Lexical and Computational Semantics and Semantic Evaluation (formerly Workshop on Sense Evaluation) (2018)


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pdf (full)bib Proceedings of The 12th International Workshop on Semantic Evaluation

pdf bib Proceedings of The 12th International Workshop on Semantic Evaluation
[S18-1000]: Marianna Apidianaki | Saif M. Mohammad | Jonathan May | Ekaterina Shutova | Steven Bethard | Marine Carpuat

pdf bib SemEval-2018 Task 1: Affect in Tweets
[S18-1001]: Saif Mohammad | Felipe Bravo-Marquez | Mohammad Salameh | Svetlana Kiritchenko

pdf bib SeerNet at SemEval-2018 Task 1: Domain Adaptation for Affect in Tweets
[S18-1002]: Venkatesh Duppada | Royal Jain | Sushant Hiray

pdf bib SemEval 2018 Task 2: Multilingual Emoji Prediction
[S18-1003]: Francesco Barbieri | Jose Camacho-Collados | Francesco Ronzano | Luis Espinosa Anke | Miguel Ballesteros | Valerio Basile | Viviana Patti | Horacio Saggion

pdf bib Tübingen-Oslo at SemEval-2018 Task 2: SVMs perform better than RNNs in Emoji Prediction
[S18-1004]: Çağrı Çöltekin | Taraka Rama

pdf bib SemEval-2018 Task 3: Irony Detection in English Tweets
[S18-1005]: Cynthia Van Hee | Els Lefever | Veronique Hoste

pdf bib THU_NGN at SemEval-2018 Task 3: Tweet Irony Detection with Densely connected LSTM and Multi-task Learning
[S18-1006]: Chuhan Wu | Fangzhao Wu | Sixing Wu | Junxin Liu | Zhigang Yuan | Yongfeng Huang

pdf bib SemEval 2018 Task 4: Character Identification on Multiparty Dialogues
[S18-1007]: Jinho D. Choi | Henry Y. Chen

pdf bib AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library
[S18-1008]: Laura Aina | Carina Silberer | Ionut-Teodor Sorodoc | Matthijs Westera | Gemma Boleda

pdf bib SemEval-2018 Task 5: Counting Events and Participants in the Long Tail
[S18-1009]: Marten Postma | Filip Ilievski | Piek Vossen

pdf bib KOI at SemEval-2018 Task 5: Building Knowledge Graph of Incidents
[S18-1010]: Paramita Mirza | Fariz Darari | Rahmad Mahendra

pdf bib SemEval 2018 Task 6: Parsing Time Normalizations
[S18-1011]: Egoitz Laparra | Dongfang Xu | Ahmed Elsayed | Steven Bethard | Martha Palmer

pdf bib Chrono at SemEval-2018 Task 6: A System for Normalizing Temporal Expressions
[S18-1012]: Amy Olex | Luke Maffey | Nicholas Morgan | Bridget McInnes

pdf bib NEUROSENT-PDI at SemEval-2018 Task 1: Leveraging a Multi-Domain Sentiment Model for Inferring Polarity in Micro-blog Text
[S18-1013]: Mauro Dragoni

pdf bib FOI DSS at SemEval-2018 Task 1: Combining LSTM States, Embeddings, and Lexical Features for Affect Analysis
[S18-1014]: Maja Karasalo | Mattias Nilsson | Magnus Rosell | Ulrika Wickenberg Bolin

pdf bib NLPZZX at SemEval-2018 Task 1: Using Ensemble Method for Emotion and Sentiment Intensity Determination
[S18-1015]: Zhengxin Zhang | Qimin Zhou | Hao Wu

pdf bib LT3 at SemEval-2018 Task 1: A classifier chain to detect emotions in tweets
[S18-1016]: Luna De Bruyne | Orphee De Clercq | Veronique Hoste

pdf bib SINAI at SemEval-2018 Task 1: Emotion Recognition in Tweets
[S18-1017]: Flor Miriam Plaza del Arco | Salud María Jiménez-Zafra | Maite Martin | L. Alfonso Urena Lopez

pdf bib UWB at SemEval-2018 Task 1: Emotion Intensity Detection in Tweets
[S18-1018]: Pavel Přibáň | Tomáš Hercig | Ladislav Lenc

pdf bib AttnConvnet at SemEval-2018 Task 1: Attention-based Convolutional Neural Networks for Multi-label Emotion Classification
[S18-1019]: Yanghoon Kim | Hwanhee Lee | Kyomin Jung

pdf bib INGEOTEC at SemEval-2018 Task 1: EvoMSA and μTC for Sentiment Analysis
[S18-1020]: Mario Graff | Sabino Miranda-Jiménez | Eric S. Tellez | Daniela Moctezuma

pdf bib Epita at SemEval-2018 Task 1: Sentiment Analysis Using Transfer Learning Approach
[S18-1021]: Guillaume Daval-Frerot | Abdesselam Bouchekif | Anatole Moreau

pdf bib KDE-AFFECT at SemEval-2018 Task 1: Estimation of Affects in Tweet by Using Convolutional Neural Network for n-gram
[S18-1022]: Masaki Aono | Shinnosuke Himeno

pdf bib RNN for Affects at SemEval-2018 Task 1: Formulating Affect Identification as a Binary Classification Problem
[S18-1023]: Aysu Ezen-Can | Ethem F. Can

pdf bib Tw-StAR at SemEval-2018 Task 1: Preprocessing Impact on Multi-label Emotion Classification
[S18-1024]: Hala Mulki | Chedi Bechikh Ali | Hatem Haddad | Ismail Babaoglu

pdf bib DL Team at SemEval-2018 Task 1: Tweet Affect Detection using Sentiment Lexicons and Embeddings
[S18-1025]: Dmitry Kravchenko | Lidia Pivovarova

pdf bib EmoIntens Tracker at SemEval-2018 Task 1: Emotional Intensity Levels in #Tweets
[S18-1026]: Ramona-Andreea Turcu | Sandra Maria Amarandei | Iuliana-Alexandra Fleșcan-Lovin-Arseni | Daniela Gifu | Diana Trandabat

