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Recent progress in leveraging deep learning methods for question answering
Question answering, serving as one of important tasks in natural language processing,
enables machines to understand questions in natural language and answer the questions …
enables machines to understand questions in natural language and answer the questions …
Chinese clinical named entity recognition via multi-head self-attention based BiLSTM-CRF
Plug-and-play knowledge injection for pre-trained language models
Z Zhang, Z Zeng, Y Lin, H Wang, D Ye, C ** with a type taxonomy: a systematic review
Fine-grained entity ty** (FGET) is an important natural language processing (NLP) task. It
is to assign fine-grained semantic types of a type taxonomy (eg, Person/artist/actor) to entity …
is to assign fine-grained semantic types of a type taxonomy (eg, Person/artist/actor) to entity …
A neighborhood-attention fine-grained entity ty** for knowledge graph completion
Knowledge graph (KG) entity ty** focuses on inferring possible entity type instances,
which is a significant subtask of knowledge graph completion (KGC). Existing entity ty** …
which is a significant subtask of knowledge graph completion (KGC). Existing entity ty** …
CORE: A knowledge graph entity type prediction method via complex space regression and embedding
Entity type prediction is an important problem in knowledge graph (KG) research. A new KG
entity type prediction method, named CORE (COmplex space Regression and E mbedding) …
entity type prediction method, named CORE (COmplex space Regression and E mbedding) …