Leonid L. Iomdin

Learn More
A multifunctional NLP environment, ETAP-3, is presented. The environment has several NLP applications, including a machine translation system, a natural language interface to SQL type databases, synonymous paraphrasing of sentences, syntactic error correction module, and a computer-assisted language learning tool. Emphasis is laid on a new module of the(More)
The paper describes a tagging scheme designed for the Russian Treebank and presents tools used for corpus creation. 1. Introductory Remarks The present paper describes a project aimed at developing the first annotated corpus of Russian texts. Large text corpora have been used in the computational linguistics community for quite a long time now; at present,(More)
We describe a project aimed at creating a deeply annotated corpus of Russian texts. The annotation consists of comprehensive morphological marking, syntactic tagging in the form of a complete dependency tree, and semantic tagging within a restricted semantic dictionary. Syntactic tagging is using about 80 dependency relations. The syntactically annotated(More)
The paper presents the work done at the Institute for Information Transmission Problems (Russian Academy of Sciences, Moscow) on the multifunctional linguistic processor ETAP-3. Its two multilingual options are discussed – machine translation in a variety of language pairs and translation to and from UNL, a meaning representation language. For each working(More)
The paper presents a large-coverage rulebased dependency parser for Russian, ETAP-3, and results of its evaluation according to several criteria. The parser takes a morphological structure of a sentence processed as input and builds a dependency tree for this sentence using a set of syntactic rules. Each rule establishes one labeled and directed link(More)
This paper discusses the UNL Enconversion of Tamil sentences. The rich morphology of Tamil enables the Enconversion process to be based on morpho-semantic features of the words and their preceding and succeeding context. The use of case relation indicating morphological suffixes, POS tag and word level semantics allows the rule based Enconversion to be(More)
This paper reports on a series of experiments which aim at integratingExample-based Machine Translation and Translation Memories with Rule-based Machine Translation. We start by examining the potentials of each MT paradigm in terms of system-internal and system-external parameters. Whereas the system-external parameters include the expected translation(More)
The paper describes the incorporation of statistical knowledge into two different Rule-Based MT (RBMT) systems. In earlier experiments, these systems were linked with Memory-Base MT components, so that by now the translation process is supported by three MT paradigms. The paper concentrates on the acquisition of rich, informative, balanced, and up-to-date(More)