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| "text": "Building on the momentum generated by the spectacular success of the Joint Conference on Lexical and Computational Semantics (*SEM) in 2012, bringing together the ACL SIGLEX and ACL SIGSEM communities, we are delighted to bring to you the second edition of the conference, as a top-tier showcase of the latest research in computational semantics. We accepted 14 papers (11 long and 3 short) for publication at the conference, out of a possible 45 submissions (a 31% acceptance rate). This is on par with some of the most competitive conferences in computational linguistics, and we are confident will set the stage for a scintillating conference.", | |
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| "section": "Introduction to *SEM 2013", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "This year, we started a tradition that we intend to maintain in all future iterations of the conference in integrating a shared task into the conference. The shared task was selected by an independent committee comprising members from SIGLEX and SIGSEM, based on an open call for proposals, and revolved around Semantic Textual Similarity (STS). The task turned out to be a huge success with 34 teams participating, submitting a total of 103 system runs.", | |
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| "section": "Introduction to *SEM 2013", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "Day One, June 13th: Day Two, June 14th:", | |
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| "section": "*SEM 2013 features a number of highlight events:", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "\u2022 A", | |
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| "section": "*SEM 2013 features a number of highlight events:", | |
| "sec_num": null | |
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| { | |
| "text": "\u2022 In the morning, a keynote address by David Forsyth from the Computer Science Department at the University of Illinois at Urbana Champagne on issues of Vision and Language. It promises to be an extremely stimulating speech, and is not to be missed.", | |
| "cite_spans": [], | |
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| "section": "*SEM 2013 features a number of highlight events:", | |
| "sec_num": null | |
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| "text": "\u2022 In the early afternoon, a panel on the relation between and future of *SEM, the *SEM Shared Task, SemEval and other events on computational semantics. In this panel, we will attempt to clarify and explain as well as devise plans for these different entities.", | |
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| "section": "*SEM 2013 features a number of highlight events:", | |
| "sec_num": null | |
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| { | |
| "text": "\u2022 Finally, at the end of the day, an award ceremony for the Best Long Paper and Best Short Paper.", | |
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| "section": "*SEM 2013 features a number of highlight events:", | |
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| { | |
| "text": "iii As always, *SEM 2013 would not have been possible without the considerable efforts of our area chairs and an impressive assortment of reviewers, drawn from the ranks of SIGLEX and SIGSEM, and the computational semantics community at large. We would also like to acknowledge the generous support for the STS Task from the DARPA Deft Program.", | |
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| "section": "*SEM 2013 features a number of highlight events:", | |
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| "text": "The Semantic Evaluation (SemEval) series of workshops focus on the evaluation and comparison of systems that can analyse diverse semantic phenomena in text with the aim of extending the current state-of-the-art in semantic analysis and creating high quality annotated datasets in a range of increasingly challenging problems in natural language semantics. SemEval provides an exciting forum for researchers to propose challenging research problems in semantics and to build systems/techniques to address such research problems.", | |
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| "ref_spans": [], | |
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| "section": "Introduction to SemEval", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "SemEval-2013 is the seventh workshop in the series. The first three workshops, SensEval-1 (1998), SensEval-2 (2001) , and SensEval-3 (2004), were focused on word sense disambiguation, each time growing in the number of languages offered in the tasks and in the number of participating teams. ", | |
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| "start": 98, | |
| "end": 115, | |
