SENSEVAL-3, the International Workshop on the Evaluation of Systems for the Semantic Analysis of Text 2004: all accepted papers
- A gloss-centered algorithm for disambiguation ↗Ganesh Ramakrishnan, B. Prithviraj, Pushpak Bhattacharyya
- An evaluation exercise for Romanian Word Sense Disambiguation ↗Rada Mihalcea, Vivi Năstase, Timothy Chklovski et al.
- Augmenting ensemble classification for Word Sense Disambiguation with a kernel PCA model ↗Marine Carpuat, Weifeng Su, Dekai Wu
- Class-based collocations for Word Sense Disambiguation ↗Tom O'Hara, Rebecca Bruce, Jeff Donner et al.
- Complementarity of lexical and simple syntactic features: The SyntaLex approach to Senseval-3 ↗Saif Mohammad, Ted Pedersen
- Context clustering for Word Sense Disambiguation based on modeling pairwise context similarities ↗Cheng Niu, Wei Li, Rohini K. Srihari et al.
- Contextual semantics for WSD ↗Eric Crestan
- Dependency based logical form transformations ↗Stephen Anthony, Jon Patrick
- GAMBL, genetic algorithm optimization of memory-based WSD ↗Bart Decadt, Véronique Hoste, Walter Daelemans et al.
- Generative models for semantic role labeling ↗Cynthia A. Thompson, Siddharth Patwardhan, Carolin Arnold
- Joining forces to resolve lexical ambiguity: East meets West in Barcelona ↗Richard Wicentowski, Grace Ngai, Dekai Wu et al.
- KUNLP system in Senseval-3 ↗Hee-Cheol Seo, Hae-Chang Rim, Soo-Hong Kim
- LCC's WSD systems for Senseval-3 ↗Adrian Novischi, Dan Moldovan, Paul Parker et al.
- Multi-component Word Sense Disambiguation ↗Massimiliano Ciaramita, Mark Johnson
- Optimizing feature set for Chinese Word Sense Disambiguation ↗Zheng-Yu Niu, Dong-Hong Ji, Chew-Lim Tan
- Pattern abstraction and term similarity for Word Sense Disambiguation: IRST at Senseval-3 ↗Carlo Strapparava, Alfio Gliozzo, Claudio Giuliano
- Probabilistic WSD in Senseval-3 ↗Judita Preiss
- SVM classification of FrameNet semantic roles ↗Dan Moldovan, Roxana Gîrju, Marian Olteanu et al.
- Semantic parsing based on FrameNet ↗Cosmin Adrian Bejan, Alessandro Moschitti, Paul Morărescu et al.
- Semantic role labeling with Boosting, SVMs, Maximum Entropy, SNOW, and Decision Lists ↗Grace Ngai, Dekai Wu, Marine Carpuat et al.
- Semantic role labelling with similarity-based generalization using EM-based clustering ↗Ulrike Baldewein, Katrin Erk, Sebastian Padó et al.
- SenseLearner: Minimally supervised Word Sense Disambiguation for all words in open text ↗Rada Mihalcea, Ehsanul Faruque
- Senseval automatic labeling of semantic roles using Maximum Entropy models ↗Namhee Kwon, Michael Fleischman, Eduard Hovy
- Senseval-3 logic forms: A system and possible improvements ↗Altaf Mohammed, Dan Moldovan, Paul Parker
- Senseval-3: The Catalan lexical sample task ↗Lluis Màrquez, Mariona Taulé, Antonia Martí et al.
- Senseval-3: The Italian all-words task ↗Marisa Ulivieri, Elisabetta Guazzini, Francesca Bertagna et al.
- Senseval-3: The Spanish lexical sample task ↗Lluis Màrquez, Mariona Taulé, Antonia Martí et al.
- Simple features for statistical Word Sense Disambiguation ↗Abolfazl Lamjiri, Osama El Demerdash, Leila Kosseim
- Structural semantic interconnection: a knowledge-based approach to Word Sense Disambiguation ↗Roberto Navigli, Paola Velardi
- Supervised Word Sense Disambiguation with Support Vector Machines and multiple knowledge sources ↗Yoong Keok Lee, Hwee Tou Ng, Tee Kiah Chia
- TALP system for the English lexical sample taskGerard Escudero, Lluis Màrquez, German Rigauour summary
- The Basque Country University system: English and Basque tasks ↗Eneko Agirre, David Martínez
- The Basque lexical-sample task ↗Eneko Agirre, Itziar Aldabe, Mikel Lersundi et al.
- The English all-words task ↗Benjamin Snyder, Martha Palmer
- The Italian lexical sample task at Senseval-3 ↗Bernardo Magnini, Danilo Giampiccolo, Alessandro Vallin
- The MITRE logical form generation system ↗Samuel Bayer, John Burger, John Greiff et al.
- The R2D2 team at Senseval-3 ↗Sonia Vázquez, Rafael Romero, Armando Suárez et al.
- The Senseval-3 English lexical sample taskRada Mihalcea, Timothy Chklovski, Adam Kilgarriffour summary
- The Senseval-3 Multilingual English-Hindi lexical sample task ↗Timothy Chklovski, Rada Mihalcea, Ted Pedersen et al.
- The Swarthmore College Senseval-3 system ↗Richard Wicentowski, Emily Thomforde, Adrian Packel
- The TALP systems for disambiguating WordNet glosses ↗Mauro Castillo, Francis Real, Jordi Asterias et al.
- The University of Alicante systems at Senseval-3 ↗Sonia Vázquez, Rafael Romero, Armando Suárez et al.
- The University of Amsterdam at Senseval-3: Semantic roles and Logic forms ↗David Ahn, Sisay Fissaha, Valentin Jijkoun et al.
- The University of Jaén Word Sense Disambiguation system ↗Manuel García-Vega, Miguel García-Cumbreras, M. Teresa Martín-Valdivia et al.
- The University of Maryland Senseval-3 system descriptions ↗Clara Cabezas, Indrajit Bhattacharya, Philip Resnik
- The “Meaning” system on the English all-words taskLuís Villarejo, Lluis Màrquez, Eneko Agirre et al.our summary
- The upv-unige-CIAOSENSO WSD system ↗Davide Buscaldi, Paolo Rosso, Francesco Masulli
- UBB system at Senseval-3 ↗Gabriela Şerban, Doina Tătar
- UBBNBC WSD system description ↗András Csomai
- Using a Word Sense Disambiguation system for translation disambiguation: the LIA-LIDILEM team experiment ↗Grégoire Moreau de Montcheuil, Marc El-Bèze, Boxing Chen et al.
- Using automatically acquired predominant senses for Word Sense Disambiguation ↗Diana McCarthy, Rob Koeling, Julie Weeds et al.
- WSD based on mutual information and syntactic patterns ↗David Férnandez-Amorós
- WSD for subcategorization acquisition task description ↗Judita Preiss, Anna Korhonen
- WSD system based on specialized Hidden Markov Model (upv-shmm-eaw) ↗Antonio Molina, Ferran Pla, Encarna Segarra
- Word Sense Disambiguation based on term to term similarity in a context space ↗Javier Artiles, Anselmo Penas, Felisa Verdejo
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