| CoNLL-2008 | Coling 2008 | ICCL |
Conference PROGRAMME
Saturday, August 16, 2008 | |
| 8:30–8:50 | Opening Remarks |
| Session 1: Parsing | |
| 8:50–9:15 | Semantic Parsing for High-Precision Semantic Role Labelling Paola Merlo and Gabriele Musillo |
| 9:15–9:40 | TAG, Dynamic Programming, and the Perceptron for Efficient, Feature-Rich Parsing Xavier Carreras, Michael Collins and Terry Koo |
| 9:40–10:05 | A Fast Boosting-based Learner for Feature-Rich Tagging and Chunking Tomoya Iwakura and Seishi Okamoto |
| 10:05–10:30 | Linguistic features in data-driven dependency parsing Lilja Ovrelid |
| 10:30-11:00 | coffee break |
| Session 2: Semantics | |
| 11:00–11:25 | Transforming Meaning Representation Grammars to Improve Semantic Parsing Rohit Kate |
| 11:25–11:50 | Using LDA to detect semantically incoherent documents Hemant Misra, Olivier Cappe and Francois Yvon |
| 11:50–12:40 | Invited talk by Regina Barzilay |
| 12:40–14:00 | Lunch |
| Shared Task | |
| 14:00–14:30 | The CoNLL 2008 Shared Task on Joint Parsing of Syntactic and Semantic Dependencies Mihai Surdeanu, Richard Johansson, Adam Meyers, Lluís Màrquez and Joakim Nivre |
| Oral Presentations | |
| 14:30–14:50 | A Latent Variable Model of Synchronous Parsing for Syntactic and Semantic Dependencies James Henderson, Paola Merlo, Gabriele Musillo and Ivan Titov |
| 14:50–15:10 | Dependency-based Syntactic–Semantic Analysis with PropBank and NomBank Richard Johansson and Pierre Nugues |
| 15:10–15:30 | A Joint Model for Parsing Syntactic and Semantic Dependencies Xavier Lluís and Lluís Màrquez |
| 15:30–15:50 | Collective Semantic Role Labelling with Markov Logic Sebastian Riedel and Ivan Meza-Ruiz |
| 15:50–16:10 | Hybrid Learning of Dependency Structures from Heterogeneous Linguistic Resources Yi Zhang, Rui Wang and Hans Uszkoreit |
| 16:10-16:20 | Closing remarks |
| 16:20-16:45 | Coffee break |
| Poster session 16:45–18:00 | |
| Parsing Syntactic and Semantic Dependencies with Two Single-Stage Maximum Entropy Models Hai Zhao and Chunyu Kit | |
| A Combined Memory-Based Semantic Role Labeler of English Roser Morante, Walter Daelemans and Vincent Van Asch | |
| A Puristic Approach for Joint Dependency Parsing and Semantic Role Labeling Alexander Volokh and Günter Neumann | |
| Discriminative Learning of Syntactic and Semantic Dependencies Lu Li, Shixi Fan, Xuan Wang and Xiaolong Wang | |
| Discriminative vs. Generative Approaches in Semantic Role Labeling Deniz Yuret, Mehmet Ali Yatbaz and Ahmet Engin Ural | |
| A Pipeline Approach for Syntactic and Semantic Dependency Parsing Yotaro Watanabe, Masakazu Iwatate, Masayuki Asahara and Yuji Matsumoto | |
| Semantic Dependency Parsing using N-best Semantic Role Sequences and Roleset Information Joo-Young Lee, Han-Cheol Cho and Hae-Chang Rim | |
| A Cascaded Syntactic and Semantic Dependency Parsing System Wanxiang Che, Zhenghua Li, Yuxuan Hu, Yongqiang Li, Bing Qin, Ting Liu and Sheng Li | |
| The Integration of Dependency Relation Classification and Semantic Role Labeling Using Bilayer Maximum Entropy Markov Models Weiwei Sun, Hongzhan Li and Zhifang Sui | |
