SemEval 2016

213 papers

VCU at Semeval-2016 Task 14: Evaluating definitional-based similarity measure for semantic taxonomy enrichment

Bridget McInnes

UMNDuluth at SemEval-2016 Task 14: WordNet’s Missing Lemmas

Jon Rusert, Ted Pedersen

Deftor at SemEval-2016 Task 14: Taxonomy enrichment using definition vectors

Hristo Tanev, Agata Rotondi

MSejrKu at SemEval-2016 Task 14: Taxonomy Enrichment by Evidence Ranking

Michael Schlichtkrull, Héctor Martínez Alonso

TALN at SemEval-2016 Task 14: Semantic Taxonomy Enrichment Via Sense-Based Embeddings

Luis Espinosa-Anke, Francesco Ronzano, Horacio Saggion

Duluth at SemEval 2016 Task 14: Extending Gloss Overlaps to Enrich Semantic Taxonomies

Ted Pedersen

TAXI at SemEval-2016 Task 13: a Taxonomy Induction Method based on Lexico-Syntactic Patterns, Substrings and Focused Crawling

Alexander Panchenko, Stefano Faralli, Eugen Ruppert, Steffen Remus, Hubert Naets

QASSIT at SemEval-2016 Task 13: On the integration of Semantic Vectors in Pretopological Spaces for Lexical Taxonomy Acquisition

Guillaume Cleuziou, José G. Moreno

JUNLP at SemEval-2016 Task 13: A Language Independent Approach for Hypernym Identification

Promita Maitra, Dipankar Das

USAAR at SemEval-2016 Task 13: Hyponym Endocentricity

Liling Tan, Francis Bond, Josef van Genabith

NUIG-UNLP at SemEval-2016 Task 13: A Simple Word Embedding-based Approach for Taxonomy Extraction

Joel Pocostales

UTHealth at SemEval-2016 Task 12: an End-to-End System for Temporal Information Extraction from Clinical Notes

Hee-Jin Lee, Hua Xu, Jingqi Wang, Yaoyun Zhang, Sungrim Moon

CENTAL at SemEval-2016 Task 12: a linguistically fed CRF model for medical and temporal information extraction

Charlotte Hansart, Damien De Meyere, Patrick Watrin, André Bittar, Cédrick Fairon

KULeuven-LIIR at SemEval 2016 Task 12: Detecting Narrative Containment in Clinical Records

Artuur Leeuwenberg, Marie-Francine Moens

Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction

Jason Fries

UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports

Peng Li, Heng Huang

ULISBOA at SemEval-2016 Task 12: Extraction of temporal expressions, clinical events and relations using IBEnt

Marcia Barros, Andre Lamurias, Gonçalo Figueiro, Marta Antunes, Joana Teixeira

UtahBMI at SemEval-2016 Task 12: Extracting Temporal Information from Clinical Text

Abdulrahman Khalifa, Sumithra Velupillai, Stéphane Meystre

GUIR at SemEval-2016 task 12: Temporal Information Processing for Clinical Narratives

Arman Cohan, Kevin Meurer, Nazli Goharian

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

Tommaso Caselli, Roser Morante

CDE-IIITH at SemEval-2016 Task 12: Extraction of Temporal Information from Clinical documents using Machine Learning techniques

Veera Raghavendra Chikka

Hitachi at SemEval-2016 Task 12: A Hybrid Approach for Temporal Information Extraction from Clinical Notes

Sarath P R, Manikandan R, Yoshiki Niwa

LIMSI at SemEval-2016 Task 12: machine-learning and temporal information to identify clinical events and time expressions

Cyril Grouin, Véronique Moriceau

OSU_CHGCG at SemEval-2016 Task 9 : Chinese Semantic Dependency Parsing with Generalized Categorial Grammar

Manjuan Duan, Lifeng Jin, William Schuler

OCLSP at SemEval-2016 Task 9: Multilayered LSTM as a Neural Semantic Dependency Parser

Lifeng Jin, Manjuan Duan, William Schuler

IHS-RD-Belarus at SemEval-2016 Task 9: Transition-based Chinese Semantic Dependency Parsing with Online Reordering and Bootstrapping.