pdf bib uOttawa at SemEval-2018 Task 1: Self-Attentive Hybrid GRU-Based Network
[S18-1027]: Ahmed Husseini Orabi | Mahmoud Husseini Orabi | Diana Inkpen | David Van Bruwaene

pdf bib THU_NGN at SemEval-2018 Task 1: Fine-grained Tweet Sentiment Intensity Analysis with Attention CNN-LSTM
[S18-1028]: Chuhan Wu | Fangzhao Wu | Junxin Liu | Zhigang Yuan | Sixing Wu | Yongfeng Huang

pdf bib EiTAKA at SemEval-2018 Task 1: An Ensemble of N-Channels ConvNet and XGboost Regressors for Emotion Analysis of Tweets
[S18-1029]: Mohammed Jabreel | Antonio Moreno

pdf bib CENTEMENT at SemEval-2018 Task 1: Classification of Tweets using Multiple Thresholds with Self-correction and Weighted Conditional Probabilities
[S18-1030]: Tariq Ahmad | Allan Ramsay | Hanady Ahmed

pdf bib Yuan at SemEval-2018 Task 1: Tweets Emotion Intensity Prediction using Ensemble Recurrent Neural Network
[S18-1031]: Min Wang | Xiaobing Zhou

pdf bib AffecThor at SemEval-2018 Task 1: A cross-linguistic approach to sentiment intensity quantification in tweets
[S18-1032]: Mostafa Abdou | Artur Kulmizev | Joan Ginés i Ametllé

pdf bib Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification
[S18-1033]: Alon Rozental | Daniel Fleischer

pdf bib deepSA2018 at SemEval-2018 Task 1: Multi-task Learning of Different Label for Affect in Tweets
[S18-1034]: Zi Yuan Gao | Chia-Ping Chen

pdf bib ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models
[S18-1035]: Huimin Xu | Man Lan | Yuanbin Wu

pdf bib EMA at SemEval-2018 Task 1: Emotion Mining for Arabic
[S18-1036]: Gilbert Badaro | Obeida El Jundi | Alaa Khaddaj | Alaa Maarouf | Raslan Kain | Hazem Hajj | Wassim El-Hajj

pdf bib NTUA-SLP at SemEval-2018 Task 1: Predicting Affective Content in Tweets with Deep Attentive RNNs and Transfer Learning
[S18-1037]: Christos Baziotis | Athanasiou Nikolaos | Alexandra Chronopoulou | Athanasia Kolovou | Georgios Paraskevopoulos | Nikolaos Ellinas | Shrikanth Narayanan | Alexandros Potamianos

pdf bib CrystalFeel at SemEval-2018 Task 1: Understanding and Detecting Emotion Intensity using Affective Lexicons
[S18-1038]: Raj Kumar Gupta | Yinping Yang

pdf bib PlusEmo2Vec at SemEval-2018 Task 1: Exploiting emotion knowledge from emoji and #hashtags
[S18-1039]: Ji Ho Park | Peng Xu | Pascale Fung

pdf bib YNU-HPCC at SemEval-2018 Task 1: BiLSTM with Attention based Sentiment Analysis for Affect in Tweets
[S18-1040]: You Zhang | Jin Wang | Xuejie Zhang

pdf bib UG18 at SemEval-2018 Task 1: Generating Additional Training Data for Predicting Emotion Intensity in Spanish
[S18-1041]: Marloes Kuijper | Mike van Lenthe | Rik van Noord

pdf bib ISCLAB at SemEval-2018 Task 1: UIR-Miner for Affect in Tweets
[S18-1042]: Meng Li | Zhenyuan Dong | Zhihao Fan | Kongming Meng | Jinghua Cao | Guanqi Ding | Yuhan Liu | Jiawei Shan | Binyang Li

pdf bib TCS Research at SemEval-2018 Task 1: Learning Robust Representations using Multi-Attention Architecture
[S18-1043]: Hardik Meisheri | Lipika Dey

pdf bib DMCB at SemEval-2018 Task 1: Transfer Learning of Sentiment Classification Using Group LSTM for Emotion Intensity prediction
[S18-1044]: Youngmin Kim | Hyunju Lee

pdf bib DeepMiner at SemEval-2018 Task 1: Emotion Intensity Recognition Using Deep Representation Learning
[S18-1045]: Habibeh Naderi | Behrouz Haji Soleimani | Saif Mohammad | Svetlana Kiritchenko | Stan Matwin

pdf bib Zewen at SemEval-2018 Task 1: An Ensemble Model for Affect Prediction in Tweets
[S18-1046]: Zewen Chi | Heyan Huang | Jiangui Chen | Hao Wu | Ran Wei

pdf bib Amrita_student at SemEval-2018 Task 1: Distributed Representation of Social Media Text for Affects in Tweets
[S18-1047]: Nidhin A. Unnithan | Shalini K | Barathi Ganesh H. B. | Anand Kumar M | Soman K P

pdf bib SSN MLRG1 at SemEval-2018 Task 1: Emotion and Sentiment Intensity Detection Using Rule Based Feature Selection
[S18-1048]: Angel Deborah S | Rajalakshmi S | S. Milton Rajendram | Mirnalinee T T

pdf bib CENNLP at SemEval-2018 Task 1: Constrained Vector Space Model in Affects in Tweets
[S18-1049]: Naveen J R | Barathi Ganesh H. B. | Anand Kumar M | Soman K P

pdf bib TeamCEN at SemEval-2018 Task 1: Global Vectors Representation in Emotion Detection
[S18-1050]: Anon George | Barathi Ganesh H. B. | Anand Kumar M | Soman K P

pdf bib IIT Delhi at SemEval-2018 Task 1 : Emotion Intensity Prediction
[S18-1051]: Bhaskar Kotakonda | Prashanth Gowda | Brejesh Lall

