Использование мер семантической близости для распознавания кореференции в русском языке

Статья посвящена описанию серии экспериментов по исследованию роли семантической информации в разрешении кореферентных связей для русского языка, ее использованию в системах автоматического анализа текстов и оценке результатов их работы. Целью первого этапа экспериментов было определить, какие метрики семантической близости между референциальными выражениями больше соответствуют кореферентным связям между ними. Подсчет метрик производился на материале русской Википедии и тезауруса RuThes. На втором этапе была разработана система автоматического распознавания кореферентности, использующая метрики семантической близости в качестве признаков для машинного обучения, и оценено качество ее работы. Результаты проведенных экспериментов позволяют установить метрики семантической близости, подходящие для использования в системах разрешения кореферентности, а также демонстрируют повышение качества работы подобных систем при использовании семантической информации.

автоматическая обработка естественного языка, распознавание кореферентности, метрики семантической близости, машинное обучение, русский язык

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