This paper describes NEREL-BIO – an annotation scheme and corpus of PubM...
In this paper, we focus on the classification of tweets as sources of
po...
The development of state-of-the-art systems in different applied areas o...
State of the art neural methods for open information extraction (OpenIE)...
We present the shared task on artificial text detection in Russian, whic...
The RuNNE Shared Task approaches the problem of nested named entity
reco...
In this work, we explore the constructive side of online reviews: advice...
Automatic monitoring of adverse drug events (ADEs) or reactions (ADRs) i...
Supporting the current trend in the AI community, we propose the AI Jour...
In this paper, we present NEREL, a Russian dataset for named entity
reco...
Concept normalization in free-form texts is a crucial step in every
text...
We show-case an application of information extraction methods, such as n...
In this paper we present a corpus of Russian strategic planning document...
In this paper we present a corpus of Russian strategic planning document...
Deep learning architectures based on self-attention have recently achiev...
The Russian Drug Reaction Corpus (RuDReC) is a new partially annotated c...
Recent research has shown the advantages of using autoencoders based on ...
We introduce an entity-centric search engineCommentsRadarthatpairs entit...
In this work, we consider the medical concept normalization problem, i.e...
We propose a novel end-to-end Aspect-based Rating Prediction model (Aspe...
In this work, we consider the medical concept normalization problem, i.e...
Information extraction from textual documents such as hospital records a...