pdf bib Mutux at SemEval-2018 Task 1: Exploring Impacts of Context Information On Emotion Detection
[S18-1052]: Pan Du | Jian-Yun Nie

pdf bib TeamUNCC at SemEval-2018 Task 1: Emotion Detection in English and Arabic Tweets using Deep Learning
[S18-1053]: Malak Abdullah | Samira Shaikh

pdf bib RIDDL at SemEval-2018 Task 1: Rage Intensity Detection with Deep Learning
[S18-1054]: Venkatesh Elango | Karan Uppal

pdf bib ARB-SEN at SemEval-2018 Task1: A New Set of Features for Enhancing the Sentiment Intensity Prediction in Arabic Tweets
[S18-1055]: El Moatez Billah Nagoudi

pdf bib psyML at SemEval-2018 Task 1: Transfer Learning for Sentiment and Emotion Analysis
[S18-1056]: Grace Gee | Eugene Wang

pdf bib UIUC at SemEval-2018 Task 1: Recognizing Affect with Ensemble Models
[S18-1057]: Abhishek Avinash Narwekar | Roxana Girju

pdf bib KU-MTL at SemEval-2018 Task 1: Multi-task Identification of Affect in Tweets
[S18-1058]: Thomas Nyegaard-Signori | Casper Veistrup Helms | Johannes Bjerva | Isabelle Augenstein

pdf bib EmoNLP at SemEval-2018 Task 2: English Emoji Prediction with Gradient Boosting Regression Tree Method and Bidirectional LSTM
[S18-1059]: Man Liu

pdf bib UMDSub at SemEval-2018 Task 2: Multilingual Emoji Prediction Multi-channel Convolutional Neural Network on Subword Embedding
[S18-1060]: Zhenduo Wang | Ted Pedersen

pdf bib UMDuluth-CS8761 at SemEval-2018 Task 2: Emojis: Too many Choices?
[S18-1061]: Jonathan Beaulieu | Dennis Asamoah Owusu

pdf bib The Dabblers at SemEval-2018 Task 2: Multilingual Emoji Prediction
[S18-1062]: Larisa Alexa | Alina Lorent | Daniela Gifu | Diana Trandabat

pdf bib THU_NGN at SemEval-2018 Task 2: Residual CNN-LSTM Network with Attention for English Emoji Prediction
[S18-1063]: Chuhan Wu | Fangzhao Wu | Sixing Wu | Zhigang Yuan | Junxin Liu | Yongfeng Huang

pdf bib #TeamINF at SemEval-2018 Task 2: Emoji Prediction in Tweets
[S18-1064]: Alison Ribeiro | Nádia Silva

pdf bib EICA Team at SemEval-2018 Task 2: Semantic and Metadata-based Features for Multilingual Emoji Prediction
[S18-1065]: Yufei Xie | Qingqing Song

pdf bib EmojiIt at SemEval-2018 Task 2: An Effective Attention-Based Recurrent Neural Network Model for Emoji Prediction with Characters Gated Words
[S18-1066]: Shiyun Chen | Maoquan Wang | Liang He

pdf bib Peperomia at SemEval-2018 Task 2: Vector Similarity Based Approach for Emoji Prediction
[S18-1067]: Jing Chen | Dechuan Yang | Xilian Li | Wei Chen | Tengjiao Wang

pdf bib ECNU at SemEval-2018 Task 2: Leverage Traditional NLP Features and Neural Networks Methods to Address Twitter Emoji Prediction Task
[S18-1068]: Xingwu Lu | Xin Mao | Man Lan | Yuanbin Wu

pdf bib NTUA-SLP at SemEval-2018 Task 2: Predicting Emojis using RNNs with Context-aware Attention
[S18-1069]: Christos Baziotis | Athanasiou Nikolaos | Athanasia Kolovou | Georgios Paraskevopoulos | Nikolaos Ellinas | Alexandros Potamianos

pdf bib Hatching Chick at SemEval-2018 Task 2: Multilingual Emoji Prediction
[S18-1070]: Joël Coster | Reinder Gerard van Dalen | Nathalie Adriënne Jacqueline Stierman

pdf bib EPUTION at SemEval-2018 Task 2: Emoji Prediction with User Adaption
[S18-1071]: Liyuan Zhou | Qiongkai Xu | Hanna Suominen | Tom Gedeon

pdf bib PickleTeam! at SemEval-2018 Task 2: English and Spanish Emoji Prediction from Tweets
[S18-1072]: Daphne Groot | Rémon Kruizinga | Hennie Veldthuis | Simon de Wit | Hessel Haagsma

pdf bib YNU-HPCC at SemEval-2018 Task 2: Multi-ensemble Bi-GRU Model with Attention Mechanism for Multilingual Emoji Prediction
[S18-1073]: Nan Wang | Jin Wang | Xuejie Zhang

pdf bib DUTH at SemEval-2018 Task 2: Emoji Prediction in Tweets
[S18-1074]: Dimitrios Effrosynidis | Georgios Peikos | Symeon Symeonidis | Avi Arampatzis

pdf bib TAJJEB at SemEval-2018 Task 2: Traditional Approaches Just Do the Job with Emoji Prediction
[S18-1075]: Angelo Basile | Kenny W. Lino

pdf bib SyntNN at SemEval-2018 Task 2: is Syntax Useful for Emoji Prediction? Embedding Syntactic Trees in Multi Layer Perceptrons
[S18-1076]: Fabio Massimo Zanzotto | Andrea Santilli

pdf bib Duluth UROP at SemEval-2018 Task 2: Multilingual Emoji Prediction with Ensemble Learning and Oversampling
[S18-1077]: Shuning Jin | Ted Pedersen

pdf bib CENNLP at SemEval-2018 Task 2: Enhanced Distributed Representation of Text using Target Classes for Emoji Prediction Representation
[S18-1078]: Naveen J R | Hariharan V | Barathi Ganesh H. B. | Anand Kumar M | Soman K P

pdf bib Manchester Metropolitan at SemEval-2018 Task 2: Random Forest with an Ensemble of Features for Predicting Emoji in Tweets
[S18-1079]: Luciano Gerber | Matthew Shardlow

