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Found 5 papers, 1 papers with code
DeepREF: A Framework for Optimized Deep Learning-based Relation Classification
There are many studies in this subarea of NLP that continue to be explored, such as SemEval campaigns (2010 to 2018), or DDI Extraction (2013). For more than ten years, different RE systems using mainly statistical models have been proposed as well as the frameworks to develop them.
DeepNLPF: A Framework for Integrating Third Party NLP Tools
Natural Language Processing (NLP) of textual data is usually broken down into a sequence of several subtasks, where the output of one the subtasks becomes the input to the following one, which constitutes an NLP pipeline.
A logic-based relational learning approach to relation extraction: The OntoILPER system
In this work, we present OntoILPER, a logic-based relational learning approach to Relation Extraction that uses Inductive Logic Programming for generating extraction models in the form of symbolic extraction rules.
The Impact of Semantic Linguistic Features in Relation Extraction: A Logical Relational Learning Approach
Relation Extraction (RE) consists in detecting and classifying semantic relations between entities in a sentence.
R\'esum\'e automatique guid\'e de textes: \'Etat de l'art et perspectives (Guided Summarization : State-of-the-art and perspectives )
Dans ce contexte, le r{\'e}sum{\'e} guid{\'e} d{\'e}fini par la campagne d{'}{\'e}valuation internationale TAC (Text Analysis Conference) en 2010, vise {\`a} encourager la recherche sur ce type d{'}approche, en se basant sur des techniques d{'}analyse en profondeur de textes.
