一种短语结构规则的自动获取方法

文中提出一种新的知识获取方法，即从完全没有任何标注的生语料库中，采用ＮＡ假设自动构造带标训练数据，利用基于多特征的相似评估技术自动获取名词短语结构规则，该方法具有两个特点：（１）由于从没有任何标注的生语料库中自动获取带标训练数据，促使带标数据规模可以很大，且容易构造不同领域的带标语料库；（２）所获取的短语结构规则具有概率属性，可用于分类检索等应用中的名词短语抽取，为论证方法有效性，采用美国Ｂｅｒｉ

A NEW APPROACH TO PHRASE STRUCTURE RULE ACQUISITION

Here presented is a new approach to NP phrase structure rule acquisition based on multi\|feature similarity estimation from corpora without bracketed and nonterminal labels. By computing the distance between a rule and all feature rules based on their local contextual information, the system could sort all rules by their distances. The smaller the distance, the larger the similarity. Experiments using Berlitz corpus show that the approach presented achieves a relatively high accuracy: 80% in the first 50 rules. This result demonstrates that training data acquisition based on NA assumption is effective for rule acquisition and parsing.