// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. package com.yahoo.language.simple; import com.yahoo.language.Language; import com.yahoo.language.LinguisticsCase; import com.yahoo.language.process.*; import com.yahoo.language.simple.kstem.KStemmer; import java.util.ArrayList; import java.util.List; import java.util.function.Function; import java.util.logging.Logger; import java.util.logging.Level; /** *

A tokenizer which splits on whitespace, normalizes and transforms using the given implementations * and stems using the kstem algorithm.

* *

This is not multithread safe.

* * @author Mathias Mølster Lidal * @author bratseth */ public class SimpleTokenizer implements Tokenizer { private static final Logger log = Logger.getLogger(SimpleTokenizer.class.getName()); private final static int SPACE_CODE = 32; private final Normalizer normalizer; private final Transformer transformer; private final KStemmer stemmer = new KStemmer(); private final SpecialTokenRegistry specialTokenRegistry; public SimpleTokenizer() { this(new SimpleNormalizer(), new SimpleTransformer()); } public SimpleTokenizer(Normalizer normalizer) { this(normalizer, new SimpleTransformer()); } public SimpleTokenizer(Normalizer normalizer, Transformer transformer) { this(normalizer, transformer, new SpecialTokenRegistry(List.of())); } public SimpleTokenizer(Normalizer normalizer, Transformer transformer, SpecialTokenRegistry specialTokenRegistry) { this.normalizer = normalizer; this.transformer = transformer; this.specialTokenRegistry = specialTokenRegistry; } /** Tokenize the input, applying the transform of this to each token string. */ @Override public Iterable tokenize(String input, Language language, StemMode stemMode, boolean removeAccents) { return tokenize(input, token -> processToken(token, language, stemMode, removeAccents)); } /** Tokenize the input, and apply the given transform to each token string. */ public Iterable tokenize(String input, Function tokenProcessor) { if (input.isEmpty()) return List.of(); List tokens = new ArrayList<>(); int nextCode = input.codePointAt(0); TokenType prevType = SimpleTokenType.valueOf(nextCode); TokenType tokenType = prevType; for (int prev = 0, next = Character.charCount(nextCode); next <= input.length(); ) { nextCode = next < input.length() ? input.codePointAt(next) : SPACE_CODE; TokenType nextType = SimpleTokenType.valueOf(nextCode); if (isAtTokenBoundary(prevType, nextType)) { String original = input.substring(prev, next); tokens.add(new SimpleToken(original).setOffset(prev) .setType(tokenType) .setTokenString(tokenProcessor.apply(original))); prev = next; prevType = nextType; tokenType = prevType; } else { tokenType = determineType(tokenType, nextType); } next += Character.charCount(nextCode); } return tokens; } private boolean isAtTokenBoundary(TokenType prevType, TokenType nextType) { // Always index each symbol as a token if (prevType == TokenType.INDEXABLE_SYMBOL || nextType == TokenType.INDEXABLE_SYMBOL) return true; return !prevType.isIndexable() || !nextType.isIndexable(); } private TokenType determineType(TokenType tokenType, TokenType characterType) { if (characterType == TokenType.ALPHABETIC) return TokenType.ALPHABETIC; return tokenType; } private String processToken(String token, Language language, StemMode stemMode, boolean removeAccents) { String original = token; log.log(Level.FINEST, () -> "processToken '" + original + "'"); token = normalizer.normalize(token); token = LinguisticsCase.toLowerCase(token); if (removeAccents) token = transformer.accentDrop(token, language); if (stemMode != StemMode.NONE) { String oldToken = token; token = stemmer.stem(token); String newToken = token; log.log(Level.FINEST, () -> "stem '" + oldToken+"' to '" + newToken+"'"); } String result = token; log.log(Level.FINEST, () -> "processed token is: " + result); return result; } }