Адамның аннотациясы

AbstractPlain text corpora contain much information which can only be accessed through human annotation and semantic analysis, which is typically very time consuming to perform. Analysis of such texts at …...

Active learning has been applied to dif- ferent NLP tasks, with the aim of limit- ing the amount of time and cost for human annotation. Most studies on active learn- …...

With the noticeable improvement in the overall quality of Machine Translation (MT) systems in recent years, post-editing of MT output is starting to become a com- mon practice among human …...

Using distributional analysis methods to compute semantic proximity links be- tween words has become commonplace in NLP. The resulting relations are often noisy or difficult to interpret in general. This …...

AbstractText-to-speech has long been centered on the production of an intelligible message of good quality. More recently, interest has shifted to the generation of more natural and expressive speech. A …...

AbstractWe present an analysis of the performance of machine learning classifiers on discriminating between similar languages and language varieties. We carried out a number of experiments using the results of …...

AbstractThe topics of mass and count have been studied for many decades in philosophy (e.g., Quine, 1960; Pelletier, 1975), linguistics (e.g., McCawley, 1975; Allen, 1980; Krifka, 1991) and psychology (e.g., …...

AbstractIn this paper, we present a new data set, named FreebaseQA, for open-domain factoid question answering (QA) tasks over structured knowledge bases, like Freebase. The data set is generated by …...

AbstractThis paper presents Unsupervised Lexical Frame Induction, Task 2 of the International Workshop on Semantic Evaluation in 2019. Given a set of prespecified syntactic forms in context, the task requires …...

AbstractRelation extraction (RE) has been extensively studied due to its importance in real-world applications such as knowledge base construction and question answering. Most of the existing works train the models …...

AbstractAdversarial attacks alter NLP model predictions by perturbing test-time inputs. However, it is much less understood whether, and how, predictions can be manipulated with small, concealed changes to the training …...

AbstractDialogue summarization is abstractive in nature, making it suffer from factual errors. The factual correctness of summaries has the highest priority before practical applications. Many efforts have been made to …...