Articles

AbstractWe present a method for acquiring reliable predicate-argument structures from raw corpora for automatic compilation of case frames. Such lexicon compilation requires highly reliable predicate-argument structures to practically contribute to Natural Language Processing (NLP) applications, such as paraphrasing, text entailment, and machine translation. However, to precisely identify predicate-argument structures, case …...

AbstractWe investigate a number of approaches to generating Stanford Dependencies, a widely used semantically-oriented dependency representation. We examine algorithms specifically designed for dependency parsing (Nivre, Nivre Eager, Covington, Eisner, and RelEx) as well as dependencies extracted from constituent parse trees created by phrase structure parsers (Charniak, Charniak-Johnson, Bikel, Berkeley and …...

We propose an unsupervised approach uti- lizing only raw corpora to enhance mor- phological alignment involving highly in- flected languages. Our method focuses on closed-class morphemes, modeling their influence on nearby words. Our language- independent model recovers important links missing in the IBM Model 4 align- ment and demonstrates improved …...

We study the problem of integrating scat- tered online opinions. For this purpose, we propose to exploit structured ontology to obtain well-formed relevant aspects to a topic and use them to organize scattered opinions to generate a structured sum- mary. Particularly, we focus on two main challenges in implementing this …...

This paper analyzes the contribution of se- mantic roles to TimeML event recognition and classification. For that purpose, an approach using conditional random fields with a variety of morphosyntactic features plus semantic roles features is developed and evaluated. Our system achieves an F1 of 81.4% in recognition and a 64.2% …...

We propose semantic role features for a Tree-to-String transducer to model the re- ordering/deletion of source-side semantic roles. These semantic features, as well as the Tree-to-String templates, are trained based on a conditional log-linear model and are shown to significantly outperform systems trained based on Max-Likelihood and EM. We also …...

Tree-based translation models, which ex- ploit the linguistic syntax of source lan- guage, usually separate decoding into two steps: parsing and translation. Although this separation makes tree-based decoding simple and efficient, its translation perfor- mance is usually limited by the number of parse trees offered by parser. Alter- natively, we …...

News tweets that report what is happen- ing have become an important real-time information source. We raise the prob- lem of Semantic Role Labeling (SRL) for news tweets, which is meaningful for fine grained information extraction and retrieval. We present a self-supervised learning approach to train a domain spe- cific …...

Previous research has demonstrated the importance of handling differences be- tween domains such as “newswire” and “biomedicine” when porting NLP systems from one domain to another. In this paper we identify the related issue of subdomain variation, i.e., differences between subsets of a domain that might be expected to be- …...

Several researchers have proposed semi-supervised learning methods for adapting event extraction systems to new event types. This paper investigates two kinds of bootstrapping methods used for event extraction: the document-centric and similarity-centric approaches, and proposes a filtered ranking method that combines the advantages of the two. We use a range …...

This paper addresses the problem of dy- namic model parameter selection for log- linear model based statistical machine translation (SMT) systems. In this work, we propose a principled method for this task by transforming it to a test data de- pendent development set selection prob- lem. We present two algorithms …...

In this paper we present a simplified shallow semantic parsing approach to learning the scope of negation (SoN). This is done by formulating it as a shallow semantic parsing problem with the negation signal as the predicate and the negation scope as its ar- guments. Our parsing approach to SoN …...

In this paper, we focus on object feature 1 1...

Previous work on bilingual lexicon extrac- tion from comparable corpora aimed at finding a good representation for the usage patterns of source and target words and at comparing these patterns efficiently. In this paper, we try to work it out in an- other way: improving the quality of the comparable …...

Polarity shifting marked by various linguistic structures has been a challenge to automatic sentiment classification. In this paper, we propose a machine learning approach to incorporate polarity shifting information into a document-level sentiment classification system. First, a feature selection method is adopted to automatically generate the training data for a …...

We present a constituent parsing-based reordering technique that improves the performance of the state-of-the-art Eng- lish-to-Japanese phrase translation sys- tem that includes distortion models by 4.76 BLEU points. The phrase transla- tion model with reordering applied at the pre-processing stage outperforms a syn- tax-based translation system that incor- porates a …...

This paper investigates the use and the prediction potential of semantic similar- ity measures for automatic generation of links across different documents and pas- sages. First, the correlation between the way people link content and the results produced by standard semantic similarity measures is investigated. The relation be- tween semantic …...

This paper describes how to cluster to- gether the phrases of a phrase-based sta- tistical machine translation (SMT) sys- tem, using information in the phrase table itself. The clustering is symmetric and recursive: it is applied both to source- language and target-language phrases, and the clustering in one language helps …...

This paper proposes a dependency-driven scheme to dynamically determine the syn- tactic parse tree structure for tree ker- nel-based anaphoricity determination in coreference resolution. Given a full syntactic parse tree, it keeps the nodes and the paths related with current mention based on con- stituent dependencies from both syntactic and …...

Text Understanding systems often commit to a single best interpretation of a sen- tence before analyzing subsequent text. This interpretation is chosen by resolv- ing ambiguous alternatives to the one with the highest confidence, given the context available at the time of commitment. Sub- sequent text, however, may contain infor- …...