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SemEval 2018

195 papers

TRANSRW at SemEval-2018 Task 12: Transforming Semantic Representations for Argument Reasoning Comprehension

Zhimin Chen, Wei Song, Lizhen Liu

Lyb3b at SemEval-2018 Task 12: Ensemble-based Deep Learning Models for Argument Reasoning Comprehension Task

Yongbin Li, Xiaobing Zhou

TakeLab at SemEval-2018 Task12: Argument Reasoning Comprehension with Skip-Thought Vectors

Ana Brassard, Tin Kuculo, Filip Boltužić, Jan Šnajder

Joker at SemEval-2018 Task 12: The Argument Reasoning Comprehension with Neural Attention

Guobin Sui, Wenhan Chao, Zhunchen Luo

UniMelb at SemEval-2018 Task 12: Generative Implication using LSTMs, Siamese Networks and Semantic Representations with Synonym Fuzzing

Anirudh Joshi, Tim Baldwin, Richard O. Sinnott, Cecile Paris

YNU Deep at SemEval-2018 Task 12: A BiLSTM Model with Neural Attention for Argument Reasoning Comprehension

Peng Ding, Xiaobing Zhou

HHU at SemEval-2018 Task 12: Analyzing an Ensemble-based Deep Learning Approach for the Argument Mining Task of Choosing the Correct Warrant

Matthias Liebeck, Andreas Funke, Stefan Conrad

YNU-HPCC at SemEval-2018 Task 12: The Argument Reasoning Comprehension Task Using a Bi-directional LSTM with Attention Model

Quanlei Liao, Xutao Yang, Jin Wang, Xuejie Zhang

BLCU_NLP at SemEval-2018 Task 12: An Ensemble Model for Argument Reasoning Based on Hierarchical Attention

Meiqian Zhao, Chunhua Liu, LU LIU, Yan Zhao, Dong Yu

NLITrans at SemEval-2018 Task 12: Transfer of Semantic Knowledge for Argument Comprehension

Timothy Niven, Hung-Yu Kao

ECNU at SemEval-2018 Task 12: An End-to-End Attention-based Neural Network for the Argument Reasoning Comprehension Task

Junfeng Tian, Man Lan, Yuanbin Wu

ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention

Wenjie Liu, Chengjie Sun, Lei Lin, Bingquan Liu

SNU_IDS at SemEval-2018 Task 12: Sentence Encoder with Contextualized Vectors for Argument Reasoning Comprehension

Taeuk Kim, Jihun Choi, Sang-goo Lee

MITRE at SemEval-2018 Task 11: Commonsense Reasoning without Commonsense Knowledge

Elizabeth Merkhofer, John Henderson, David Bloom, Laura Strickhart, Guido Zarrella

Lyb3b at SemEval-2018 Task 11: Machine Comprehension Task using Deep Learning Models

Yongbin Li, Xiaobing Zhou

IUCM at SemEval-2018 Task 11: Similar-Topic Texts as a Comprehension Knowledge Source

Sofia Reznikova, Leon Derczynski

Jiangnan at SemEval-2018 Task 11: Deep Neural Network with Attention Method for Machine Comprehension Task

Jiangnan Xia

YNU-HPCC at Semeval-2018 Task 11: Using an Attention-based CNN-LSTM for Machine Comprehension using Commonsense Knowledge

Hang Yuan, Jin Wang, Xuejie Zhang

CSReader at SemEval-2018 Task 11: Multiple Choice Question Answering as Textual Entailment

Zhengping Jiang, Qi Sun

ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task

Yixuan Sheng, Man Lan, Yuanbin Wu

YNU_Deep at SemEval-2018 Task 11: An Ensemble of Attention-based BiLSTM Models for Machine Comprehension

Peng Ding, Xiaobing Zhou

YNU_AI1799 at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge of Different model ensemble

Qingxun Liu, Hongdou Yao, Xaobing Zhou, Ge Xie

ELiRF-UPV at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge

José-Ángel González, Lluís-F. Hurtado, Encarna Segarra, Ferran Pla

NTU NLP Lab System at SemEval-2018 Task 10: Verifying Semantic Differences by Integrating Distributional Information and Expert Knowledge

Yow-Ting Shiue, Hen-Hsen Huang, Hsin-Hsi Chen

UMD at SemEval-2018 Task 10: Can Word Embeddings Capture Discriminative Attributes?

