Parsimmon

Parsimmon is a wee linguistics toolkit for iOS written in Swift.

We currently support Swift 3.0. If you are looking for Objective-C, please use version 0.3.4 or earlier.

Toolkit

Currently available tools:

• Tokenizer
• Tagger
• Lemmatizer
• Naive Bayes Classifier
• Decision Tree (alpha)
• Handle languages specifications
• Support Vector Machines

Installation

The easiest way to get started is to use CocoaPods version 0.36 or higher. Just add the following line to your Podfile:

pod 'Parsimmon', :git => 'https://github.com/ludovic-coder/Parsimmon.git'

Examples

To start using Parsimmon:

import Parsimmon

Tokenizer

let tokenizer = Tokenizer()
let tokens = tokenizer.tokenize(text: "The quick brown fox jumps over the lazy dog")
print(tokens)

(
The,
quick,
brown,
fox,
jumps,
over,
the,
lazy,
dog
)

Tagger

let tagger = Tagger()
let taggedTokens = tagger.tagWordsInText(text: "The quick brown fox jumps over the lazy dog")
print(taggedTokens)

(
"('The', Determiner)",
"('quick', Adjective)",
"('brown', Adjective)",
"('fox', Noun)",
"('jumps', Noun)",
"('over', Preposition)",
"('the', Determiner)",
"('lazy', Adjective)",
"('dog', Noun)"
)

Lemmatizer

let lemmatizer = Lemmatizer()
let lemmatizedTokens = lemmatizer.lemmatizeWordsInText(text: "Diane, I'm holding in my hand a small box of chocolate bunnies.")
print(lemmatizedTokens)

(
diane,
i,
be,
hold,
in,
my,
hand,
a,
small,
box,
of,
chocolate,
bunny
)

Naive Bayes Classifier

let classifier = NaiveBayesClassifier()

// Train the classifier with some ham examples.
classifier.trainWithText(text: "nom nom ham", category: "ham")
classifier.trainWithText(text: "make sure to get the ham", category: "ham")
classifier.trainWithText(text: "please put the eggs in the fridge", category: "ham")

// Train the classifier with some spam examples.
classifier.trainWithText(text: "spammy spam spam", category: "spam")
classifier.trainWithText(text: "what does the fox say?", category: "spam")
classifier.trainWithText(text: "and fish go blub", category: "spam")

// Classify some new text. Is it ham or spam?
// In practice, you'd want to train with more examples first.
let firstExample = "use the eggs in the fridge."
let secondExample = "what does the fish say?"

print("\(firstExample) => \(classifier.classify(text: firstExample))")
print("\(secondExample) => \(classifier.classify(text: secondExample))")

'use the eggs in the fridge.' => ham
'what does the fish say?' => spam

License

MIT

Contributing

We’d love to see your ideas for improving this library! The best way to contribute is by submitting a pull request. We’ll do our best to respond to your patch as soon as possible. You can also submit a new GitHub issue if you find bugs or have questions.

Please make sure to follow our general coding style and add test coverage for new features!