Generation Challenges 2011 Surface Realisation Shared Task ========================================================== Call for Pre-Registration and Sample Data Release ------------------------------------------------- We invite teams of researchers to pre-register now for the GenChal'11 Surface Realisation Shared Task (SR 2011) by filling in the registration form on the SR Task website (http://www.nltg.brighton.ac.uk/research/sr-task). Once registered, teams will be given access to sample data for the SR Task to familiarise themselves with the two common-ground input representation formats we have developed and to provide comment and feedback to us by March 25, 2011. The complete SR Task training and development data will be distributed on March 31, and the deadline for submitting system outputs will be in early August (exact date to be confirmed). Below we provide a brief overview of the SR Task. For more information please visit the SR Task website: http://www.nltg.brighton.ac.uk/research/sr-task SR Task: The task for participating teams is to develop systems that map (one of) the common-ground input representations to surface word strings (fully realised sentences), and to submit system outputs for the inputs in the test data set. Data: The SR Task data is derived from the CoNLL-08 corpus which itself merges data from several other corpora (the WSJ Treebank, the BBN Corpus, Propbank and Nombank). We have processed and adapted this data to make it useful for generation tasks. Evaluation: Submitted system outputs will be evaluated by a variety of automatic metrics and human-assessed quality criteria. Common-ground Input Representations: 1. Shallow: Each word and punctuation marker is represented as a node in a syntactic dependency tree. Information at each node consists of a word's lemma, a coarse-grained POS-tag and, where appropriate, number and tense features and sense tag IDs. Edges between nodes are labelled with syntactic labels. 2. Deep: Graphs containing semantic relations when available, shallow relations otherwise. Information at each node consists of a word's lemma and, where appropriate, number and tense features and sense tag IDs. No POS tags are given for the deep representation. Commas have been removed from the deep representation, as have some function words. For both shallow and deep representations relations are arbitrarily ordered. Sentences have single sentence roots. Organising Team: Anja Belz, NLTG, University of Brighton, UK Josef van Genabith, CNGL, Dublin City University, Ireland Deirdre Hogan, CNGL, Cublin City University, Ireland Amanda Stent, AT&T Labs Research Inc., US Mike White, Department of Linguistics, The Ohio State University, US Additional members of Common-ground Input Representation Working Group: Bernd Bohnet, IMS, University of Stuttgart, Germany Johan Bos, Groningen University, Netherlands Aoife Cahill, IMS, University of Stuttgart, Germany Charles Callaway, University of Haifa, Israel Pablo Gervas, Universidad Complutense de Madrid, Spain Stephan Oepen, University of Oslo, Norway Leo Wanner, Information and Communication Technologies, UPF, Barcelona, Spain SR Task contact email: nlg-stec@itri.brighton.ac.uk SR Task website: http://www.nltg.brighton.ac.uk/research/sr-task