使用简单的语法驱动的非词汇化依赖解析器改进麦芽依赖解析器

Anil Krishna Eragani, V. Kuchibhotla
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引用次数: 1

摘要

在本文中,我们提出了一种将非词汇化语法特征集成到麦芽依赖解析器中的方法。Malt解析器是一个词法化的解析器,与所有词法化的解析器一样,它容易出现数据稀疏性。我们的目标是通过提供来自非词汇化解析器的特性来解决这个问题。与词汇化解析器相反,非词汇化解析器以其健壮性而闻名。我们用POS标记序列作为语法规则构建了一个简单的非词汇化语法解析器。我们使用语法解析器中的特性作为Malt的附加特性。我们在英语和印地语最先进的麦芽结果上实现了约0.17-0.30% (UAS)的改进。
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Improving malt dependency parser using a simple grammar-driven unlexicalised dependency parser
In this paper, we present an approach to integrate unlexicalised grammatical features into Malt dependency parser. Malt parser is a lexicalised parser, and like every lexicalised parser, it is prone to data sparseness. We aim to address this problem by providing features from an unlexicalised parser. Contrary to lexicalised parsers, unlexicalised parsers are known for their robustness. We build a simple unlexicalised grammatical parser with POS tag sequences as grammar rules. We use the features from the grammatical parser as additional features to Malt. We achieved improvements of about 0.17-0.30% (UAS) on both English and Hindi state-of-the-art Malt results.
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