Семантикалық Ақпарат

This paper presents a computer-tool tea- ching system supplied by a language proce- ssor. Its aim is to correct mistakes in texts written by foreign students learning Russian as a …...

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 …...

The lexicons for Knowledge-Based Machine Translation systems require knowledge in- tensive morphological, syntactic and se- mantic information. This information is of- ten used in different ways and usually for- matted …...

This paper addresses the issue of word-sense ambiguity in extraction from machine-readable resources for the con- struction of large-scale knowledge sources. We describe two experiments: one which ignored word-sense distinctions, …...

In this paper we present an evalua- tion of overlap-based measures of sim- ilarity for sentences in the same lan- guage. The measures include syntactic and semantic information, and to …...

Collocation extraction systems based on pure statistical methods suffer from two major problems. The first problem is their relatively low precision and recall rates. The second problem is their difficulty …...

We conduct large-scale experiments to in- vestigate optimal features for classification of verbs in biomedical texts. We intro- duce a range of feature sets and associated extraction techniques, and evaluate …...

Event anaphora resolution plays a critical role in discourse analysis. This paper focuses on improving event pronoun resolution using both local and global semantic information. In particular, a predicate-argument structure …...

AbstractThis article reports an intrinsic automatic summarization evaluation in the scientific lecture domain. The lecture takes place in a Smart Room that has access to different types of documents produced …...

AbstractInformation Extraction is an important task in Natural Language Processing, consisting of finding a structured representation for the information expressed in natural language text. Two key steps in information extraction …...

Text Analytics using semantic information is the latest trend of research due to its potential to represent better the texts content compared with the bag-of-words approaches. On the contrary, representation …...

AbstractNowadays, social media has become a popular platform for companies to understand their customers. It provides valuable opportunities to gain new insights into how a person’s opinion about a product …...

Automatic event schema induction (AESI) means to extract meta-event from raw text, in other words, to find out what types (tem- plates) of event may exist in the raw text …...

AbstractThis paper introduces LexFr, a corpus-based French lexical resource built by adapting the framework LexIt, originally developed to describe the combinatorial potential of Italian predicates. As in the original framework, …...

AbstractThe utility of additional semantic information for the task of next utterance selection in an automated dialogue system is the focus of study in this paper. In particular, we show …...

AbstractEvent factuality prediction (EFP) is the task of assessing the degree to which an event mentioned in a sentence has happened. For this task, both syntactic and semantic information are …...

AbstractState-of-the-art approaches for text classification leverage a transformer architecture with a linear layer on top that outputs a class distribution for a given prediction problem. While effective, this approach suffers …...

AbstractTo provide analysis of recent researches of automatic question generation from text,we surveyed 9 papers between 2019 to early 2021, retrieved from Paper with Code(PwC). Our research follows the survey …...

AbstractIn the field of dialogue summarization, due to the lack of training data, it is often difficult for supervised summary generation methods to learn vital information from dialogue context with …...

AbstractLanguage models are often trained on text alone, without additional grounding. There is debate as to how much of natural language semantics can be inferred from such a procedure. We …...

AbstractDual encoders are now the dominant architecture for dense retrieval. Yet, we have little understanding of how they represent text, and why this leads to good performance. In this work, …...