Morphology Based Automatic Acquisition of Large-coverage Lexica
Morphology Based Automatic Acquisition of Large-coverage Lexica
复制标题
基于形态学的大覆盖词汇自动获取
DOI：
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发表时间：
2004
期刊：
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通讯作者：
B. Lang
中科院分区：
文献类型：
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作者：
Lionel Clément;Benoît Sagot;B. Lang
本文介绍了一种利用大型语料库和形态学知识构建覆盖面广的形态学词典的新技术，并以法语为例进行了应用。基本上，它依赖于这样一个想法，即如果在语料库中发现的几个不同的词被最好地解释为这个词元的形态变体，则可以猜测假设词元的存在。我们首先通过在2500万单词的一般法语语料库中提取动词和形容词来验证我们的技术。与其他可用的法语词汇资源相比，我们的结果是非常令人满意的，因为我们涵盖了许多词，往往是派生词，并不总是存在于其他词汇。将该算法应用于植物学语料库中的领域形容词的提取也取得了很好的效果，从而证明了该算法在领域词汇提取中的可用性。此外，它可以推广到任何具有实质形态的语言。
In this article, we introduce a new technique for constructing wide-coverage morphological lexica from large corpora and morphological knowledge, with an application to French. Basically, it relies on the idea that the existence of a hypothetical lemma can be guessed if several different words found in the corpus are best interpreted as morphological variants of this lemma. We first validated our technique by extracting verbs and adjectives on a general French corpus of 25 million words. Compared with other lexical resources available for French, our results are very satisfying, since we cover many words, often derived words, that are not always present in other lexica. Application of our algorithm to the acquisition of domain-specific adjectives on a botanic corpus gave also very good results, thus demonstrating its usability to extract domain-specific lexica. Moreover, it is generalizable to any language with a substantial morphology.