pdf bib Tweety at SemEval-2018 Task 2: Predicting Emojis using Hierarchical Attention Neural Networks and Support Vector Machine
[S18-1080]: Daniel Kopev | Atanas Atanasov | Dimitrina Zlatkova | Momchil Hardalov | Ivan Koychev | Ivelina Nikolova | Galia Angelova

pdf bib LIS at SemEval-2018 Task 2: Mixing Word Embeddings and Bag of Features for Multilingual Emoji Prediction
[S18-1081]: Gaël Guibon | Magalie Ochs | Patrice Bellot

pdf bib ALANIS at SemEval-2018 Task 3: A Feature Engineering Approach to Irony Detection in English Tweets
[S18-1082]: Kevin Swanberg | Madiha Mirza | Ted Pedersen | Zhenduo Wang

pdf bib NEUROSENT-PDI at SemEval-2018 Task 3: Understanding Irony in Social Networks Through a Multi-Domain Sentiment Model
[S18-1083]: Mauro Dragoni

pdf bib UWB at SemEval-2018 Task 3: Irony detection in English tweets
[S18-1084]: Tomáš Hercig

pdf bib NIHRIO at SemEval-2018 Task 3: A Simple and Accurate Neural Network Model for Irony Detection in Twitter
[S18-1085]: Thanh Vu | Dat Quoc Nguyen | Xuan-Son Vu | Dai Quoc Nguyen | Michael Catt | Michael Trenell

pdf bib LDR at SemEval-2018 Task 3: A Low Dimensional Text Representation for Irony Detection
[S18-1086]: Bilal Ghanem | Francisco Rangel | Paolo Rosso

pdf bib IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets
[S18-1087]: Edison Marrese-Taylor | Suzana Ilic | Jorge Balazs | Helmut Prendinger | Yutaka Matsuo

pdf bib PunFields at SemEval-2018 Task 3: Detecting Irony by Tools of Humor Analysis
[S18-1088]: Elena Mikhalkova | Yuri Karyakin | Alexander Voronov | Dmitry Grigoriev | Artem Leoznov

pdf bib HashCount at SemEval-2018 Task 3: Concatenative Featurization of Tweet and Hashtags for Irony Detection
[S18-1089]: Won Ik Cho | Woo Hyun Kang | Nam Soo Kim

pdf bib WLV at SemEval-2018 Task 3: Dissecting Tweets in Search of Irony
[S18-1090]: Omid Rohanian | Shiva Taslimipoor | Richard Evans | Ruslan Mitkov

pdf bib Random Decision Syntax Trees at SemEval-2018 Task 3: LSTMs and Sentiment Scores for Irony Detection
[S18-1091]: Aidan San

pdf bib ELiRF-UPV at SemEval-2018 Tasks 1 and 3: Affect and Irony Detection in Tweets
[S18-1092]: José-Ángel González | Lluís-F. Hurtado | Ferran Pla

pdf bib IronyMagnet at SemEval-2018 Task 3: A Siamese network for Irony detection in Social media
[S18-1093]: Aniruddha Ghosh | Tony Veale

pdf bib CTSys at SemEval-2018 Task 3: Irony in Tweets
[S18-1094]: Myan Sherif | Sherine Mamdouh | Wegdan Ghazi

pdf bib Irony Detector at SemEval-2018 Task 3: Irony Detection in English Tweets using Word Graph
[S18-1095]: Usman Ahmed | Lubna Zafar | Faiza Qayyum | Muhammad Arshad Islam

pdf bib Lancaster at SemEval-2018 Task 3: Investigating Ironic Features in English Tweets
[S18-1096]: Edward Dearden | Alistair Baron

pdf bib INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter
[S18-1097]: Delia Irazú Hernández Farías | Fernando Sánchez-Vega | Manuel Montes-y-Gómez | Paolo Rosso

pdf bib ECNU at SemEval-2018 Task 3: Exploration on Irony Detection from Tweets via Machine Learning and Deep Learning Methods
[S18-1098]: Zhenghang Yin | Feixiang Wang | Man Lan | Wenting Wang

pdf bib KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection
[S18-1099]: Luise Dürlich

pdf bib NTUA-SLP at SemEval-2018 Task 3: Tracking Ironic Tweets using Ensembles of Word and Character Level Attentive RNNs
[S18-1100]: Christos Baziotis | Athanasiou Nikolaos | Pinelopi Papalampidi | Athanasia Kolovou | Georgios Paraskevopoulos | Nikolaos Ellinas | Alexandros Potamianos

pdf bib YNU-HPCC at SemEval-2018 Task 3: Ensemble Neural Network Models for Irony Detection on Twitter
[S18-1101]: Bo Peng | Jin Wang | Xuejie Zhang

pdf bib Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection
[S18-1102]: Nishant Nikhil | Muktabh Mayank Srivastava

pdf bib SSN MLRG1 at SemEval-2018 Task 3: Irony Detection in English Tweets Using MultiLayer Perceptron
[S18-1103]: Rajalakshmi S | Angel Deborah S | S. Milton Rajendram | Mirnalinee T T

pdf bib NLPRL-IITBHU at SemEval-2018 Task 3: Combining Linguistic Features and Emoji pre-trained CNN for Irony Detection in Tweets
[S18-1104]: Harsh Rangwani | Devang Kulshreshtha | Anil Kumar Singh

pdf bib ValenTO at SemEval-2018 Task 3: Exploring the Role of Affective Content for Detecting Irony in English Tweets
[S18-1105]: Delia Irazú Hernández Farías | Viviana Patti | Paolo Rosso

pdf bib #NonDicevoSulSerio at SemEval-2018 Task 3: Exploiting Emojis and Affective Content for Irony Detection in English Tweets
[S18-1106]: Endang Wahyu Pamungkas | Viviana Patti

pdf bib KNU CI System at SemEval-2018 Task4: Character Identification by Solving Sequence-Labeling Problem
[S18-1107]: Cheoneum Park | Heejun Song | Changki Lee