Alexander Zhang, Marine Carpuat

ABDN at SemEval-2018 Task 10: Recognising Discriminative Attributes using Context Embeddings and WordNet

Rui Mao, Guanyi Chen, Ruizhe Li, Chenghua Lin

UNBNLP at SemEval-2018 Task 10: Evaluating unsupervised approaches to capturing discriminative attributes

Milton King, Ali Hakimi Parizi, Paul Cook

Discriminator at SemEval-2018 Task 10: Minimally Supervised Discrimination

Artur Kulmizev, Mostafa Abdou, Vinit Ravishankar, Malvina Nissim

AmritaNLP at SemEval-2018 Task 10: Capturing discriminative attributes using convolution neural network over global vector representation.

Vivek Vinayan, Anand Kumar M, Soman K P

ECNU at SemEval-2018 Task 10: Evaluating Simple but Effective Features on Machine Learning Methods for Semantic Difference Detection

Yunxiao Zhou, Man Lan, Yuanbin Wu

Igevorse at SemEval-2018 Task 10: Exploring an Impact of Word Embeddings Concatenation for Capturing Discriminative Attributes

Maxim Grishin

BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes

Enrico Santus, Chris Biemann, Emmanuele Chersoni

Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational Knowledge

Robyn Speer, Joanna Lowry-Duda

UNAM at SemEval-2018 Task 10: Unsupervised Semantic Discriminative Attribute Identification in Neural Word Embedding Cones

Ignacio Arroyo-Fernández, Ivan Meza, Carlos-Francisco Méndez-Cruz

Wolves at SemEval-2018 Task 10: Semantic Discrimination based on Knowledge and Association

Shiva Taslimipoor, Omid Rohanian, Le An Ha, Gloria Corpas Pastor, Ruslan Mitkov

ELiRF-UPV at SemEval-2018 Task 10: Capturing Discriminative Attributes with Knowledge Graphs and Wikipedia

José-Ángel González, Lluís-F. Hurtado, Encarna Segarra, Ferran Pla

ALB at SemEval-2018 Task 10: A System for Capturing Discriminative Attributes

Bogdan Dumitru, Alina Maria Ciobanu, Liviu P. Dinu

THU_NGN at SemEval-2018 Task 10: Capturing Discriminative Attributes with MLP-CNN model

Chuhan Wu, Fangzhao Wu, Sixing Wu, Zhigang Yuan, Yongfeng Huang

CitiusNLP at SemEval-2018 Task 10: The Use of Transparent Distributional Models and Salient Contexts to Discriminate Word Attributes

Pablo Gamallo

GHH at SemEval-2018 Task 10: Discovering Discriminative Attributes in Distributional Semantics

Mohammed Attia, Younes Samih, Manaal Faruqui, Wolfgang Maier

Meaning_space at SemEval-2018 Task 10: Combining explicitly encoded knowledge with information extracted from word embeddings

Pia Sommerauer, Antske Fokkens, Piek Vossen

UWB at SemEval-2018 Task 10: Capturing Discriminative Attributes from Word Distributions

Tomáš Brychcín, Tomáš Hercig, Josef Steinberger, Michal Konkol

300-sparsans at SemEval-2018 Task 9: Hypernymy as interaction of sparse attributes

Gábor Berend, Márton Makrai, Peter Foldiak

ADAPT at SemEval-2018 Task 9: Skip-Gram Word Embeddings for Unsupervised Hypernym Discovery in Specialised Corpora

Alfredo Maldonado, Filip Klubička

EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery

Ahmad Issa Alaa Aldine, Mounira Harzallah, Giuseppe Berio, Nicolas Béchet, Ahmad Faour

UMDuluth-CS8761 at SemEval-2018 Task9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings

Arshia Zernab Hassan, Manikya Swathi Vallabhajosyula, Ted Pedersen

NLP_HZ at SemEval-2018 Task 9: a Nearest Neighbor Approach

Wei Qiu, Mosha Chen, Linlin Li, Luo Si

SJTU-NLP at SemEval-2018 Task 9: Neural Hypernym Discovery with Term Embeddings

Zhuosheng Zhang, Jiangtong Li, Hai Zhao, Bingjie Tang

Apollo at SemEval-2018 Task 9: Detecting Hypernymy Relations Using Syntactic Dependencies

Mihaela Onofrei, Ionuț Hulub, Diana Trandabat, Daniela Gifu

Digital Operatives at SemEval-2018 Task 8: Using dependency features for malware NLP

