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POBuilding a lemmatizer: speed optimization
 

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    <p>I am building a lemmatizer in python. As I need it to run in realtime/process fairly large amount of data the processing speed is of the essence. Data: I have all possible suffixes that are linked to all wordtypes that they can be combined with. Additionally I have lemmaforms that are linked to both their wordtype(s) and lemma(s). The program takes a word as input and outputs its lemma. word = lemmafrom + suffix</p> <p>For example (Note: although the example is given in English I am not building a lemmatizer for English):</p> <p>word: forbidding</p> <p>lemmaform: forbidd</p> <p>suffix: ing</p> <p>lemma: forbid</p> <p>My solution:</p> <p>I have converted the data to (nested) dicts:</p> <pre><code>suffixdict : {suffix1:[type1,type2, ... , type(n)], suffix2:[type1,type2, ... , type(n)]} lemmaformdict : {lemmaform:{type1:lemma}} </code></pre> <p>1) Find all possible suffixes and word types that they are linked to. If the longest possible suffix is 3 characters long, the program tries to match 'ing', 'ng', 'n' to the keys in suffixdict. If the key exists it returns a value (a set of wordtypes).</p> <p>2) For each matching suffix search the lemmaform from the dict. If lemmaform exists it returns the wordtypes.</p> <p>3) Finally, the program tries to intersect the wordtypes produced in steps 1) ans 2) and if the intersection is sucessful it returns the lemma of the word.</p> <p>My question: could there be a better solution to my problem from the prespective of speed? (Disregarding the option to keep frequent words and lemmas in the dictionary) Help much appriciated.</p>
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