pdf bib NewsReader at SemEval-2018 Task 5: Counting events by reasoning over event-centric-knowledge-graphs
[S18-1108]: Piek Vossen

pdf bib FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System
[S18-1109]: Carla Abreu | Eugénio Oliveira

pdf bib NAI-SEA at SemEval-2018 Task 5: An Event Search System
[S18-1110]: Yingchi Liu | Quanzhi Li | Luo Si

pdf bib SemEval-2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers
[S18-1111]: Kata Gábor | Davide Buscaldi | Anne-Kathrin Schumann | Behrang QasemiZadeh | Haifa Zargayouna | Thierry Charnois

pdf bib ETH-DS3Lab at SemEval-2018 Task 7: Effectively Combining Recurrent and Convolutional Neural Networks for Relation Classification and Extraction
[S18-1112]: Jonathan Rotsztejn | Nora Hollenstein | Ce Zhang

pdf bib SemEval-2018 Task 8: Semantic Extraction from CybersecUrity REports using Natural Language Processing (SecureNLP)
[S18-1113]: Peter Phandi | Amila Silva | Wei Lu

pdf bib DM_NLP at SemEval-2018 Task 8: neural sequence labeling with linguistic features
[S18-1114]: Chunping Ma | Huafei Zheng | Pengjun Xie | Chen Li | Linlin Li | Luo Si

pdf bib SemEval-2018 Task 9: Hypernym Discovery
[S18-1115]: Jose Camacho-Collados | Claudio Delli Bovi | Luis Espinosa Anke | Sergio Oramas | Tommaso Pasini | Enrico Santus | Vered Shwartz | Roberto Navigli | Horacio Saggion

pdf bib CRIM at SemEval-2018 Task 9: A Hybrid Approach to Hypernym Discovery
[S18-1116]: Gabriel Bernier-Colborne | Caroline Barriere

pdf bib SemEval-2018 Task 10: Capturing Discriminative Attributes
[S18-1117]: Alicia Krebs | Alessandro Lenci | Denis Paperno

pdf bib SUNNYNLP at SemEval-2018 Task 10: A Support-Vector-Machine-Based Method for Detecting Semantic Difference using Taxonomy and Word Embedding Features
[S18-1118]: Sunny Lai | Kwong Sak Leung | Yee Leung

pdf bib SemEval-2018 Task 11: Machine Comprehension Using Commonsense Knowledge
[S18-1119]: Simon Ostermann | Michael Roth | Ashutosh Modi | Stefan Thater | Manfred Pinkal

pdf bib Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine Comprehension
[S18-1120]: Liang Wang | Meng Sun | Wei Zhao | Kewei Shen | Jingming Liu

pdf bib SemEval-2018 Task 12: The Argument Reasoning Comprehension Task
[S18-1121]: Ivan Habernal | Henning Wachsmuth | Iryna Gurevych | Benno Stein

pdf bib GIST at SemEval-2018 Task 12: A network transferring inference knowledge to Argument Reasoning Comprehension task
[S18-1122]: HongSeok Choi | Hyunju Lee

pdf bib LightRel at SemEval-2018 Task 7: Lightweight and Fast Relation Classification
[S18-1123]: Tyler Renslow | Günter Neumann

pdf bib OhioState at SemEval-2018 Task 7: Exploiting Data Augmentation for Relation Classification in Scientific Papers Using Piecewise Convolutional Neural Networks
[S18-1124]: Dushyanta Dhyani

pdf bib The UWNLP system at SemEval-2018 Task 7: Neural Relation Extraction Model with Selectively Incorporated Concept Embeddings
[S18-1125]: Yi Luan | Mari Ostendorf | Hannaneh Hajishirzi

pdf bib UC3M-NII Team at SemEval-2018 Task 7: Semantic Relation Classification in Scientific Papers via Convolutional Neural Network
[S18-1126]: Víctor Suárez-Paniagua | Isabel Segura-Bedmar | Akiko Aizawa

pdf bib MIT-MEDG at SemEval-2018 Task 7: Semantic Relation Classification via Convolution Neural Network
[S18-1127]: Di Jin | Franck Dernoncourt | Elena Sergeeva | Matthew McDermott | Geeticka Chauhan

pdf bib SIRIUS-LTG-UiO at SemEval-2018 Task 7: Convolutional Neural Networks with Shortest Dependency Paths for Semantic Relation Extraction and Classification in Scientific Papers
[S18-1128]: Farhad Nooralahzadeh | Lilja Øvrelid | Jan Tore Lønning

pdf bib IRCMS at SemEval-2018 Task 7 : Evaluating a basic CNN Method and Traditional Pipeline Method for Relation Classification
[S18-1129]: Zhongbo Yin | Zhunchen Luo | Wei Luo | Mao Bin | Changhai Tian | Yuming Ye | Shuai Wu

pdf bib Bf3R at SemEval-2018 Task 7: Evaluating Two Relation Extraction Tools for Finding Semantic Relations in Biomedical Abstracts
[S18-1130]: Mariana Neves | Daniel Butzke | Gilbert Schönfelder | Barbara Grune

pdf bib Texterra at SemEval-2018 Task 7: Exploiting Syntactic Information for Relation Extraction and Classification in Scientific Papers
[S18-1131]: Andrey Sysoev | Vladimir Mayorov

pdf bib UniMa at SemEval-2018 Task 7: Semantic Relation Extraction and Classification from Scientific Publications
[S18-1132]: Thorsten Keiper | Zhonghao Lyu | Sara Pooladzadeh | Yuan Xu | Jingyi Zhang | Anne Lauscher | Simone Paolo Ponzetto

pdf bib GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification
[S18-1133]: Sean MacAvaney | Luca Soldaini | Arman Cohan | Nazli Goharian

pdf bib ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings
[S18-1134]: Lena Hettinger | Alexander Dallmann | Albin Zehe | Thomas Niebler | Andreas Hotho

