Parsing Natural Language Sentences by Semi-supervised Methods
Table 6: UAS of supervised lexicalized and delexicalized monolingual parsers, as well as the two best-performing transfer parser setups. For the supervised parsers, the columns corresponds to annotation style used for parsing, or parsing/output if a conversion was performed after parsing. For the delexicalized parser transfer, the columns correspond to parsing with both P and S style, converting the parse trees to the same style (P or S), and combining the trees.
['Tgt lang', 'Lexicalized supervised P', 'Lexicalized supervised S/P', 'Lexicalized supervised S', 'Lexicalized supervised P/S', 'Delexicalized supervised P', 'Delexicalized supervised S/P', 'Delexicalized supervised S', 'Delexicalized supervised P/S', 'Transfer P,S/P/P', 'Transfer S,P/S/S']
For the lexicalized parser, the P style is clearly better, achieving +0.77% UAS absolute on average. To obtain S style parse trees, it is generally better to parse the text using a parser trained on a P style treebank, and then to convert the output parse trees, which yields a +0.46% higher UAS than parsing directly using an S style treebank. Here, the adpositions clearly provide important information to the parser, and their annotation as heads benefits the results.