LOME: Large ontology multilingual extraction

P Xia, G Qin, S Vashishtha, Y Chen, T Chen… - arXiv preprint arXiv …, 2021 - arxiv.org
We present LOME, a system for performing multilingual information extraction. Given a text
document as input, our core system identifies spans of textual entity and event mentions with …

DeepPavlov dream: platform for building generative AI assistants

D Zharikova, D Kornev, F Ignatov… - Proceedings of the …, 2023 - aclanthology.org
Abstract An open-source DeepPavlov Dream Platform is specifically tailored for
development of complex dialog systems like Generative AI Assistants. The stack prioritizes …

[PDF][PDF] Efficient Neural Methods for Coreference Resolution

P Xia - 2022 - jscholarship.library.jhu.edu
Coreference resolution is a core task in natural language processing and in creating
language technologies. Neural methods and models for automatically resolving references …

[HTML][HTML] Deep Neural Network Models for Sequence Labeling and Coreference Tasks/Глубокие нейросетевые модели для задач разметки последовательности и …

ЛТ Ань - 2020 - dissercat.com
Deep neural network models have recently received tremendous attentions from both
academy and industry, and of course, garnered amazing results in a variety of domains …

Using Thesaurus Data to Improve Coreference Resolution for Russian

I Azerkovich - Proceedings of the 10th Global Wordnet Conference, 2019 - aclanthology.org
Semantic information about entities, specifically, how close in meaning two mentions are to
each other, can become very useful for the task of co-reference resolution. One of the most …

[引用][C] ДИЗАССЕМБЛИРОВАНИЕ ИЛИ ЯЗЫКОВАЯ МОДЕЛЬ ИСПОЛНИМЫХ КОДОВ

АС Монасова - Молодежная наука в XXI веке: традиции, инновации …, 2021 - elibrary.ru
В статье раскрыты основные принципы дизассемблирования. Рассмотрен метод
скрытой однородной модели Маркова, как решения проблемы по разделению …

[引用][C] DEEP NEURAL NETWORK MODELS FOR SEQUENCE LABELING AND COREFERENCE TASKS

BM Sergeevich