Artsiom Artsymenia, Palina Dounar, Maria Yermakovich

CMU at SemEval-2016 Task 8: Graph-based AMR Parsing with Infinite Ramp Loss

Jeffrey Flanigan, Chris Dyer, Noah A. Smith, Jaime Carbonell

CU-NLP at SemEval-2016 Task 8: AMR Parsing using LSTM-based Recurrent Neural Networks

William Foland, James H. Martin

CLIP@UMD at SemEval-2016 Task 8: Parser for Abstract Meaning Representation using Learning to Search

Sudha Rao, Yogarshi Vyas, Hal Daume III, Philip Resnik

UofR at SemEval-2016 Task 8: Learning Synchronous Hyperedge Replacement Grammar for AMR Parsing

Xiaochang Peng, Daniel Gildea

The Meaning Factory at SemEval-2016 Task 8: Producing AMRs with Boxer

Johannes Bjerva, Johan Bos, Hessel Haagsma

CAMR at SemEval-2016 Task 8: An Extended Transition-based AMR Parser

Chuan Wang, Sameer Pradhan, Xiaoman Pan, Heng Ji, Nianwen Xue

UCL+Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound

James Goodman, Andreas Vlachos, Jason Naradowsky

ICL-HD at SemEval-2016 Task 8: Meaning Representation Parsing - Augmenting AMR Parsing with a Preposition Semantic Role Labeling Neural Network

Lauritz Brandt, David Grimm, Mengfei Zhou, Yannick Versley

M2L at SemEval-2016 Task 8: AMR Parsing with Neural Networks

Yevgeniy Puzikov, Daisuke Kawahara, Sadao Kurohashi

DynamicPower at SemEval-2016 Task 8: Processing syntactic parse trees with a Dynamic Semantics core

Alastair Butler

RIGA at SemEval-2016 Task 8: Impact of Smatch Extensions and Character-Level Neural Translation on AMR Parsing Accuracy

Guntis Barzdins, Didzis Gosko

LIMSI-COT at SemEval-2016 Task 12: Temporal relation identification using a pipeline of classifiers

Julien Tourille, Olivier Ferret, Aurélie Névéol, Xavier Tannier

IIT-TUDA at SemEval-2016 Task 5: Beyond Sentiment Lexicon: Combining Domain Dependency and Distributional Semantics Features for Aspect Based Sentiment Analysis

Ayush Kumar, Sarah Kohail, Amit Kumar, Asif Ekbal, Chris Biemann

SwissCheese at SemEval-2016 Task 4: Sentiment Classification Using an Ensemble of Convolutional Neural Networks with Distant Supervision

Jan Deriu, Maurice Gonzenbach, Fatih Uzdilli, Aurelien Lucchi, Valeria De Luca

KeLP at SemEval-2016 Task 3: Learning Semantic Relations between Questions and Answers

Simone Filice, Danilo Croce, Alessandro Moschitti, Roberto Basili

Inspire at SemEval-2016 Task 2: Interpretable Semantic Textual Similarity Alignment based on Answer Set Programming

Mishal Kazmi, Peter Schüller

UMD-TTIC-UW at SemEval-2016 Task 1: Attention-Based Multi-Perspective Convolutional Neural Networks for Textual Similarity Measurement

Hua He, John Wieting, Kevin Gimpel, Jinfeng Rao, Jimmy Lin

SemEval-2016 Task 14: Semantic Taxonomy Enrichment

David Jurgens, Mohammad Taher Pilehvar

SemEval-2016 Task 13: Taxonomy Extraction Evaluation (TExEval-2)

Georgeta Bordea, Els Lefever, Paul Buitelaar

SemEval-2016 Task 9: Chinese Semantic Dependency Parsing

Wanxiang Che, Yanqiu Shao, Ting Liu, Yu Ding

SemEval-2016 Task 8: Meaning Representation Parsing

Jonathan May

SemEval-2016 Task 12: Clinical TempEval

Steven Bethard, Guergana Savova, Wei-Te Chen, Leon Derczynski, James Pustejovsky

Pomona at SemEval-2016 Task 11: Predicting Word Complexity Based on Corpus Frequency

David Kauchak

AI-KU at SemEval-2016 Task 11: Word Embeddings and Substring Features for Complex Word Identification

Onur Kuru

UWB at SemEval-2016 Task 11: Exploring Features for Complex Word Identification

Michal Konkol

HMC at SemEval-2016 Task 11: Identifying Complex Words Using Depth-limited Decision Trees

Maury Quijada, Julie Medero

CoastalCPH at SemEval-2016 Task 11: The importance of designing your Neural Networks right

