Leonid L. Iomdin

Parsing the SynTagRus Treebank of Russian

We present the first results on parsing the SynTagRus treebank of Russian with a data-driven dependency parser, achieving a labeled attachment score of over 82% and an unlabeled attachment score of 89%. A feature analysis shows that high parsing accuracy is crucially dependent on the use of both lexical and morphological features. We conjecture that the latter result can be generalized to richly inflected languages in general, provided that sufficient amounts of training data are available.

Creating a Universal Networking Language module within an advanced NLP system

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 processor responsible for the interface with the Universal Networking Language, a recent product by the UN University intended for the facilitation of multilanguage, multiethnic access to communication networks such as WWW. The UNL module of ETAP-3 naturally combines the two major approaches accepted in machine translation: the transfer-based approach and the interlingua approach.

Towards a Dynamic Linkage of Example-based and Rule-based Machine Translation

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 quality and translation coverage, system-internal parameters relate to adaptability and recall of translation units. We prefer a dynamic linkage of different MT paradigms where the sharing of labor amongst the modules involved, such as segmentation andsegment translation, is decided dynamically during runtime. We motivatethe communication of linguistically rich data structures between thedifferent components in a hybrid system and show that this linkage leadsto better translation results and improves the customization possibilitiesof the system.

Multilinguality in ETAP-3: reuse of lexical resources

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 language, ETAP has one integral dictionary, which is used in all applications both for the analysis and synthesis (generation) of the given language. In difficult cases, interactive dialogue with the user is used for disambiguation. Emphasis is laid on multiple use of lexical resources in the multilingual environment.

Semantic Paraphrasing for Information Retrieval and Extraction

The paper is devoted to the development of a system of synonymous and quasi-synonymous paraphrasing and its practical applications, first of all in the domain of search engine optimization and information extraction. This system is part of the ETAP-3 multifunctional NLP environment created by the Laboratory of Computational Linguistics of the Kharkevich Institute for Information Transmission Problems. Combinatorial dictionaries of Russian, English and some other languages and a rule-driven parser constitute the core of ETAP-3 while a variety of generating modules are used in a number of applications. The paraphrase generator, based on the apparatus of lexical functions, is one such module. We describe the general layout of the paraphrase generator and discuss an experiment that demonstrates its potential as a tool for search optimization.

Interactive resolution of intrinsic and translational ambiguity in a machine translation system

The paper presents the module of interactive word sense disambiguation and syntactic ambiguity resolution used within a machine translation system, ETAP-3. The method applied consists in asking the user to identify a word sense, or a syntactic interpretation, whenever the system lacks reliable data to make the choice automatically. In lexical disambiguation, part of man-machine dialogue refers to the analysis phase, while the other part is activated during transfer. For this purpose, entries of the working dictionaries of the system are supplemented with clear diagnostic comments and illustrations that enable the user to choose the most appropriate option and in this way channel the course of system operation.