医药知识图谱自动问答系统实现,包括构建知识图谱、基于知识图谱的流水线问答以及前端实现。实体识别(基于词典+BERT_CRF)、实体链接(Sentence-BERT做匹配)、意图识别(基于提问词+领域词词典)。
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Mar 9, 2022 - JavaScript
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医药知识图谱自动问答系统实现,包括构建知识图谱、基于知识图谱的流水线问答以及前端实现。实体识别(基于词典+BERT_CRF)、实体链接(Sentence-BERT做匹配)、意图识别(基于提问词+领域词词典)。
nlp neo4j django-application knowledge-graph ner echarts entity-linking relation-extraction kgqa kbqa mention-detection pytorch-transformers relation-detection
[NeurIPS 2022 Spotlight] RLIP: Relational Language-Image Pre-training and a series of other methods to solve HOI detection and Scene Graph Generation.
Implementation of BERT-Based Span Entity and Relation Prediction Models for Question Answering over Wikidata
natural-language-processing sparql wikidata transformer question-answering bert relation-detection span-detection
Code for rendering images for NeurRIPS 2020 paper "Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D"
Master Thesis: Extraction of Gateways in Process Model Generation from Text
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