Dependency Parser

AbstractWe present a rule-based, deterministic dependency parser for Japanese. It was implemented in C++, using object classes that reflect linguistic concepts and thus facilitate the transfer of linguistic intuitions into …...

We propose a novel statistical translation model to improve translation selection of collocation. In the statistical approach that has been popularly applied for translation selection, bilingual corpora are used to …...

Collocation translation is important for machine translation and many other NLP tasks. Unlike previous methods using bilingual parallel corpora, this paper presents a new method for acquiring collocation translations by …...

This paper describes a system developed for the transformation of English sentences into a first order logical form representation. The method- ology is centered on the use of a dependency …...

. We explore the use of a partially annotated corpus to build a depen- dency parser for Japanese. We examine two types of partially annotated corpora. It is found that …...

We investigate the utility of supertag infor- mation for guiding an existing dependency parser of German. Using weighted con- straints to integrate the additionally avail- able information, the decision process …...

In the paper we describe a dependency parser that uses exact search and global learning (Crammer et al., 2006) to produce labelled dependency trees. Our system inte- grates the task …...

We present a revision learning model for improving the accuracy of a dependency parser. The revision stage corrects the out- put of the base parser by means of revi- sion …...

AbstractThis paper presents some preliminary results of our dependency parser for Thai. It is part of an ongoing project in developing a syntactically annotated Thai corpus. The parser has been …...

We present the first results on parsing the SYNTAGRUS treebank of Russian with a data-driven dependency parser, achieving a labeled attachment score of over 82% and an unlabeled attachment score …...

We connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to another. We propose quasi- …...

We compare several state of the art dependency parsers with our own parser based on a linear classification technique. Our primary goal is therefore to use syntactic information only, in …...

. The present paper describes the development of a query focused multi-document automatic summarization. A graph is constructed, where the nodes are sentences of the documents and edge scores reflect …...

AbstractThis paper describes how we built a dependency Treebank for questions. The questions for the Treebank were drawn from questions from the TREC 10 QA task and from Yahoo! Answers. …...

Incremental parsing techniques such as shift-reduce have gained popularity thanks to their efficiency, but there remains a major problem: the search is greedy and only explores a tiny fraction of …...

AbstractThe creation of language resources for less-resourced languages like the historical ones benefits from the exploitation of language-independent tools and methods developed over the years by many projects for modern …...

inThis paper describes our participation the the SemEval-2010 Task #12, Parser Evaluation using Textual Entail- ment. Our system incorporated two depen- dency parsers, one semantic role labeler, and a deep …...

We describe DCU’s LFG dependency- based metric submitted to the shared eval- uation task of WMT-MetricsMATR 2010. The metric is built on the LFG F-structure- based approach presented in (Owczarzak …...

In addition to a high accuracy, short pars- ing and training times are the most impor- tant properties of a parser. However, pars- ing and training times are still relatively …...

It is well known that parsing accuracies drop significantly on out-of-domain data. What is less known is that some parsers suffer more from domain shifts than others. We show that …...

Accuracy of dependency parsers is one of the key factors limiting the quality of dependency- based machine translation. This paper deals with the influence of various dependency pars- ing approaches …...

We present a quasi-synchronous dependency grammar (Smith and Eisner, 2006) for ma- chine translation in which the leaves of the tree are phrases rather than words as in pre- vious …...

Counts from large corpora (like the web) can be powerful syntactic cues. Past work has used web counts to help resolve isolated am- biguities, such as binary noun-verb PP attach- …...

In this paper we present our systems for the STS task. Our systems are all based on a simple process of identifying the components that correspond between two sentences. Cur- …...

The goal of semantic dependency parsing is to build dependency structure and label seman- tic relation between a head and its modifier. To attain this goal, we concentrate on obtain- …...

AbstractWord sketches are one-page, automatic, corpus-based summaries of a word's grammatical and collocational behaviour. In this paper we present word sketches for Turkish. Until now, word sketches have been generated …...

This paper describes an approach to improve summaries for a collection of Twitter posts cre- ated using the Phrase Reinforcement (PR) Al- gorithm (Sharifi et al., 2010a). The PR algo- …...

Almost all current dependency parsers classify based on millions of sparse indi- cator features. Not only do these features generalize poorly, but the cost of feature computation restricts parsing speed …...

AbstractWe present a gold standard annotation of syntactic dependencies in the English Web Treebank corpus using the Stanford Dependencies formalism. This resource addresses the lack of a gold standard dependency …...

AbstractIn this paper we present a system for experimenting with combinations of dependency parsers. The system supports initial training of different parsing models, creation of parsebank(s) with these models, and …...

AbstractIn this paper we present the results of an ongoing experiment of bootstrapping a Treebank for Catalan by using a Dependency Parser trained with Spanish sentences. In order to save …...

AbstractThis article presents the methods, results, and precision of the syntactic annotation process of the Rhapsodie Treebank of spoken French. The Rhapsodie Treebank is an 33,000 word corpus annotated for …...

We investigate grammatical error detec- tion in spoken language, and present a data-driven method to train a dependency parser to automatically identify and label grammatical errors. This method is ag- …...

