA -> SENTENCE: Apply the QA tokenizer first, followed by the sentence tokenizer</li> <li>QA: Apply just the QA tokenizer</li> </ol> <p>Therefore, the expected output is as follows:</p> <p><strong>1. QA -> SENTENCE</strong></p> <pre><code>[ ('QUESTION', ('SENTENCE', 'What is a good way to achieve this?'), ), ('ANSWER', ('SENTENCE', 'I am not so sure', 'I think I will use Python') ) ] </code></pre> <p><strong>2. QA</strong></p> <pre><code>[ ('QUESTION', 'What is a good way to achieve this?'), ('ANSWER', 'I am not so sure. I think I will use Python') ] </code></pre> <p>What is a good design to achieve this efficiently?</p>
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    1. COare you asking what libraries to use?
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    2. CO@JoranBeasley: Either libraries or a good extensible design pattern that is scalable. I haven't taken compilers so I just want to make sure I am not re-implementing something standard from that area.
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    3. COIm not sure for lexers/grammars I have really only messed with ply ... but that may be what your looking for ... here is a good list of parsing options : http://nedbatchelder.com/text/python-parsers.html ... although Im not sure if that even partially answers your question
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