Chris Brew

Flytxt_NTNU at SemEval-2018 Task 8: Identifying and Classifying Malware Text Using Conditional Random Fields and Naïve Bayes Classifiers

Utpal Kumar Sikdar, Biswanath Barik, Björn Gambäck

Villani at SemEval-2018 Task 8: Semantic Extraction from Cybersecurity Reports using Representation Learning

Pablo Loyola, Kugamoorthy Gajananan, Yuji Watanabe, Fumiko Satoh

UMBC at SemEval-2018 Task 8: Understanding Text about Malware

Ankur Padia, Arpita Roy, Taneeya Satyapanich, Francis Ferraro, Shimei Pan

HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports

Mingming Fu, Xuemin Zhao, Yonghong Yan

TeamDL at SemEval-2018 Task 8: Cybersecurity Text Analysis using Convolutional Neural Network and Conditional Random Fields

Manikandan R, Krishna Madgula, Snehanshu Saha

Talla at SemEval-2018 Task 7: Hybrid Loss Optimization for Relation Classification using Convolutional Neural Networks

Bhanu Pratap, Daniel Shank, Oladipo Ositelu, Byron Galbraith

NTNU at SemEval-2018 Task 7: Classifier Ensembling for Semantic Relation Identification and Classification in Scientific Papers

Biswanath Barik, Utpal Kumar Sikdar, Björn Gambäck

SciREL at SemEval-2018 Task 7: A System for Semantic Relation Extraction and Classification

Darshini Mahendran, Chathurika Brahmana, Bridget McInnes

NEUROSENT-PDI at SemEval-2018 Task 7: Discovering Textual Relations With a Neural Network Model

Mauro Dragoni

TakeLab at SemEval-2018 Task 7: Combining Sparse and Dense Features for Relation Classification in Scientific Texts

Martin Gluhak, Maria Pia Di Buono, Abbas Akkasi, Jan Šnajder

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

Lena Hettinger, Alexander Dallmann, Albin Zehe, Thomas Niebler, Andreas Hotho

GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification

Sean MacAvaney, Luca Soldaini, Arman Cohan, Nazli Goharian

UniMa at SemEval-2018 Task 7: Semantic Relation Extraction and Classification from Scientific Publications

Thorsten Keiper, Zhonghao Lyu, Sara Pooladzadeh, Yuan Xu, Jingyi Zhang

Texterra at SemEval-2018 Task 7: Exploiting Syntactic Information for Relation Extraction and Classification in Scientific Papers

Andrey Sysoev, Vladimir Mayorov

Bf3R at SemEval-2018 Task 7: Evaluating Two Relation Extraction Tools for Finding Semantic Relations in Biomedical Abstracts

Mariana Neves, Daniel Butzke, Gilbert Schönfelder, Barbara Grune

IRCMS at SemEval-2018 Task 7 : Evaluating a basic CNN Method and Traditional Pipeline Method for Relation Classification

Zhongbo Yin, Zhunchen Luo, Wei Luo, Mao Bin, Changhai Tian

SIRIUS-LTG-UiO at SemEval-2018 Task 7: Convolutional Neural Networks with Shortest Dependency Paths for Semantic Relation Extraction and Classification in Scientific Papers

Farhad Nooralahzadeh, Lilja Øvrelid, Jan Tore Lønning

MIT-MEDG at SemEval-2018 Task 7: Semantic Relation Classification via Convolution Neural Network

Di Jin, Franck Dernoncourt, Elena Sergeeva, Matthew McDermott, Geeticka Chauhan

UC3M-NII Team at SemEval-2018 Task 7: Semantic Relation Classification in Scientific Papers via Convolutional Neural Network

Víctor Suárez-Paniagua, Isabel Segura-Bedmar, Akiko Aizawa

The UWNLP system at SemEval-2018 Task 7: Neural Relation Extraction Model with Selectively Incorporated Concept Embeddings

Yi Luan, Mari Ostendorf, Hannaneh Hajishirzi

OhioState at SemEval-2018 Task 7: Exploiting Data Augmentation for Relation Classification in Scientific Papers Using Piecewise Convolutional Neural Networks

Dushyanta Dhyani

LightRel at SemEval-2018 Task 7: Lightweight and Fast Relation Classification

Tyler Renslow, Günter Neumann

GIST at SemEval-2018 Task 12: A network transferring inference knowledge to Argument Reasoning Comprehension task

