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Turing at SemEval-2017 Task 8: Sequential Approach to Rumour StanceClassif i cation with Branch-LSTMElena Kochkina 12 , Maria Liakata 12 , Isabelle Augenstein 31University of Warwick, Coventry, United Kingdom2Alan Turing Institute, London, United Kingdom3University College London, London, United...
Vechtomova, UWaterloo at SemEval-2017 Task 8: Detect- ing Stance towards Rumours with Topic Independent Features, in: Proceed- ings of SemEval, ACL, 2017, pp. 461-464.Hareesh Bahuleyan and Olga Vechtomova. 2017. Uwaterloo at semeval-2017 task 8: Detecting stance towards rumours with ...
This paper describes the system developed for SemEval 2017 task 6: #HashTagWars -Learning a Sense of Humor. Learning to recognize sense of humor is the important task for language understanding applications. Different set of features based on frequency of words, structure of tweets and semantics...
We describe the SemEval task of extracting keyphrases and relations between them from scientific documents, which is crucial for understanding which publications describe which processes, tasks and materials. Although this was a new task, we had a total of 26 submissions across 3 evaluation scenarios...
Neobility at SemEval-2017 Task 1: An Attention-based SentenceSimilarity ModelWenLi Zhuang∗Shan-Si Elementary SchoolChangHua County, Taiwanbibo9901@gmail.comErnie ChangDepartment of LinguisticsUniversity of WashingtonSeattle, WA 98195, USAcyc025@uw.eduAbstractThis paper describes a neural-networkmodel ...
SemEval-2017 Task 4 Sentiment Analysis in Twitter Introduction SemEval-2017 Task 4is a text sentiment classification task: Given a message, classify whether the message is of positive, negative, or neutral sentiment. Run Experiments #install the environmentconda create -n allennlp python=3.6sourceac...
puns. The task will occur as part of the SemEval-2017 workshop, to be collocated with the 55th Annual Meeting of the Association for Computational Linguistics in Vancouver, Canada on August 3-4, 2017. SemEval is an ongoing series of evaluations of computational ...
SiTAKA at SemEval-2017 Task 4: Sentiment Analysis in Twitter Based on a Rich Set of Features M Jabreel,A Moreno - Meeting of the Association for Computational Linguistics 被引量: 0发表: 2017年 SemEval-2013 Task 2: Sentiment Analysis in Twitter In recent years, sentiment analysis in social...
This paper describes our approach to the SemEval 2017 Task 10: "ExtractingKeyphrases and Relations from Scientific Publications", specifically to Subtask(B): "Classification of identified keyphrases". We explored three differentdeep learning approaches: a character-level convolutional neural network (CN...