| "text": "SensEval-2 (2001)", | |
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| "section": "Introduction to SemEval", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "v", | |
| "cite_spans": [], | |
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| "section": "Introduction to SemEval", | |
| "sec_num": null | |
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| { | |
| "text": "About 100 teams submitted more than 300 systems for the 12 tasks of SemEval-2013. This volume contains both Task Description papers that describe each of the above tasks and System Description papers that describe the systems that participated in the above tasks. A total of 12 task description papers and 101 system description papers are included in this volume.", | |
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| "section": "Introduction to SemEval", | |
| "sec_num": null | |
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| { | |
| "text": "We are indebted to all program committee members for their high quality, elaborate and thoughtful reviews. The papers in this proceedings have surely benefited from this feedback. We are grateful to *SEM 2013 and NAACL-HLT 2013 conference organizers for local organization and the forum. We most gratefully acknowledge the support of our sponsors, the ACL Special Interest Group on the Lexicon (SIGLEX) and the ACL Special Interest Group on Computational Semantics (SIGSEM). ", | |
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| "section": "Introduction to SemEval", | |
| "sec_num": null | |
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| ], | |
| "back_matter": [ | |
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| "text": "We hope you enjoy *SEM 2013, and look forward to engaging with all of you, Mona Diab (The George Washington University, General Chair) Timothy Baldwin (The University of Mebourne, Program Committee Co-Chair) Marco Baroni (University of Trento, Program Committee Co-Chair) Program Committee for Volume 1:Nabil Abdullah (University of Windsor), Eneko Agirre (University of the Basque Country), Nicholas Asher (CNRS Institut de Recherche en Informatique de Toulouse), Eser Ayg\u00fcn, Timothy Baldwin (The University of Melbourne), Eva Banik (Computational Linguistics Ltd), Marco Baroni (University of Trento), Alberto Barr\u00f3n-Cede\u00f1o (Universitat Polit\u00e8cnica de Catalunya), Roberto Basili (University of Roma, Tor Vergata), Miroslav Batchkarov (University of Sussex), Cosmin Bejan, Sabine Bergler (Concordia University), Shane Bergsma (Johns Hopkins University), Steven Bethard (University of Colorado Boulder), Ergun Bicici (Centre for Next Generation Localisation), Chris Biemann (TU Darmstadt), Eduardo Blanco (Lymba Corporation), Gemma Boleda (The University of Texas at Austin), Francis Bond (Nanyang Technological University), Paul Buitelaar (DERI, National University of Ireland, Galway), Razvan Bunescu (Ohio University), Harry Bunt (Tilburg University), Aljoscha Burchardt (DFKI), Davide Buscaldi (LIPN, Universit\u00e9 Paris 13), Olivia Buzek (Johns Hopkins University), Nicoletta Calzolari (ILC-CNR), Annalina Caputo (Dept. ", | |
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| "section": "acknowledgement", | |
| "sec_num": null | |
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Silva IITB-Sentiment-Analysts: Participation in Sentiment Analysis in Twitter SemEval 2013 Task Karan Chawla, Ankit Ramteke and Pushpak Bhattacharyya SSA-UO: Unsupervised Sentiment Analysis in Twitter Reynier Ortega Bueno, Adrian Fonseca Bruz\u00f3n, Yoan Guti\u00e9rrez and Andres Montoyo senti.ue-en: an approach for informally written short texts in SemEval-2013 Sentiment Analysis task Jos\u00e9 Saias and Hil\u00e1rio Fernandes teragram: Rule-based detection of sentiment phrases using SAS Sentiment Analysis Hilke Reckman, Cheyanne Baird, Jean Crawford, Richard Crowell, Linnea Micciulla, Saratendu Sethi and Fruzsina Veress CodeX: Combining an SVM Classifier and Character N-gram Language Models for Sen- timent Analysis on Twitter Text Qi Han, Junfei Guo and Hinrich Schuetze sielers : Feature Analysis and Polarity Classification of Expressions from Twitter and SMS Data Harshit Jain, Aditya Mogadala and Vasudeva Varma Kea: Expression-level Sentiment Analysis from Twitter Data Ameeta Agrawal and Aijun An NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets Saif Mohammad, Svetlana Kiritchenko and Xiaodan Zhu UoM: Using Explicit Semantic Analysis for Classifying Sentiments Sapna Negi and Michael Rosner bwbaugh : Hierarchical sentiment analysis with partial self-training Wesley Baugh Serendio: Simple and Practical lexicon based approach to Sentiment Analysis Prabu palanisamy, Vineet Yadav and Harsha Elchuri SZTE-NLP: Sentiment Detection on Twitter Messages Viktor Hangya, Gabor Berend and Rich\u00e1rd Farkas xxxiii Day 3: Saturday June 15, 2013 (continued) BOUNCE: Sentiment Classification in Twitter using Rich Feature Sets Nadin K\u00f6kciyan, Arda \u00c7 elebi, Arzucan\u00d6zg\u00fcr and Suzan\u00dcsk\u00fcdarl\u0131 nlp.cs.aueb.gr: Two Stage Sentiment Analysis Prodromos Malakasiotis, Rafael Michael Karampatsis, Konstantina Makrynioti and John Pavlopoulos NILC USP: A Hybrid System for Sentiment Analysis in Twitter Messages Pedro Balage Filho and Thiago Pardo SemEval-2013 Task 3: Spatial Role Labeling Oleksandr Kolomiyets, Parisa Kordjamshidi, Marie-Francine Moens and Steven Bethard UNITOR-HMM-TK: Structured Kernel-based learning for Spatial Role Labeling Emanuele Bastianelli, Danilo Croce, Roberto Basili and Daniele Nardi SemEval-2013 Task 7: The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge Myroslava Dzikovska, Rodney Nielsen, Chris Brew, Claudia Leacock, Danilo Giampic- colo, Luisa Bentivogli, Peter Clark, Ido Dagan and Hoa Trang Dang UKP-BIU: Similarity and Entailment Metrics for Student Response Analysis Omer Levy, Torsten Zesch, Ido Dagan and Iryna Gurevych ETS: Domain Adaptation and Stacking for Short Answer Scoring Michael Heilman and Nitin Madnani EHU-ALM: Similarity-Feature Based Approach for Student Response Analysis Itziar Aldabe, Montse Maritxalar and Oier Lopez de Lacalle CNGL: Grading Student Answers by Acts of Translation Ergun Bicici and Josef van Genabith Celi: EDITS and Generic Text Pair Classification Milen Kouylekov, Luca Dini, Alessio Bosca and Marco Trevisan LIMSIILES: Basic English Substitution for Student Answer Assessment at SemEval 2013", | |
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| { | |
| "first": "Antonio", | |
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| "last": "Fern\u00e1ndez Orqu\u00edn", | |
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| "first": "Andr\u00e9s", | |
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| "raw_text": "Daniel Sanchez-Cisneros and Fernando Aparicio Gali FBK-irst : A Multi-Phase Kernel Based Approach for Drug-Drug Interaction Detection and Classification that Exploits Linguistic Information Md. Faisal Mahbub Chowdhury and Alberto Lavelli WBI-DDI: Drug-Drug Interaction Extraction using Majority Voting Philippe Thomas, Mariana Neves, Tim Rockt\u00e4schel and Ulf Leser WBI-NER: The impact of domain-specific features on the performance of identifying and classifying mentions of drugs Tim Rockt\u00e4schel, Torsten Huber, Michael Weidlich and Ulf Leser UMCC DLSI: Semantic and Lexical features for detection and classification Drugs in biomedical texts Armando Collazo, Alberto Ceballo, Dennys D. Puig, Yoan Guti\u00e9rrez, Jos\u00e9 I. Abreu, Roger P\u00e9rez, Antonio Fern\u00e1ndez Orqu\u00edn, Andr\u00e9s Montoyo, Rafael Mu\u00f1oz and Franc Camara NIL UCM: Extracting Drug-Drug interactions from text through combination of sequence and tree kernels Behrouz Bokharaeian and ALBERTO DIAZ UTurku: Drug Named Entity Recognition and Drug-Drug Interaction Extraction Using SVM Classification and Domain Knowledge Jari Bj\u00f6rne, Suwisa Kaewphan and Tapio Salakoski LASIGE: using Conditional Random Fields and ChEBI ontology Tiago Grego, Francisco Pinto and Francisco M Couto UWM-TRIADS: Classifying Drug-Drug Interactions with Two-Stage SVM and Post- Processing Majid Rastegar-Mojarad, Richard D. Boyce and Rashmi Prasad xxxv Day 3: Saturday June 15, 2013 (continued) SCAI: Extracting drug-drug interactions using a rich feature vector Tamara Bobic, Juliane Fluck and Martin Hofmann-Apitius UColorado SOM: Extraction of Drug-Drug Interactions from Biomedical Text using Knowledge-rich and Knowledge-poor Features Negacy Hailu, Lawrence E. Hunter and K. Bretonnel Cohen SemEval-2013 Task 13: Word Sense Induction for Graded and Non-Graded Senses David Jurgens and Ioannis Klapaftis UoS: A Graph-Based System for Graded Word Sense Induction David Hope and Bill Keller AI-KU: Using Substitute Vectors and Co-Occurrence Modeling For Word Sense Induction and Disambiguation Osman Baskaya, Enis Sert, Volkan Cirik and Deniz Yuret unimelb: Topic Modelling-based Word Sense Induction Jey Han Lau, Paul Cook and Timothy Baldwin xxxvi", | |
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| "text": "timely and impressive panel on Towards Deep Natural Language Understanding,", | |
| "content": "<table><tr><td>featuring the following panelists:</td></tr><tr><td>-Kevin Knight (USC/Information Sciences Institute)</td></tr><tr><td>-Chris Manning (Stanford University)</td></tr><tr><td>-Martha Palmer (University of Colorado at Boulder)</td></tr><tr><td>-Owen Rambow (Columbia University)</td></tr><tr><td>-Dan Roth (University of Illinois at Urbana-Champaign)</td></tr><tr><td>\u2022 A Reception and Shared Task Poster Session in the evening, thanks to the generous</td></tr><tr><td>sponsorship of the DARPA Deft program.</td></tr></table>" | |
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