Лингвистические явления

Command relations are important tools in linguistics, especially in anaphora theory. In this paper I present an indexing technique which allows us to implement a simple and efficient check for …...

Recent developments in statistical modeling of various linguistic phenomena have shown that additional features give consistent per- formance improvements. Quite often, im- provements are limited by the number of fea- …...

AbstractNaturally-occurring instances of linguistic phenomena are important both for training and for evaluating automatic text processing. When available in large quantities, they also prove interesting material for linguistic studies. In …...

AbstractWe analyze in this paper a number of data sets proposed over the last decade or so for the task of paraphrase identification. The goal of the analysis is to …...

Within the field of Statistical Machine Trans- lation (SMT), the neural approach (NMT) has recently emerged as the first technology able to challenge the long-standing dominance of phrase-based approaches (PBMT). …...

AbstractWe describe a multi-agent communication framework for examining high-level linguistic phenomena at the community-level. We demonstrate that complex linguistic behavior observed in natural language can be reproduced in this simple …...

AbstractThis paper describes a test suite submission providing detailed statistics of linguistic performance for the state-of-the-art German-English systems of the Fifth Conference of Machine Translation (WMT20). The analysis covers 107 …...

AbstractDeep neural models have repeatedly proved excellent at memorizing surface patterns from large datasets for various ML and NLP benchmarks. They struggle to achieve human-like thinking, however, because they lack …...

AbstractThis work describes an analysis of inter-annotator disagreements in human evaluation of machine translation output. The errors in the analysed texts were marked by multiple annotators under guidance of different …...

AbstractIn the age of large transformer language models, linguistic evaluation play an important role in diagnosing models’ abilities and limitations on natural language understanding. However, current evaluation methods show some …...

AbstractExplicit linguistic knowledge, encoded by resources such as rule-based morphological analyzers, continues to prove useful in downstream NLP tasks, especially for low-resource languages and dialects. Rules are an important asset …...

AbstractIt is common for websites that contain User-Generated Text (UGT) to provide an automatic translation option to reach out to their linguistically diverse users. In such scenarios, the process of …...

AbstractIn this paper, we focus on how current Machine Translation (MT) engines perform on the translation of emotion-loaded texts by evaluating outputs from Google Translate according to a framework proposed …...