Joachim Bingel, Natalie Schluter, Héctor Martínez Alonso

AmritaCEN at SemEval-2016 Task 11: Complex Word Identification using Word Embedding

Sanjay S.P, Anand Kumar M, Soman K P

IIIT at SemEval-2016 Task 11: Complex Word Identification using Nearest Centroid Classification

Ashish Palakurthi, Radhika Mamidi

TALN at SemEval-2016 Task 11: Modelling Complex Words by Contextual, Lexical and Semantic Features

Francesco Ronzano, Ahmed AbuRa’ed, Luis Espinosa-Anke, Horacio Saggion

Garuda & Bhasha at SemEval-2016 Task 11: Complex Word Identification Using Aggregated Learning Models

Prafulla Choubey, Shubham Pateria

MacSaar at SemEval-2016 Task 11: Zipfian and Character Features for ComplexWord Identification

Marcos Zampieri, Liling Tan, Josef van Genabith

LTG at SemEval-2016 Task 11: Complex Word Identification with Classifier Ensembles

Shervin Malmasi, Mark Dras, Marcos Zampieri

MAZA at SemEval-2016 Task 11: Detecting Lexical Complexity Using a Decision Stump Meta-Classifier

Shervin Malmasi, Marcos Zampieri

JU_NLP at SemEval-2016 Task 11: Identifying Complex Words in a Sentence

Niloy Mukherjee, Braja Gopal Patra, Dipankar Das, Sivaji Bandyopadhyay

CLaC at SemEval-2016 Task 11: Exploring linguistic and psycho-linguistic Features for Complex Word Identification

Elnaz Davoodi, Leila Kosseim

Melbourne at SemEval 2016 Task 11: Classifying Type-level Word Complexity using Random Forests with Corpus and Word List Features

Julian Brooke, Alexandra Uitdenbogerd, Timothy Baldwin

SV000gg at SemEval-2016 Task 11: Heavy Gauge Complex Word Identification with System Voting

Gustavo Paetzold, Lucia Specia

Sensible at SemEval-2016 Task 11: Neural Nonsense Mangled in Ensemble Mess

Gillin Nat

USAAR at SemEval-2016 Task 11: Complex Word Identification with Sense Entropy and Sentence Perplexity

José Manuel Martínez Martínez, Liling Tan

PLUJAGH at SemEval-2016 Task 11: Simple System for Complex Word Identification

Krzysztof Wróbel

VectorWeavers at SemEval-2016 Task 10: From Incremental Meaning to Semantic Unit (phrase by phrase)

Andreas Scherbakov, Ekaterina Vylomova, Fei Liu, Timothy Baldwin

ICL-HD at SemEval-2016 Task 10: Improving the Detection of Minimal Semantic Units and their Meanings with an Ontology and Word Embeddings

Angelika Kirilin, Felix Krauss, Yannick Versley

UW-CSE at SemEval-2016 Task 10: Detecting Multiword Expressions and Supersenses using Double-Chained Conditional Random Fields

Mohammad Javad Hosseini, Noah A. Smith, Su-in Lee

UTU at SemEval-2016 Task 10: Binary Classification for Expression Detection (BCED)

Jari Björne, Tapio Salakoski

WHUNlp at SemEval-2016 Task DiMSUM: A Pilot Study in Detecting Minimal Semantic Units and their Meanings using Supervised Models

Xin Tang, Fei Li, Donghong Ji

UFRGS&LIF at SemEval-2016 Task 10: Rule-Based MWE Identification and Predominant-Supersense Tagging

Silvio Cordeiro, Carlos Ramisch, Aline Villavicencio

ITNLP-AiKF at SemEval-2016 Task 3 a quesiton answering system using community QA repository

Chang’e Jia

ConvKN at SemEval-2016 Task 3: Answer and Question Selection for Question Answering on Arabic and English Fora

Alberto Barrón-Cedeño, Daniele Bonadiman, Giovanni Da San Martino, Shafiq Joty, Alessandro Moschitti

MTE-NN at SemEval-2016 Task 3: Can Machine Translation Evaluation Help Community Question Answering?

