Chinese semantic dependency graph is extended from semantic dependency tree, which uses directed acyclic graphs to capture richer latent semantics of sentences. In this paper, we propose two approaches for Chinese semantic dependency graph parsing. In the first approach, we build a non-projective transition-based dependency parser with the Swap-based algorithm. Then we use a classifier to add a...

We present a study of cross-lingual direct transfer parsing for the Irish language. Firstly we discuss mapping of the annotation scheme of the Irish Dependency Treebank to a universal dependency scheme. We explain our dependency label mapping choices and the structural changes required in the Irish Dependency Treebank. We then experiment with the universally annotated treebanks of ten languages...

This paper proposes the incremental dependency parsing method based on the context-free grammar with dependency information. In the proposed method, the reachability, which represents the relation between categories, is used. In parallel to the inputting of sentence, the dependency, which is the relation between the modifying word and the modified word, is computed. In the proposed method, the ...

Most current dependency parsers presuppose that input words have been morphologically disambiguated using a part-of-speech tagger before parsing begins. We present a transitionbased system for joint part-of-speech tagging and labeled dependency parsing with nonprojective trees. Experimental evaluation on Chinese, Czech, English and German shows consistent improvements in both tagging and parsin...

Parsing is an important process of Natural Language Processing (NLP) and Computational Linguistics which is used to understand the syntax and semantics of a natural language sentences confined to the grammar. Parser is a computational system which processes input sentence according to the productions of the grammar, and builds one or more constituent structures which conform to the grammar. The...

Most of the syntax-based metrics obtain the similarity by comparing the substructures extracted from the trees of hypothesis and reference. These substructures are defined by human and can’t express all the information in the trees because of the limited length of substructures. In addition, the overlapped parts between these sub-structures are computed repeatedly. To avoid these problems, we p...

We introduce a new dependency treebank for Croatian within the Universal Dependencies framework. We construct it on top of the SETIMES.HR corpus, augmenting the resource by additional part-of-speech and dependency-syntactic annotation layers adherent to the framework guidelines. In this contribution, we outline the treebank design choices, and we use the resource to benchmark dependency parsing...

We introduce MaltParser, a data-driven parser generator for dependency parsing. Given a treebank in dependency format, MaltParser can be used to induce a parser for the language of the treebank. MaltParser supports several parsing algorithms and learning algorithms, and allows user-defined feature models, consisting of arbitrary combinations of lexical features, part-of-speech features and depe...

In this paper we describe the system by METU team for universal dependency parsing of multilingual text. We use a neural network-based dependency parser that has a greedy transition approach to dependency parsing. CCG supertags contain rich structural information that proves useful in certain NLP tasks. We experiment with CCG supertags as additional features in our experiments. The neural netwo...