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Relation Extraction

82 papers with code · Natural Language Processing

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A Hierarchical Multi-task Approach for Learning Embeddings from Semantic Tasks

14 Nov 2018huggingface/hmtl

The model is trained in a hierarchical fashion to introduce an inductive bias by supervising a set of low level tasks at the bottom layers of the model and more complex tasks at the top layers of the model.

MULTI-TASK LEARNING NAMED ENTITY RECOGNITION (NER) RELATION EXTRACTION

Simplifying Graph Convolutional Networks

19 Feb 2019stellargraph/stellargraph

Graph Convolutional Networks (GCNs) and their variants have experienced significant attention and have become the de facto methods for learning graph representations.

IMAGE CLASSIFICATION RELATION EXTRACTION SENTIMENT ANALYSIS TEXT CLASSIFICATION

BioBERT: a pre-trained biomedical language representation model for biomedical text mining

25 Jan 2019dmis-lab/biobert

However, as deep learning models require a large amount of training data, applying deep learning to biomedical text mining is often unsuccessful due to the lack of training data in biomedical fields.

MEDICAL NAMED ENTITY RECOGNITION MEDICAL RELATION EXTRACTION QUESTION ANSWERING RELATION EXTRACTION SENTENCE CLASSIFICATION

Indirect Supervision for Relation Extraction using Question-Answer Pairs

30 Oct 2017shanzhenren/CoType

However, due to the incompleteness of knowledge bases and the context-agnostic labeling, the training data collected via distant supervision (DS) can be very noisy.

QUESTION ANSWERING RELATION EXTRACTION

CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases

27 Oct 2016shanzhenren/CoType

We propose a novel domain-independent framework, called CoType, that runs a data-driven text segmentation algorithm to extract entity mentions, and jointly embeds entity mentions, relation mentions, text features and type labels into two low-dimensional spaces (for entity and relation mentions respectively), where, in each space, objects whose types are close will also have similar representations.

RELATION EXTRACTION

Context-Aware Representations for Knowledge Base Relation Extraction

EMNLP 2017 UKPLab/emnlp2017-relation-extraction

We demonstrate that for sentence-level relation extraction it is beneficial to consider other relations in the sentential context while predicting the target relation.

QUESTION ANSWERING RELATION EXTRACTION