Francisco Guzmán, Preslav Nakov, Lluis Marquez

SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word Embeddings

Todor Mihaylov, Preslav Nakov

ECNU at SemEval-2016 Task 3: Exploring Traditional Method and Deep Learning Method for Question Retrieval and Answer Ranking in Community Question Answering

Guoshun Wu, Man Lan

QU-IR at SemEval 2016 Task 3: Learning to Rank on Arabic Community Question Answering Forums with Word Embedding

Rana Malhas, Marwan Torki, Tamer Elsayed

Overfitting at SemEval-2016 Task 3: Detecting Semantically Similar Questions in Community Question Answering Forums with Word Embeddings

Hujie Wang, Pascal Poupart

ICL00 at SemEval-2016 Task 3: Translation-Based Method for CQA System

Yunfang Wu, Minghua Zhang

UniMelb at SemEval-2016 Task 3: Identifying Similar Questions by combining a CNN with String Similarity Measures

Timothy Baldwin, Huizhi Liang, Bahar Salehi, Doris Hoogeveen, Yitong Li

PMI-cool at SemEval-2016 Task 3: Experiments with PMI and Goodness Polarity Lexicons for Community Question Answering

Daniel Balchev, Yasen Kiprov, Ivan Koychev, Preslav Nakov

SUper Team at SemEval-2016 Task 3: Building a Feature-Rich System for Community Question Answering

Tsvetomila Mihaylova, Pepa Gencheva, Martin Boyanov, Ivana Yovcheva, Todor Mihaylov

SLS at SemEval-2016 Task 3: Neural-based Approaches for Ranking in Community Question Answering

Mitra Mohtarami, Yonatan Belinkov, Wei-Ning Hsu, Yu Zhang, Tao Lei

RDI_Team at SemEval-2016 Task 3: RDI Unsupervised Framework for Text Ranking

Ahmed Magooda, Amr Gomaa, Ashraf Mahgoub, Hany Ahmed, Mohsen Rashwan

UH-PRHLT at SemEval-2016 Task 3: Combining Lexical and Semantic-based Features for Community Question Answering

Marc Franco-Salvador, Sudipta Kar, Thamar Solorio, Paolo Rosso

DTSim at SemEval-2016 Task 2: Interpreting Similarity of Texts Based on Automated Chunking, Chunk Alignment and Semantic Relation Prediction

Rajendra Banjade, Nabin Maharjan, Nobal Bikram Niraula, Vasile Rus

UWB at SemEval-2016 Task 2: Interpretable Semantic Textual Similarity with Distributional Semantics for Chunks

Miloslav Konopík, Ondřej Pražák, David Steinberger, Tomáš Brychcín

VENSESEVAL at Semeval-2016 Task 2 iSTS - with a full-fledged rule-based approach

Rodolfo Delmonte

IISCNLP at SemEval-2016 Task 2: Interpretable STS with ILP based Multiple Chunk Aligner

Lavanya Tekumalla, Sharmistha Jat

FBK-HLT-NLP at SemEval-2016 Task 2: A Multitask, Deep Learning Approach for Interpretable Semantic Textual Similarity

Simone Magnolini, Anna Feltracco, Bernardo Magnini

Rev at SemEval-2016 Task 2: Aligning Chunks by Lexical, Part of Speech and Semantic Equivalence

Ping Tan, Karin Verspoor, Timothy Miller

iUBC at SemEval-2016 Task 2: RNNs and LSTMs for interpretable STS

Iñigo Lopez-Gazpio, Eneko Agirre, Montse Maritxalar

DalGTM at SemEval-2016 Task 1: Importance-Aware Compositional Approach to Short Text Similarity

Jie Mei, Aminul Islam, Evangelos Milios

RTM at SemEval-2016 Task 1: Predicting Semantic Similarity with Referential Translation Machines and Related Statistics

Ergun Biçici

SERGIOJIMENEZ at SemEval-2016 Task 1: Effectively Combining Paraphrase Database, String Matching, WordNet, and Word Embedding for Semantic Textual Similarity

Sergio Jiménez

SimiHawk at SemEval-2016 Task 1: A Deep Ensemble System for Semantic Textual Similarity

Peter Potash, William Boag, Alexey Romanov, Vasili Ramanishka, Anna Rumshisky

ASOBEK at SemEval-2016 Task 1: Sentence Representation with Character N-gram Embeddings for Semantic Textual Similarity

Asli Eyecioglu, Bill Keller

UNBNLP at SemEval-2016 Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation

Milton King, Waseem Gharbieh, Sohyun Park, Paul Cook