pdf bib TakeLab at SemEval-2018 Task 7: Combining Sparse and Dense Features for Relation Classification in Scientific Texts
[S18-1135]: Martin Gluhak | Maria Pia di Buono | Abbas Akkasi | Jan Šnajder

pdf bib NEUROSENT-PDI at SemEval-2018 Task 7: Discovering Textual Relations With a Neural Network Model
[S18-1136]: Mauro Dragoni

pdf bib SciREL at SemEval-2018 Task 7: A System for Semantic Relation Extraction and Classification
[S18-1137]: Darshini Mahendran | Chathurika Brahmana | Bridget McInnes

pdf bib NTNU at SemEval-2018 Task 7: Classifier Ensembling for Semantic Relation Identification and Classification in Scientific Papers
[S18-1138]: Biswanath Barik | Utpal Kumar Sikdar | Björn Gambäck

pdf bib Talla at SemEval-2018 Task 7: Hybrid Loss Optimization for Relation Classification using Convolutional Neural Networks
[S18-1139]: Bhanu Pratap | Daniel Shank | Oladipo Ositelu | Byron Galbraith

pdf bib TeamDL at SemEval-2018 Task 8: Cybersecurity Text Analysis using Convolutional Neural Network and Conditional Random Fields
[S18-1140]: Manikandan R | Krishna Madgula | Snehanshu Saha

pdf bib HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports
[S18-1141]: Mingming Fu | Xuemin Zhao | Yonghong Yan

pdf bib UMBC at SemEval-2018 Task 8: Understanding Text about Malware
[S18-1142]: Ankur Padia | Arpita Roy | Taneeya Satyapanich | Francis Ferraro | Shimei Pan | Youngja Park | Anupam Joshi | Tim Finin

pdf bib Villani at SemEval-2018 Task 8: Semantic Extraction from Cybersecurity Reports using Representation Learning
[S18-1143]: Pablo Loyola | Kugamoorthy Gajananan | Yuji Watanabe | Fumiko Satoh

pdf bib Flytxt_NTNU at SemEval-2018 Task 8: Identifying and Classifying Malware Text Using Conditional Random Fields and Naïve Bayes Classifiers
[S18-1144]: Utpal Kumar Sikdar | Biswanath Barik | Björn Gambäck

pdf bib Digital Operatives at SemEval-2018 Task 8: Using dependency features for malware NLP
[S18-1145]: Chris Brew

pdf bib Apollo at SemEval-2018 Task 9: Detecting Hypernymy Relations Using Syntactic Dependencies
[S18-1146]: Mihaela Onofrei | Ionut Hulub | Diana Trandabat | Daniela Gifu

pdf bib SJTU-NLP at SemEval-2018 Task 9: Neural Hypernym Discovery with Term Embeddings
[S18-1147]: Zhuosheng Zhang | Jiangtong Li | Hai Zhao | Bingjie Tang

pdf bib NLP_HZ at SemEval-2018 Task 9: a Nearest Neighbor Approach
[S18-1148]: Wei Qiu | Mosha Chen | Linlin Li | Luo Si

pdf bib UMDuluth-CS8761 at SemEval-2018 Task9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings
[S18-1149]: Arshia Zernab Hassan | Manikya Swathi Vallabhajosyula | Ted Pedersen

pdf bib EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery
[S18-1150]: Ahmad Issa Alaa Aldine | Mounira Harzallah | Giuseppe Berio | Nicolas Béchet | Ahmad Faour

pdf bib ADAPT at SemEval-2018 Task 9: Skip-Gram Word Embeddings for Unsupervised Hypernym Discovery in Specialised Corpora
[S18-1151]: Alfredo Maldonado | Filip Klubička

pdf bib 300-sparsans at SemEval-2018 Task 9: Hypernymy as interaction of sparse attributes
[S18-1152]: Gábor Berend | Márton Makrai | Péter Földiák

pdf bib UWB at SemEval-2018 Task 10: Capturing Discriminative Attributes from Word Distributions
[S18-1153]: Tomáš Brychcín | Tomáš Hercig | Josef Steinberger | Michal Konkol

pdf bib Meaning_space at SemEval-2018 Task 10: Combining explicitly encoded knowledge with information extracted from word embeddings
[S18-1154]: Pia Sommerauer | Antske Fokkens | Piek Vossen

pdf bib GHH at SemEval-2018 Task 10: Discovering Discriminative Attributes in Distributional Semantics
[S18-1155]: Mohammed Attia | Younes Samih | Manaal Faruqui | Wolfgang Maier

pdf bib CitiusNLP at SemEval-2018 Task 10: The Use of Transparent Distributional Models and Salient Contexts to Discriminate Word Attributes
[S18-1156]: Pablo Gamallo

pdf bib THU_NGN at SemEval-2018 Task 10: Capturing Discriminative Attributes with MLP-CNN model
[S18-1157]: Chuhan Wu | Fangzhao Wu | Sixing Wu | Zhigang Yuan | Yongfeng Huang

pdf bib ALB at SemEval-2018 Task 10: A System for Capturing Discriminative Attributes
[S18-1158]: Bogdan Dumitru | Alina Maria Ciobanu | Liviu P. Dinu

pdf bib ELiRF-UPV at SemEval-2018 Task 10: Capturing Discriminative Attributes with Knowledge Graphs and Wikipedia
[S18-1159]: José-Ángel González | Lluís-F. Hurtado | Encarna Segarra | Ferran Pla

pdf bib Wolves at SemEval-2018 Task 10: Semantic Discrimination based on Knowledge and Association
[S18-1160]: Shiva Taslimipoor | Omid Rohanian | Le An Ha | Gloria Corpas Pastor | Ruslan Mitkov

pdf bib UNAM at SemEval-2018 Task 10: Unsupervised Semantic Discriminative Attribute Identification in Neural Word Embedding Cones
[S18-1161]: Ignacio Arroyo-Fernández | Ivan Meza | Carlos-Francisco Méndez-Cruz

