Синтаксические особенности

AbstractMachine Translation (MT) systems that process unrestricted text should be able to deal with words that are not found in the MT lexicon. Without some kind of recognition, the parse …...

This paper explores the contribution of a broad range of syntactic features to WSD: grammatical relations coded as the presence of adjuncts/arguments in isolation or as subcategorization frames, and instantiated …...

In this paper, experiments on automatic extraction of keywords from abstracts us- ing a supervised machine learning algo- rithm are discussed. The main point of this paper is that by …...

The success of supervised learning approaches to word sense disambiguation is largely de- pendent on the features used to represent the context in which an ambiguous word occurs. Previous work …...

We describe a method for discriminative training of a language model that makes use of syntactic features. We follow a reranking approach, where a baseline recogniser is used to produce …...

In this paper, we study the impact of a group of features extracted automatically from machine-generated parse trees on coreference resolution. One focus is on designing syn- tactic features using …...

AbstractIn this article we address the task of automatic text structuring into linear and non-overlapping thematic episodes. Our investigation reports on the use of various lexical, acoustic and syntactic features, …...

The increasing use of large open-domain document sources is exacerbating the problem of ambiguity in named entities. This paper explores the use of a range of syntactic and semantic features …...

This short paper presents a system developed at the Université Paris 13 for the Semeval 2007 Metonymy Resolution Task (task #08, location name track; see Markert and Nissim, 2007). The …...

Syntactic Features for Text Categorisation Ari Chanen School of Information Technologies University of Sydney Sydney, Australia, 2006 ari@it.usyd.edu.au Jon Patrick School of Information Technologies University of Sydney Sydney, Australia, 2006 …...

We present an algorithm for unsupervised induction of labeled parse trees. The al- gorithm has three stages: bracketing, ini- tial labeling, and label clustering. Brack- eting is done from raw …...

. The Phrase-Based Statistical Machine Translation (PB-SMT) model has recently begun to include source context modeling, under the assumption that the proper lexical choice of an ambiguous word can be …...

In previous research in automatic verb classification, syntactic features have proved the most useful features, although manual classifications rely heavily on se- mantic features. We show, in contrast with previous …...

. The ability to accurately classify temporal relations between events is an important task in a large number of natural language processing and text mining applications such as question answering, …...

AbstractIn this paper we present a description of negation cues and their scope in biomedical texts, based on the cues that occur in the BioScope corpus. We provide information about …...

Question detection serves great purposes in the cQA question retrieval task. While detecting questions in standard language data corpus is relatively easy, it becomes a great challenge for online content. …...

This paper presents a two-stage approach to summarizing multiple contrastive viewpoints in opinionated text. In the first stage, we use an unsupervised probabilistic approach to model and extract multiple viewpoints …...

We describe an open source computational grammar for Punjabi; a resource-poor language. The grammar is developed in GF (Grammatical framework), which is a tool for multilingual grammar formalism. First, we …...

Attempts to profile authors according to their characteristics extracted from textual data, in- cluding native language, have drawn attention in recent years, via various machine learn- ing approaches utilising mostly …...

Arabic morphology is complex, partly be- cause of its richness, and partly because of common irregular word forms, such as broken plurals (which resemble singular nouns), and nouns with irregular …...

We present an approach to automatically re- cover hidden attributes of scientific articles, such as whether the author is a native English speaker, whether the author is a male or …...

AbstractWe define a variable-order Markov model, representing a Probabilistic Context Free Grammar, built from the sentence-level, de-lexicalized parse of source texts generated by a standard lexicalized parser, which we apply …...

This paper describes the systems deployed by the ALPAGE team to participate to the SemEval-2014 Task on Broad-Coverage Semantic Dependency Parsing. We de- veloped two transition-based dependency parsers with extended …...

Definiteness expresses a constellation of semantic, pragmatic, and discourse properties—the communicative functions—of an NP. We present a supervised classifier for English NPs that uses lexical, morphological, and syntactic features to …...

AbstractTranslating prepositions is a difficult and under-studied problem in SMT. We present a novel method to improve the translation of prepositions by using noun classes to model their selectional preferences. …...

The widespread use of deception in online sources has motivated the need for meth- ods to automatically profile and identify deceivers. This work explores deception, gender and age detection in …...

Syntactic features play an essential role in identifying relationship in a sentence. Pre- vious neural network models directly work on raw word sequences or constituent parse trees, thus often suffer …...

AbstractWe extend classic review mining work by building a binary classifier that predicts whether a review of a documentary film was written by an expert or a layman with 90.70% …...

AbstractWe consider the task of predicting how literary a text is, with a gold standard from human ratings. Aside from a standard bigram baseline, we apply rich syntactic tree fragments, …...

AbstractWe propose a deep learning architecture to capture argumentative relations of attack and support from one piece of text to another, of the kind that naturally occur in a debate. …...

AbstractMost existing research on authorship attribution uses various lexical, syntactic and semantic features. In this paper we demonstrate an effective template-based approach for combining various syntactic features of a document …...

AbstractIn the present paper we describe the UPV-28-UNITO system’s submission to the RumorEval 2019 shared task. The approach we applied for addressing both the subtasks of the contest exploits both …...

AbstractBERT is a recent language representation model that has surprisingly performed well in diverse language understanding benchmarks. This result indicates the possibility that BERT networks capture structural information about language. …...

AbstractIn this study, we propose a conversation-analytic annotation scheme for turn-taking behavior in multi-party conversations. The annotation scheme is motivated by a proposal of a proper model of turn-taking incorporating …...

AbstractTextual content is the most significant as well as substantially the big part of CQA (Community Question Answering) forums. Users gain reputation for contributing such content. Although linguistic quality is …...

AbstractElementary Discourse Unit (EDU) recognition is the basic task of discourse analysis, and the Chinese and English discourse alignment corpus is helpful to the studies of EDU recognition. This paper …...

AbstractRecognizing the layout of unstructured digital documents is crucial when parsing the documents into the structured, machine-readable format for downstream applications. Recent studies in Document Layout Analysis usually rely on …...

AbstractIn this paper we present FeatureBART, a linguistically motivated sequence-to-sequence monolingual pre-training strategy in which syntactic features such as lemma, part-of-speech and dependency labels are incorporated into the span prediction …...