The paper describes the project held within Russian National Corpus (http://www.ruscorpora.ru). Beside such obligatory constituents of a linguistic corpus as POS (parts of speech) and morphological tagging RNC contains semantic annotation. Six classifications are involved in the tagging: category, taxonomy, mereology, topology, evaluation and derivational classes. The operating of the context s...

Background: An ongoing assessment of the literature is difficult with the rapidly increasing volume of research publications and limited effective information extraction tools which identify entity relationships from text. A recent study reported development of Muscorian, a generic text processing tool for extracting proteinprotein interactions from text that achieved comparable performance to ...

In order, to make text a suitable input to an automatic method of information extraction it is usually transformed from unstructured source of information into a structured format. Part of Speech Tagging is one of the preprocessing steps which assign one of the parts of speech to the given word. In this paper we had discussed various models of supervised and unsupervised technique shown the com...

Part-of-speech (POS) tagging is the process of assigning each word of an input text into an appropriate morphological class. Automatic recognition of parts-of-speech is very important for high level NLP applications, since it would be usually infeasible to perform this task manually in practical systems. One approach to POS tagging uses morphological disambiguation which selects the most suitab...

dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. part-of-speech (pos) tagging is a prerequisite for dependency parsing. generally, dependency parsers do the pos tagging task along with dependency parsing in a pipeline mode. unfortunately, in pipel...

ing and then consider part-of-speech tagging, which was the first syntactic problem to successfully be attacked by statistical techniques and also serves as a good warm-up for the main topic—statistical parsing. Here, I consider both the simplified case in which the input string is viewed as a string of parts of speech and the more interesting case in which the parser is guided by statistical i...

Pre-trained word embeddings improve the performance of a neural model at the cost of increasing the model size. We propose to benefit from this resource without paying the cost by operating strictly at the sublexical level. Our approach is quite simple: before task-specific training, we first optimize sub-word parameters to reconstruct pre-trained word embeddings using various distance measures...

The purpose of part-of-speech tagging is to automatically tag the words of a text, written in a certain language, with labels that usually take the form of acronyms that designate the appropriate parts-of-speech. In this paper we propose a new approach to the problem that divides it in two different tasks: a learning task and an optimization task. We tackled each of those tasks with evolutionar...