TAILIEUCHUNG - Báo cáo khoa học: "Coreference Resolution Using Semantic Relatedness Information from Automatically Discovered Patterns"

Semantic relatedness is a very important factor for the coreference resolution task. To obtain this semantic information, corpusbased approaches commonly leverage patterns that can express a specific semantic relation. The patterns, however, are designed manually and thus are not necessarily the most effective ones in terms of accuracy and breadth. To deal with this problem, in this paper we propose an approach that can automatically find the effective patterns for coreference resolution. We explore how to automatically discover and evaluate patterns, and how to exploit the patterns to obtain the semantic relatedness information. . | Coreference Resolution Using Semantic Relatedness Information from Automatically Discovered Patterns Xiaofeng Yang Jian Su Institute for Infocomm Research 21 Heng Mui Keng Terrace Singapore 119613 xiaofengy sujian @ Abstract Semantic relatedness is a very important factor for the coreference resolution task. To obtain this semantic information corpusbased approaches commonly leverage patterns that can express a specific semantic relation. The patterns however are designed manually and thus are not necessarily the most effective ones in terms of accuracy and breadth. To deal with this problem in this paper we propose an approach that can automatically find the effective patterns for coreference resolution. We explore how to automatically discover and evaluate patterns and how to exploit the patterns to obtain the semantic relatedness information. The evaluation on ACE data set shows that the pattern based semantic information is helpful for coreference resolution. 1 Introduction Semantic relatedness is a very important factor for coreference resolution as noun phrases used to refer to the same entity should have a certain semantic relation. To obtain this semantic information previous work on reference resolution usually leverages a semantic lexicon like WordNet Vieira and Poe-sio 2000 Harabagiu et al. 2001 Soon et al. 2001 Ng and Cardie 2002 . However the drawback of WordNet is that many expressions especially for proper names word senses and semantic relations are not available from the database Vieira and Poe-sio 2000 . In recent years increasing interest has 528 been seen in mining semantic relations from large text corpora. One common solution is to utilize a pattern that can represent a specific semantic relation . X such as Y for is-a relation and X and other Y for other-relation . Instantiated with two given noun phrases the pattern is searched in a large corpus and the occurrence number is used as a measure of their semantic relatedness

• Báo cáo khoa học
• Coreference Resolution
• Semantic Relatedness Information
• Automatically Discovered Patterns
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• VNU Journal of Science
• Coreference resolution in Vietnamese electronic medical records
• Vietnamese electronic medical records
• Adjective mentions possible
• Coreference resolution in Vietnamese EMRs
• Unsupervised Event Coreference Resolution
• Rich Linguistic Features
• Long Papers
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• Coreference Resolution across Corpora
• Coding Schemes
• and Preprocessing Information
• Coreference Resolution with Reconcile
• Veselin Stoyanov
• Conundrums in Noun Phrase Coreference Resolution
• Making Sense
• State of the Art
• Bootstrapping Coreference Resolution
• Word Associations
• Hamidreza Kobdani
• World Knowledge
• Altaf Rahman and Vincent Ng
• State of the art NLP
• Approaches to Coreference Resolution
• Theory and Practical Recipes
• An Entity Mention Model
• Inductive Logic Programming
• Enforcing Transitivity
• Jenny Rose Finkel and Christopher D
• Manning
• Conditional Modality Fusion
• Jacob Eisenstein and Randall Davis
• Semantic Class Induction
• Vincent Ng
• A Modular Toolkit
• Unsupervised Coreference Resolution
• Nonparametric Bayesian Model
• Aria Haghighi and Dan Klein
• Machine Learning for Coreference Resolution
• From Local Classification to Global Ranking
• A Mention Synchronous Coreference Resolution Algorithm
• the Bell Tree
• Xiaoqiang Luo and Abe Ittycheriah Hongyan Jing and Nanda Kambhatla and Salim Roukos
• Learning Noun Phrase Anaphoricity to Improve Coreference Resolution
• Issues in Representation and Optimization
• Competition Learning Approach
• Xiaofeng Yang
• Reference Resolution
• beyond Coreference
• Conceptual Frame and its Application
• Improving Machine Learning
• Vincent Ng and Claire Cardie
• Semantic Role Labeling
• Simone Paolo Ponzetto and Michael Strube
• scientific reports
• model language
• process natural language
• Optimization in Coreference Resolution Is Not Needed
• A Nearly Optimal Algorithm
• Intensional Constraints
• BMC Bioinformatics
• Coreference annotation
• Colorado Richly Annotated Full Text
• Syntactic annotation
• Domain specific ontologies