pdf (v2) pdf (v1) bib Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational Knowledge
[S18-1162]: Robyn Speer | Joanna Lowry-Duda

pdf bib BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes
[S18-1163]: Enrico Santus | Chris Biemann | Emmanuele Chersoni

pdf bib Igevorse at SemEval-2018 Task 10: Exploring an Impact of Word Embeddings Concatenation for Capturing Discriminative Attributes
[S18-1164]: Maxim Grishin

pdf bib ECNU at SemEval-2018 Task 10: Evaluating Simple but Effective Features on Machine Learning Methods for Semantic Difference Detection
[S18-1165]: Yunxiao Zhou | Man Lan | Yuanbin Wu

pdf bib AmritaNLP at SemEval-2018 Task 10: Capturing discriminative attributes using convolution neural network over global vector representation.
[S18-1166]: Vivek Vinayan | Anand Kumar M | Soman K P

pdf bib Discriminator at SemEval-2018 Task 10: Minimally Supervised Discrimination
[S18-1167]: Artur Kulmizev | Mostafa Abdou | Vinit Ravishankar | Malvina Nissim

pdf bib UNBNLP at SemEval-2018 Task 10: Evaluating unsupervised approaches to capturing discriminative attributes
[S18-1168]: Milton King | Ali Hakimi Parizi | Paul Cook

pdf bib ABDN at SemEval-2018 Task 10: Recognising Discriminative Attributes using Context Embeddings and WordNet
[S18-1169]: Rui Mao | Guanyi Chen | Ruizhe Li | Chenghua Lin

pdf bib UMD at SemEval-2018 Task 10: Can Word Embeddings Capture Discriminative Attributes?
[S18-1170]: Alexander Zhang | Marine Carpuat

pdf bib NTU NLP Lab System at SemEval-2018 Task 10: Verifying Semantic Differences by Integrating Distributional Information and Expert Knowledge
[S18-1171]: Yow-Ting Shiue | Hen-Hsen Huang | Hsin-Hsi Chen

pdf bib ELiRF-UPV at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge
[S18-1172]: José-Ángel González | Lluís-F. Hurtado | Encarna Segarra | Ferran Pla

pdf bib YNU_AI1799 at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge of Different model ensemble
[S18-1173]: Qingxun Liu | Hongdou Yao | Xaobing Zhou | Ge Xie

pdf bib YNU_Deep at SemEval-2018 Task 11: An Ensemble of Attention-based BiLSTM Models for Machine Comprehension
[S18-1174]: Peng Ding | Xiaobing Zhou

pdf bib ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task
[S18-1175]: Yixuan Sheng | Man Lan | Yuanbin Wu

pdf bib CSReader at SemEval-2018 Task 11: Multiple Choice Question Answering as Textual Entailment
[S18-1176]: Zhengping Jiang | Qi Sun

pdf bib YNU-HPCC at Semeval-2018 Task 11: Using an Attention-based CNN-LSTM for Machine Comprehension using Commonsense Knowledge
[S18-1177]: Hang Yuan | Jin Wang | Xuejie Zhang

pdf bib Jiangnan at SemEval-2018 Task 11: Deep Neural Network with Attention Method for Machine Comprehension Task
[S18-1178]: Jiangnan Xia

pdf bib IUCM at SemEval-2018 Task 11: Similar-Topic Texts as a Comprehension Knowledge Source
[S18-1179]: Sofia Reznikova | Leon Derczynski

pdf bib Lyb3b at SemEval-2018 Task 11: Machine Comprehension Task using Deep Learning Models
[S18-1180]: Yongbin Li | Xiaobing Zhou

pdf bib MITRE at SemEval-2018 Task 11: Commonsense Reasoning without Commonsense Knowledge
[S18-1181]: Elizabeth Merkhofer | John Henderson | David Bloom | Laura Strickhart | Guido Zarrella

pdf bib SNU_IDS at SemEval-2018 Task 12: Sentence Encoder with Contextualized Vectors for Argument Reasoning Comprehension
[S18-1182]: Taeuk Kim | Jihun Choi | Sang-goo Lee

pdf bib ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention
[S18-1183]: Wenjie Liu | Chengjie Sun | Lei Lin | Bingquan Liu

pdf bib ECNU at SemEval-2018 Task 12: An End-to-End Attention-based Neural Network for the Argument Reasoning Comprehension Task
[S18-1184]: Junfeng Tian | Man Lan | Yuanbin Wu

pdf bib NLITrans at SemEval-2018 Task 12: Transfer of Semantic Knowledge for Argument Comprehension
[S18-1185]: Timothy Niven | Hung-Yu Kao

pdf bib BLCU_NLP at SemEval-2018 Task 12: An Ensemble Model for Argument Reasoning Based on Hierarchical Attention
[S18-1186]: Meiqian Zhao | Chunhua Liu | Lu Liu | Yan Zhao | Dong Yu

pdf bib YNU-HPCC at SemEval-2018 Task 12: The Argument Reasoning Comprehension Task Using a Bi-directional LSTM with Attention Model
[S18-1187]: Quanlei Liao | Xutao Yang | Jin Wang | Xuejie Zhang

pdf bib HHU at SemEval-2018 Task 12: Analyzing an Ensemble-based Deep Learning Approach for the Argument Mining Task of Choosing the Correct Warrant
[S18-1188]: Matthias Liebeck | Andreas Funke | Stefan Conrad

pdf bib YNU Deep at SemEval-2018 Task 12: A BiLSTM Model with Neural Attention for Argument Reasoning Comprehension
[S18-1189]: Peng Ding | Xiaobing Zhou

pdf bib UniMelb at SemEval-2018 Task 12: Generative Implication using LSTMs, Siamese Networks and Semantic Representations with Synonym Fuzzing
[S18-1190]: Anirudh Joshi | Tim Baldwin | Richard O. Sinnott | Cecile Paris

pdf bib Joker at SemEval-2018 Task 12: The Argument Reasoning Comprehension with Neural Attention
[S18-1191]: Guobin Sui | Wenhan Chao | Zhunchen Luo

