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- W4313443839 abstract "The NLP relies heavily on question answering. It provides an automated method for retrieving responses from a context. Finding context from several documents, studies, and testimonials is becoming increasingly important. Because NLP models for question answering are quite sophisticated and resource intensive, the purpose of this study is to provide a novel lightweight method to question answering in NLP by introducing the knowledge graph as input to the transfer learning model of T5. This study provides an overall holistic perspective of the suggested model’s various parameters." @default.
- W4313443839 created "2023-01-06" @default.
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- W4313443839 date "2023-01-01" @default.
- W4313443839 modified "2023-10-16" @default.
- W4313443839 title "Combining the Knowledge Graph and T5 in Question Answering in NLP" @default.
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- W4313443839 doi "https://doi.org/10.1007/978-981-19-5443-6_30" @default.
- W4313443839 hasPublicationYear "2023" @default.
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