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)。
-
Updated
Mar 9, 2022 - JavaScript
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)。
[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
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
Add a description, image, and links to the relation-detection topic page so that developers can more easily learn about it.
To associate your repository with the relation-detection topic, visit your repo's landing page and select "manage topics."