Papers by Bernard Espinasse

2 papers
DeepNLPF: A Framework for Integrating Third Party NLP Tools (2020.lrec-1)

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Challenge: Many third-party NLP tools perform distinct NLP subtasks, but integration is difficult . authors present a framework that enables easy integration of third-parties into a pipeline .
Approach: They propose a framework that enables easy integration of third-party NLP tools . it provides an API for complete pipeline customization including definition of input/output formats .
Outcome: The proposed framework reduces runtime processing time compared to executing the same pipeline in a sequential manner.
DeepREF: A Framework for Optimized Deep Learning-based Relation Classification (2022.lrec-1)

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Challenge: Existing frameworks for relation extraction (RE) are limited due to lack of implementation details.
Approach: They propose to use deep learning to develop relation extraction systems using deep learning models.
Outcome: The proposed framework is inspired by the OpenNRE and REflex existing frameworks.

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