Лексическая информация

How lexical information should be formulated, and how it is organized in computer memory for rapid retrieval, are central questions for computational linguists who want to create systems for language …...

In this paper we present the first implementation of LING- STAT, an interactive machine translation system designed to increase the productivity of a user, with little knowledge of the source …...

Information about words--their pronunciation, syntax and meaning--is a crucial and costly part of human language technology. Many questions remain about the best way to express and use such lexical information. …...

In this paper we deal with several kinds of anaphora in unrestricted texts. These kinds of anaphora are pronominal references, surface- count anaphora and one-anaphora. In order to solve these …...

We present an approach to the incremental ac- crual of lexical information for unknown words that is constraint-based and compatible with standard unification-based grammars. Although the tech- niques are language-independent …...

We propose an approach to summarization exploiting both lexical information and the output of an automatic anaphoric re- solver, and using Singular Value Decom- position (SVD) to identify the main …...

Dependency-based representations of natu- ral language syntax require a fine balance between structural flexibility and computa- tional complexity. In previous work, several constraints have been proposed to identify classes of …...

Various types of structural information - e.g., about the type of constructions in which binding constraints apply, or about the structure of names - play a central role in coreference …...

Unsupervised grammar induction models tend to employ relatively simple models of syntax when compared to their supervised counter- parts. Traditionally, the unsupervised mod- els have been kept simple due to …...

AbstractWith the growing interest in opinion mining from web data, more works are focused on mining in English and Chinese reviews. Probing into the problem of product opinion mining, this …...

AbstractThis paper focuses on the central role played by lexical information in the task of Recognizing Textual Entailment. In particular, the usefulness of lexical knowledge extracted from several widely used …...

. Extraction was attempted of broad-scale, high-precision Japanese-English paral- lel translation expressions from large aligned parallel corpora. To acquire broad-scale parallel translation expressions, a new method was used to extract …...

We present an approach for Seman- tic Role Labeling (SRL) using Condi- tional Random Fields in a joint identifi- cation/classification step. The approach is based on shallow syntactic information (chunks) …...

This paper presents an approach for detecting promotional content in Wikipedia. By incor- porating stylometric features, including fea- tures based on n-gram and PCFG language models, we demonstrate improved accuracy …...

Metaphor is an important way of convey- ing the affect of people, hence understand- ing how people use metaphors to convey affect is important for the communication between individuals and …...

AbstractAutomatic syntactic analysis of a corpus requires detailed lexical and morphological information that cannot always be harvested from traditional dictionaries. In building the INESS Norwegian treebank, it is often the …...

We present the description of our submission to SemEval-2016 Task 2, for the sub-task of aligning pre-annotated chunks between sen- tence pairs and providing similarity and relat- edness labels for …...

In this paper, we propose Extended HowNet 2.0 – an entity-relation common-sense representation model. Comparing to HowNet and Extended HowNet, E-HowNet 2.0 has the following improvements: (a) Reorganizing the hierarchical …...

AbstractModern neural machine translation (NMT) models employ a large number of parameters, which leads to serious over-parameterization and typically causes the underutilization of computational resources. In response to this problem, …...

AbstractTransformer-based language models benefit from conditioning on contexts of hundreds to thousands of previous tokens. What aspects of these contexts contribute to accurate model prediction? We describe a series of …...