Papers Relation Classification

Bidirectional Recurrent Convolutional Neural Network for Relation Classification

Context-aware Argumentative Relation Mining

Which argument is more convincing? Analyzing and predicting convincingness of Web arguments using bidirectional LSTM

Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification

Discourse Relation Sense Classification Systems for CoNLL-2016 Shared Task

On the Compositionality and Semantic Interpretation of English Noun Compounds

Combining Lexical and Spatial Knowledge to Predict Spatial Relations between Objects in Images

Learning Semantically and Additively Compositional Distributional Representations

This paper connects a vector-based composition model to a formal semantics, the Dependency-based Compositional Semantics (DCS). We show theoretical evidence that the vector compositions in our model conform to the logic …

Neural Network Models for Implicit Discourse Relation Classification in English and Chinese without Surface Features

Inferring implicit discourse relations in natural language text is the most difficult subtask in discourse parsing. Surface features achieve good performance, but they are not readily applicable to other languages withou…

A Latent Variable Recurrent Neural Network for Discourse-Driven Language Models

Dependency Based Embeddings for Sentence Classification Tasks

VUACLTL at SemEval 2016 Task 12: A CRF Pipeline to Clinical TempEval

Combining Recurrent and Convolutional Neural Networks for Relation Classification

This paper investigates two different neural architectures for the task of relation classification: convolutional neural networks and recurrent neural networks. For both models, we demonstrate the effect of different arc…

Semantic Annotation of the ACL Anthology Corpus for the Automatic Analysis of Scientific Literature

This paper describes the process of creating a corpus annotated for concepts and semantic relations in the scientific domain. A part of the ACL Anthology Corpus was selected for annotation, but the annotation process its…

Comparing Convolutional Neural Networks to Traditional Models for Slot Filling

We address relation classification in the context of slot filling, the task of finding and evaluating fillers like "Steve Jobs" for the slot X in "X founded Apple". We propose a convolutional neural network which splits …

Implicit Discourse Relation Classification via Multi-Task Neural Networks

Without discourse connectives, classifying implicit discourse relations is a challenging task and a bottleneck for building a practical discourse parser. Previous research usually makes use of one kind of discourse frame…

A Latent Variable Recurrent Neural Network for Discourse Relation Language Models

This paper presents a novel latent variable recurrent neural network architecture for jointly modeling sequences of words and (possibly latent) discourse relations between adjacent sentences. A recurrent neural network g…

Improved Relation Classification by Deep Recurrent Neural Networks with Data Augmentation

Nowadays, neural networks play an important role in the task of relation classification. By designing different neural architectures, researchers have improved the performance to a large extent in comparison with traditi…

End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures

We present a novel end-to-end neural model to extract entities and relations between them. Our recurrent neural network based model captures both word sequence and dependency tree substructure information by stacking bid…

Normalization of Relative and Incomplete Temporal Expressions in Clinical Narratives

We analyze the RI-TIMEXes in temporally annotated corpora and propose two hypotheses regarding the normalization of RI-TIMEXes in the clinical narrative domain: the anchor point hypothesis and the anchor relation hypothe…