Китайский

The problem of verb-noun categorial ambiguity is critical and relatively unique for non-inflectional languages, especially Chinese. We consider the verb-noun categorial fluidity a continuum and any categorial shift a transitional …...

Cross-linguistically, there are two devices for grammar to process the focus mark [+FocusJ: the fronting of focused constituents and the insertion of a Focus Mark such as the English 'be' …...

We present a novel mechanism for im- proving reference resolution by using the output of a relation tagger to rescore coreference hypotheses. Experiments show that this new framework can im- …...

In this paper we investigate named entity transliteration based on a phonetic scoring method. The phonetic method is computed using phonetic features and carefully designed pseudo features. The proposed method …...

Numerative classifiers are ubiquitous in many Asian languages. This paper pro- poses a method to construct a taxonomy of numerative classifiers based on a noun- classifier agreement database. The taxon- …...

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 …...

. With the advent of consumer generated media (e.g., Amazon reviews, Twitter, etc.), sentiment classification becomes a heated topic. Previous work heavily relies on a large amount of linguistic resources, …...

Most current dependency parsers presuppose that input words have been morphologically disambiguated using a part-of-speech tagger before parsing begins. We present a transition- based system for joint part-of-speech tagging and …...

AbstractIn this paper, we report our efforts in building a multi-lingual multi-party online chat corpus in order to develop a firm understanding in a set of social constructs such as …...

We propose a minimally supervised method for multilingual paraphrase extraction from definition sentences on the Web. Hashimoto et al. (2011) extracted paraphrases from Japanese definition sentences on the Web, as- …...

Learning from errors is a crucial aspect of improving expertise. Based on this no- tion, we discuss a robust statistical frame- work for analysing the impact of different error types …...

We investigate different ways of learning structured perceptron models for coref- erence resolution when using non-local features and beam search. Our experi- mental results indicate that standard tech- niques such …...

AbstractAbstract Meaning Representations (AMRs) are rooted, directional and labeled graphs that abstract away from morpho-syntactic idiosyncrasies such as word category (verbs and nouns), word order, and function words (determiners, some …...

By analyzing corpus data, we have shown that the tendencies of restricting perfective past marking to Accomplishments and Achievements and imperfective marking to Statives and Activities as described by the …...

AbstractWe release a massive expansion of the paraphrase database (PPDB) that now includes a collection of paraphrases in 23 different languages. The resource is derived from large volumes of bilingual …...

AbstractThis paper outlines the recent development on multilingual medical data and multilingual speech recognition system for network-based speech-to-speech translation in the medical domain. The overall speech-to-speech translation (S2ST) system was …...

As part of the SemEval-2015 shared task on Broad-Coverage Semantic Dependency Pars- ing, we evaluate the performace of our last year’s system (TurboSemanticParser) on mul- tiple languages and out-of-domain data. …...

When a large-scale incident or disaster oc- curs, there is often a great demand for rapidly developing a system to extract detailed and new information from low- resource languages (LLs). …...

AbstractWe propose a dependency parsing pipeline, in which the parsing of long-distance projections and localized dependencies are explicitly decomposed at the input level. A chosen baseline dependency parsing model performs …...

AbstractConventional graph-based dependency parsers guarantee a tree structure both during training and inference. Instead, we formalize dependency parsing as the problem of independently selecting the head of each word in …...

AbstractWord segmentation is a low-level NLP task that is non-trivial for a considerable number of languages. In this paper, we present a sequence tagging framework and apply it to word …...

AbstractWe show that constituency parsing benefits from unsupervised pre-training across a variety of languages and a range of pre-training conditions. We first compare the benefits of no pre-training, fastText, ELMo, …...

AbstractWe propose a new type of representation learning method that models words, phrases and sentences seamlessly. Our method does not depend on word segmentation and any human-annotated resources (e.g., word …...

AbstractEarly intervention for suicide risks with social media data has increasingly received great attention. Using a suicide dictionary created by mental health experts is one of the effective ways to …...

AbstractRecent work has shown that neural rerankers can improve results for dependency parsing over the top k trees produced by a base parser. However, all neural rerankers so far have …...

AbstractWe develop high performance multilingual Abstract Meaning Representation (AMR) systems by projecting English AMR annotations to other languages with weak supervision. We achieve this goal by bootstrapping transformer-based multilingual word …...

AbstractThis paper presents the GX system for the Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) task. The purpose of the MCL-WiC task is to tackle the challenge of capturing the polysemous …...

AbstractEvidence from psycholinguistic studies suggests that the human brain builds a hierarchical syntactic structure during language comprehension. However, it is still unknown whether the neural basis of such structures is …...