HongSeok Choi, Hyunju Lee

SemEval-2018 Task 12: The Argument Reasoning Comprehension Task

Ivan Habernal, Henning Wachsmuth, Iryna Gurevych, Benno Stein

Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine Comprehension

Liang Wang, Meng Sun, Wei Zhao, Kewei Shen, Jingming Liu

SemEval-2018 Task 11: Machine Comprehension Using Commonsense Knowledge

Simon Ostermann, Michael Roth, Ashutosh Modi, Stefan Thater, Manfred Pinkal

SUNNYNLP at SemEval-2018 Task 10: A Support-Vector-Machine-Based Method for Detecting Semantic Difference using Taxonomy and Word Embedding Features

Sunny Lai, Kwong Sak Leung, Yee Leung

SemEval-2018 Task 10: Capturing Discriminative Attributes

Alicia Krebs, Alessandro Lenci, Denis Paperno

CRIM at SemEval-2018 Task 9: A Hybrid Approach to Hypernym Discovery

Gabriel Bernier-Colborne, Caroline Barrière

SemEval-2018 Task 9: Hypernym Discovery

Jose Camacho-Collados, Claudio Delli Bovi, Luis Espinosa-Anke, Sergio Oramas, Tommaso Pasini

DM_NLP at SemEval-2018 Task 8: neural sequence labeling with linguistic features

Chunping Ma, Huafei Zheng, Pengjun Xie, Chen Li, Linlin Li

SemEval-2018 Task 8: Semantic Extraction from CybersecUrity REports using Natural Language Processing (SecureNLP)

Peter Phandi, Amila Silva, Wei Lu

ETH-DS3Lab at SemEval-2018 Task 7: Effectively Combining Recurrent and Convolutional Neural Networks for Relation Classification and Extraction

Jonathan Rotsztejn, Nora Hollenstein, Ce Zhang

SemEval-2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers

Kata Gábor, Davide Buscaldi, Anne-Kathrin Schumann, Behrang QasemiZadeh, Haïfa Zargayouna

NAI-SEA at SemEval-2018 Task 5: An Event Search System

Yingchi Liu, Quanzhi Li, Luo Si

FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System

Carla Abreu, Eugénio Oliveira

NewsReader at SemEval-2018 Task 5: Counting events by reasoning over event-centric-knowledge-graphs

Piek Vossen

KNU CI System at SemEval-2018 Task4: Character Identification by Solving Sequence-Labeling Problem

Cheoneum Park, Heejun Song, Changki Lee

#NonDicevoSulSerio at SemEval-2018 Task 3: Exploiting Emojis and Affective Content for Irony Detection in English Tweets

Endang Wahyu Pamungkas, Viviana Patti

ValenTO at SemEval-2018 Task 3: Exploring the Role of Affective Content for Detecting Irony in English Tweets

Delia Irazú Hernández Farías, Viviana Patti, Paolo Rosso

NLPRL-IITBHU at SemEval-2018 Task 3: Combining Linguistic Features and Emoji pre-trained CNN for Irony Detection in Tweets

Harsh Rangwani, Devang Kulshreshtha, Anil Kumar Singh

SSN MLRG1 at SemEval-2018 Task 3: Irony Detection in English Tweets Using MultiLayer Perceptron

Rajalakshmi S, Angel Deborah S, S Milton Rajendram, Mirnalinee T T

Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection

Nishant Nikhil, Muktabh Mayank Srivastava

YNU-HPCC at SemEval-2018 Task 3: Ensemble Neural Network Models for Irony Detection on Twitter

Bo Peng, Jin Wang, Xuejie Zhang

NTUA-SLP at SemEval-2018 Task 3: Tracking Ironic Tweets using Ensembles of Word and Character Level Attentive RNNs

Christos Baziotis, Athanasiou Nikolaos, Pinelopi Papalampidi, Athanasia Kolovou, Georgios Paraskevopoulos

KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection

Luise Dürlich

ECNU at SemEval-2018 Task 3: Exploration on Irony Detection from Tweets via Machine Learning and Deep Learning Methods

Zhenghang Yin, Feixiang Wang, Man Lan, WenTing Wang

INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter

Delia Irazú Hernández Farías, Fernando Sanchez-Vega, Manuel Montes-y-Gómez, Paolo Rosso

Lancaster at SemEval-2018 Task 3: Investigating Ironic Features in English Tweets

Edward Dearden, Alistair Baron

Irony Detector at SemEval-2018 Task 3: Irony Detection in English Tweets using Word Graph

Usman Ahmed, Lubna Zafar, Faiza Qayyum, Muhammad Arshad Islam