AbstractIn this paper we investigate how different dependency representations of a treebank influence the accuracy of the dependency parser trained on this treebank and the impact on several parser applications: …...

AbstractGrammar models conceived for parsing purposes are often poorer than models that are motivated linguistically. We present a grammar model which is linguistically satisfactory and based on the principles of …...

We present a novel approach for induc- ing unsupervised dependency parsers for languages that have no labeled training data, but have translated text in a resource- rich language. We train …...

We present a two-stage framework to parse a sentence into its Abstract Meaning Repre- sentation (AMR). We first use a dependency parser to generate a dependency tree for the sentence. …...

We present a novel method for the cross- lingual transfer of dependency parsers. Our goal is to induce a dependency parser in a target language of interest without any direct …...

In English-to-Japanese translation, BLEU (Papineni et al., 2002), the de facto standard evaluation metric for machine translation (MT), has very weak corre- lation with human judgments (Goto et al., 2011; …...

Many NLP systems use dependency parsers as critical components. Jonit learn- ing parsers usually achieve better parsing accuracies than two-stage methods. How- ever, classical joint parsing algorithms significantly increase computational …...

We propose a discriminatively trained re- current neural network (RNN) that pre- dicts the actions for a fast and accurate shift-reduce dependency parser. The RNN uses its output-dependent model struc- …...

The high-dimensionality of lexical features in parsing can be memory consuming and cause over-fitting problems. We propose a general framework to replace all lexical feature tem- plates by low-dimensional features …...

AbstractThis paper presents a new linguistic resource for the study and computational processing of Portuguese. CINTIL DependencyBank PREMIUM is a corpus of Portuguese news text, accurately manually annotated with a …...

AbstractBecause of the small size of Romanian corpora, the performance of a PoS tagger or a dependency parser trained with the standard supervised methods fall far short from the performance …...

AbstractWe introduce DeQue, a lexicon covering French complex prepositions (CPRE) like “à partir de” (from) and complex conjunctions (CCONJ) like “bien que” (although). The lexicon includes fine-grained linguistic description based …...

In this paper, we present a straightforward strategy for transferring dependency parsers across languages. The proposed method learns a parser from partially annotated data obtained through the projection of annotations …...

AbstractWe present experiments in incrementally learning a dependency parser. The parser will be used in the WordsEye Linguistics Tools (WELT) (Ulinski et al., 2014) which supports field linguists documenting a …...

In this paper we present our system de- veloped for the SemEval 2016 Task 2 - Interpretable Semantic Textual Similarity along with the results obtained for our sub- mitted runs. …...

AbstractThe paper introduces a “train once, use many” approach for the syntactic analysis of phrasal compounds (PC) of the type XP+N like “Would you like to sit on my knee?” …...

Syntactic parsing of web queries is impor- tant for query understanding. However, web queries usually do not observe the grammar of a written language, and no labeled syntactic trees for …...

AbstractIn this paper we present ThReeNN, a model for Community Question Answering, Task 3, of SemEval-2017. The proposed model exploits both syntactic and semantic information to build a single and …...

AbstractIn this paper, we present our proposed system (EXPR) to participate in the hypernym discovery task of SemEval 2018. The task addresses the challenge of discovering hypernym relations from a …...

AbstractSemantic role labeling (SRL) aims to identify the predicate-argument structure of a sentence. Inspired by the strong correlation between syntax and semantics, previous works pay much attention to improve SRL …...

AbstractNeural encoders have allowed dependency parsers to shift from higher-order structured models to simpler first-order ones, making decoding faster and still achieving better accuracy than non-neural parsers. This has led …...

AbstractThe research presented in this paper aims at enriching the manually morphosyntactically annotated part of National Corpus of Polish (NKJP1M) with a syntactic layer, i.e. dependency trees of sentences, and …...

AbstractWe consider the task of cross-lingual adaptation of dependency parsers without annotated target corpora and parallel corpora. Previous work either directly applies a discriminative source parser to the target language, …...

AbstractUnlike English letters, Chinese characters have rich and specific meanings. Usually, the meaning of a word can be derived from its constituent characters in some way. Several previous works on …...

AbstractSyntactic information, especially dependency trees, has been widely used by existing studies to improve relation extraction with better semantic guidance for analyzing the context information associated with the given entities. …...

AbstractWhile the predictive performance of modern statistical dependency parsers relies heavily on the availability of expensive expert-annotated treebank data, not all annotations contribute equally to the training of the parsers. …...

Various methods have been proposed to generate code-switched texts. Many of these involve training neural networks and, in turn, require some (albeit small) amounts of code-switched texts or parallel corpora …...

AbstractThis paper presents the phonological, morphological, and syntactic distinctions between formal and informal Persian, showing that these two variants have fundamental differences that cannot be attributed solely to pronunciation discrepancies. …...

AbstractText generation often involves producing coherent and grammatically correct texts that also satisfy a given set of semantic constraints. While most approaches for conditional text generation have primarily focused on …...

AbstractThis study aims to tackle some challenges posed by legal texts in the field of NLP. The LegalEval challenge proposes three tasks, based on Indial Legal documents: Rhetorical Roles Prediction, …...