18595675. APPARATUS AND METHOD FOR DEEP LEARNING-BASED COREFERENCE RESOLUTION USING DEPENDENCY RELATION simplified abstract (Electronics and Telecommunications Research Institute)
Contents
APPARATUS AND METHOD FOR DEEP LEARNING-BASED COREFERENCE RESOLUTION USING DEPENDENCY RELATION
Organization Name
Electronics and Telecommunications Research Institute
Inventor(s)
Joon Young Jung of Daejeon (KR)
APPARATUS AND METHOD FOR DEEP LEARNING-BASED COREFERENCE RESOLUTION USING DEPENDENCY RELATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18595675 titled 'APPARATUS AND METHOD FOR DEEP LEARNING-BASED COREFERENCE RESOLUTION USING DEPENDENCY RELATION
The present invention involves an apparatus and method for deep learning-based coreference resolution using a dependency relation.
- Training data generation module extracts natural language sentences from a paragraph and performs dependency parsing.
- Embedding module generates an integrated embedding vector for the natural language paragraph based on the sentences and dependency relation data.
- Coreference resolution module trains a deep learning neural network to generate a coreference resolution model based on the integrated embedding vector and a first coreference mention preset.
- Potential Applications:
This technology can be applied in natural language processing, information retrieval systems, chatbots, and machine translation.
- Problems Solved:
This innovation addresses the challenge of resolving coreferences in natural language text, improving the accuracy and efficiency of language processing systems.
- Benefits:
- Enhanced accuracy in identifying coreferences in text - Improved performance of natural language processing systems - Streamlined information retrieval processes
- Commercial Applications:
This technology can be utilized in AI-powered chatbots, search engines, language translation services, and content recommendation systems.
- Prior Art:
Researchers can explore prior studies on deep learning-based coreference resolution and dependency parsing techniques in natural language processing.
- Frequently Updated Research:
Stay updated on advancements in deep learning models for coreference resolution and the integration of dependency relations in language processing systems.
- Questions about Coreference Resolution:
1. How does deep learning improve coreference resolution accuracy? 2. What are the key challenges in implementing dependency parsing for coreference resolution?
Original Abstract Submitted
The present invention relates to an apparatus and method for deep learning-based coreference resolution using a dependency relation. An apparatus for deep learning-based coreference resolution according to the present invention includes a training data generation module that extracts one or more natural language sentences from a natural language paragraph and performs dependency parsing on the natural language sentences to generate dependency relation data of the natural language sentences, an embedding module that generates an integrated embedding vector for the natural language paragraph based on the natural language sentence and the dependency relation data, and a coreference resolution module that trains a deep learning neural network based on the integrated embedding vector and a first coreference mention preset for the natural language paragraph to generate a coreference resolution model.