pdf bib TakeLab at SemEval-2018 Task12: Argument Reasoning Comprehension with Skip-Thought Vectors
[S18-1192]: Ana Brassard | Tin Kuculo | Filip Boltuzic | Jan Šnajder

pdf bib Lyb3b at SemEval-2018 Task 12: Ensemble-based Deep Learning Models for Argument Reasoning Comprehension Task
[S18-1193]: Yongbin Li | Xiaobing Zhou

pdf bib TRANSRW at SemEval-2018 Task 12: Transforming Semantic Representations for Argument Reasoning Comprehension
[S18-1194]: Zhimin Chen | Wei Song | Lizhen Liu


up

pdf (full)bib Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics

pdf bib Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics
[S18-2000]: Malvina Nissim | Jonathan Berant | Alessandro Lenci

pdf bib Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization
[S18-2001]: Kian Kenyon-Dean | Jackie Chi Kit Cheung | Doina Precup

pdf bib Learning distributed event representations with a multi-task approach
[S18-2002]: Xudong Hong | Asad Sayeed | Vera Demberg

pdf bib Assessing Meaning Components in German Complex Verbs: A Collection of Source-Target Domains and Directionality
[S18-2003]: Sabine Schulte im Walde | Maximilian Köper | Sylvia Springorum

pdf bib Learning Neural Word Salience Scores
[S18-2004]: Krasen Samardzhiev | Andrew Gargett | Danushka Bollegala

pdf bib Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems
[S18-2005]: Svetlana Kiritchenko | Saif Mohammad

pdf bib Graph Algebraic Combinatory Categorial Grammar
[S18-2006]: Sebastian Beschke | Wolfgang Menzel

pdf bib Mixing Context Granularities for Improved Entity Linking on Question Answering Data across Entity Categories
[S18-2007]: Daniil Sorokin | Iryna Gurevych

pdf bib Quantitative Semantic Variation in the Contexts of Concrete and Abstract Words
[S18-2008]: Daniela Naumann | Diego Frassinelli | Sabine Schulte im Walde

pdf bib EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet
[S18-2009]: Gilbert Badaro | Hussein Jundi | Hazem Hajj | Wassim El-Hajj

pdf bib The Limitations of Cross-language Word Embeddings Evaluation
[S18-2010]: Amir Bakarov | Roman Suvorov | Ilya Sochenkov

pdf bib How Gender and Skin Tone Modifiers Affect Emoji Semantics in Twitter
[S18-2011]: Francesco Barbieri | Jose Camacho-Collados

pdf bib Element-wise Bilinear Interaction for Sentence Matching
[S18-2012]: Jihun Choi | Taeuk Kim | Sang-goo Lee

pdf bib Named Graphs for Semantic Representation
[S18-2013]: Richard Crouch | Aikaterini-Lida Kalouli

pdf bib Learning Patient Representations from Text
[S18-2014]: Dmitriy Dligach | Timothy Miller

pdf bib Polarity Computations in Flexible Categorial Grammar
[S18-2015]: Hai Hu | Larry Moss

pdf bib Coarse Lexical Frame Acquisition at the Syntax–Semantics Interface Using a Latent-Variable PCFG Model
[S18-2016]: Laura Kallmeyer | Behrang QasemiZadeh | Jackie Chi Kit Cheung

pdf bib Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction
[S18-2017]: Hongyuan Mei | Sheng Zhang | Kevin Duh | Benjamin Van Durme

pdf bib Exploiting Partially Annotated Data in Temporal Relation Extraction
[S18-2018]: Qiang Ning | Zhongzhi Yu | Chuchu Fan | Dan Roth

pdf bib Predicting Word Embeddings Variability
[S18-2019]: Benedicte Pierrejean | Ludovic Tanguy

pdf bib Integrating Multiplicative Features into Supervised Distributional Methods for Lexical Entailment
[S18-2020]: Tu Vu | Vered Shwartz

pdf bib Deep Affix Features Improve Neural Named Entity Recognizers
[S18-2021]: Vikas Yadav | Rebecca Sharp | Steven Bethard

pdf bib Fine-grained Entity Typing through Increased Discourse Context and Adaptive Classification Thresholds
[S18-2022]: Sheng Zhang | Kevin Duh | Benjamin Van Durme

pdf bib Hypothesis Only Baselines in Natural Language Inference
[S18-2023]: Adam Poliak | Jason Naradowsky | Aparajita Haldar | Rachel Rudinger | Benjamin Van Durme

pdf bib Quality Signals in Generated Stories
[S18-2024]: Manasvi Sagarkar | John Wieting | Lifu Tu | Kevin Gimpel

pdf bib Term Definitions Help Hypernymy Detection
[S18-2025]: Wenpeng Yin | Dan Roth

pdf bib Agree or Disagree: Predicting Judgments on Nuanced Assertions
[S18-2026]: Michael Wojatzki | Torsten Zesch | Saif Mohammad | Svetlana Kiritchenko

pdf bib A Multimodal Translation-Based Approach for Knowledge Graph Representation Learning
[S18-2027]: Hatem Mousselly Sergieh | Teresa Botschen | Iryna Gurevych | Stefan Roth

pdf bib Putting Semantics into Semantic Roles
[S18-2028]: James Allen | Choh Man Teng

pdf bib Measuring Frame Instance Relatedness
[S18-2029]: Valerio Basile | Roque Lopez Condori | Elena Cabrio

pdf bib Solving Feature Sparseness in Text Classification using Core-Periphery Decomposition
[S18-2030]: Xia Cui | Sadamori Kojaku | Naoki Masuda | Danushka Bollegala

pdf bib Robust Handling of Polysemy via Sparse Representations
[S18-2031]: Abhijit Mahabal | Dan Roth | Sid Mittal

pdf bib Multiplicative Tree-Structured Long Short-Term Memory Networks for Semantic Representations
[S18-2032]: Nam Khanh Tran | Weiwei Cheng