Foundations of statistical natural language processing
Foundations of statistical natural language processing
Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Machine Learning
A non-projective dependency parser
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
A comparison of parsing technologies for the biomedical domain
Natural Language Engineering
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
An improved extraction pattern representation model for automatic IE pattern acquisition
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Computer-aided generation of multiple-choice tests
HLT-NAACL-EDUC '03 Proceedings of the HLT-NAACL 03 workshop on Building educational applications using natural language processing - Volume 2
A computer-aided environment for generating multiple-choice test items
Natural Language Engineering
Speech and Language Processing (2nd Edition)
Speech and Language Processing (2nd Edition)
Discovering relations among named entities from large corpora
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
A semantic approach to IE pattern induction
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Bidirectional inference with the easiest-first strategy for tagging sequence data
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Automatic question generation for vocabulary assessment
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Preemptive information extraction using unrestricted relation discovery
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
On-demand information extraction
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
A real-time multiple-choice question generation for language testing: a preliminary study
EdAppsNLP 05 Proceedings of the second workshop on Building Educational Applications Using NLP
EdAppsNLP 05 Proceedings of the second workshop on Building Educational Applications Using NLP
Learning relations from biomedical corpora using dependency trees
KDECB'06 Proceedings of the 1st international conference on Knowledge discovery and emergent complexity in bioinformatics
Developing a robust part-of-speech tagger for biomedical text
PCI'05 Proceedings of the 10th Panhellenic conference on Advances in Informatics
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In this paper, we investigate an unsupervised approach to Relation Extraction to be applied in the context of automatic generation of multiplechoice questions (MCQs). MCQs are a popular large-scale assessment tool making it much easier for test-takers to take tests and for examiners to interpret their results. Our approach to the problem aims to identify the most important semantic relations in a document without assigning explicit labels to them in order to ensure broad coverage, unrestricted to predefined types of relations. In this paper, we present an approach to learn semantic relations between named entities by employing a dependency tree model. Our findings indicate that the presented approach is capable of achieving high precision rates, which are much more important than recall in automatic generation of MCQs, and its enhancement with linguistic knowledge helps to produce significantly better patterns. The intended application for the method is an e-Learning system for automatic assessment of students' comprehension of training texts; however it can also be applied to other NLP scenarios, where it is necessary to recognise the most important semantic relations without any prior knowledge as to their types.