ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings

In this paper we describe our system for SemEval-2018 Task 7 on classification of semantic relations in scientific literature for clean (subtask 1.1) and noisy data (subtask 1.2). We compare two models for classification, a C-LSTM which utilizes only word embeddings and an SVM that also takes handcrafted features into account. To adapt to the domain of science we train word embeddings on scientific papers collected from arXiv.org. The hand-crafted features consist of lexical features to model the semantic relations as well as the entities between which the relation holds. Classification of Relations using Embeddings (ClaiRE) achieved an F1 score of 74.89% for the first subtask and 78.39% for the second.

[1]  Sanda M. Harabagiu,et al.  UTD: Classifying Semantic Relations by Combining Lexical and Semantic Resources , 2010, *SEMEVAL.

[2]  Chih-Jen Lin,et al.  Probability Estimates for Multi-class Classification by Pairwise Coupling , 2003, J. Mach. Learn. Res..

[3]  Makoto Miwa,et al.  End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures , 2016, ACL.

[4]  Dongyan Zhao,et al.  Semantic Relation Classification via Convolutional Neural Networks with Simple Negative Sampling , 2015, EMNLP.

[5]  Martha Palmer,et al.  Verbnet: a broad-coverage, comprehensive verb lexicon , 2005 .

[6]  Jason Weston,et al.  Reading Wikipedia to Answer Open-Domain Questions , 2017, ACL.

[7]  Andreas Hotho,et al.  ClaiRE at SemEval-2018 Task 7 - Extended Version , 2018, ArXiv.

[8]  Jeffrey Dean,et al.  Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.

[9]  Bowen Zhou,et al.  Classifying Relations by Ranking with Convolutional Neural Networks , 2015, ACL.

[10]  Jeffrey Pennington,et al.  GloVe: Global Vectors for Word Representation , 2014, EMNLP.

[11]  Chen Lin,et al.  Neural Temporal Relation Extraction , 2017, EACL.

[12]  Petr Sojka,et al.  Software Framework for Topic Modelling with Large Corpora , 2010 .

[13]  Zhiyuan Liu,et al.  A C-LSTM Neural Network for Text Classification , 2015, ArXiv.

[14]  Yoon Kim,et al.  Convolutional Neural Networks for Sentence Classification , 2014, EMNLP.

[15]  Behrang Q. Zadeh,et al.  SemEval-2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers , 2018, *SEMEVAL.