| Mixing and Blending Syntactic and Semantic Dependencies Yvonne Samuelsson, Oscar Täckström, Sumithra Velupillai, Johan Eklund, Mark Fishel and Markus Saers | |
| Dependency Tree-based SRL with Proper Pruning and Extensive Feature Engineering Hongling Wang, Honglin Wang, Guodong Zhou and Qiaoming Zhu | |
| DeSRL: A Linear-Time Semantic Role Labeling System Massimiliano Ciaramita, Giuseppe Attardi, Felice Dell’Orletta and Mihai Surdeanu | |
| Probabilistic Model for Syntactic and Semantic Dependency Parsing Enhong Chen, Liu Shi and Dawei Hu | |
| Applying Sentence Simplification to the CoNLL-2008 Shared Task David Vickrey and Daphne Koller | |
Sunday, August 17, 2008 | |
| Session 1: Language Acquisition I | |
| 8:50–9:15 | Picking them up and Figuring them out: Verb-Particle Constructions, Noise and Idiomaticity Carlos Ramisch, Aline Villavicencio, Leonardo Moura and Marco Idiart |
| 9:15–9:40 | Fast Mapping in Word Learning: What Probabilities Tell Us Afra Alishahi, Afsaneh Fazly and Suzanne Stevenson |
| 9:40–10:05 | Improving Word Segmentation by Simultaneously Learning Phonotactics Daniel Blanchard and Jeffrey Heinz |
| 10:05–10:30 | A MDL-based Model of Gender Knowledge Acquisition Harmony Marchal, Benoît Lemaire, Maryse Bianco and Philippe Dessus |
| 10:30–11:00 | Coffee break |
| Session 2: Language Acquisition II | |
| 11:00–11:25 | Baby SRL: Modeling Early Language Acquisition. Michael Connor, Yael Gertner, Cynthia Fisher and Dan Roth |
| 11:25–11:50 | An Incremental Bayesian Model for Learning Syntactic Categories Christopher Parisien, Afsaneh Fazly and Suzanne Stevenson |
| 11:50–12:40 | Invited talk by Nick Chater |
| 12:40–14:00 | Lunch |
| 13:30–14:00 | SIGNLL Business Meeting |
| Session 3: Semantic extraction | |
| 14:00–14:25 | Fully Unsupervised Graph-Based Discovery of General-Specific Noun Relationships from Web Corpora Frequency Counts Gaël Dias, Raycho Mukelov and Guillaume Cleuziou |
| 14:25–14:50 | Acquiring Knowledge from the Web to be used as Selectors for Noun Sense Disambiguation Hansen A. Schwartz and Fernando Gomez |
| 14:50–15:15 | Automatic Chinese Catchword Extraction Based on Time Series Analysis Han Ren, Donghong Ji, Jing Wan and Lei Han |
| 15:15–15:40 | Easy as ABC? Facilitating Pictorial Communication via Semantically Enhanced Layout Andrew B. Goldberg, Xiaojin Zhu, Charles R. Dyer, Mohamed Eldawy and Lijie Heng |
| 15:40–16:00 | Coffee break |
| Session 4: Morphology, MT and Generation | |
| 16:00–16:25 | A Nearest-Neighbor Approach to the Automatic Analysis of Ancient Greek Morphology John Lee |
| 16:25–16:50 | Context-based Arabic Morphological Analysis for Machine Translation Thuy Linh Nguyen and Stephan Vogel |
| 16:50–17:15 | A Tree-to-String Phrase-based Model for Statistical Machine Translation Thai Phuong Nguyen, Akira Shimazu, Tu Bao Ho, Minh Le Nguyen and Vinh Van Nguyen |
| 17:15–17:40 | Trainable Speaker-Based Referring Expression Generation Giuseppe Di Fabbrizio, Amanda Stent and Srinivas Bangalore |
| 17:40–18:00 | Closing remarks and best paper award |