The Theory and Practice of Discourse Parsing and Summarization
The Theory and Practice of Discourse Parsing and Summarization
Discourse relations: a structural and presuppositional account using lexicalised TAG
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
An unsupervised approach to recognizing discourse relations
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Sentence level discourse parsing using syntactic and lexical information
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Automatic detection of causal relations for Question Answering
MultiSumQA '03 Proceedings of the ACL 2003 workshop on Multilingual summarization and question answering - Volume 12
Using automatically labelled examples to classify rhetorical relations: An assessment
Natural Language Engineering
Discourse Connective Argument Identification with Connective Specific Rankers
ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
Discourse level opinion interpretation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Annotating discourse connectives in the Chinese Treebank
CorpusAnno '05 Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky
Revisiting readability: a unified framework for predicting text quality
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Developing an Arabic treebank: methods, guidelines, procedures, and tools
Semitic '04 Proceedings of the Workshop on Computational Approaches to Arabic Script-based Languages
SigDIAL '06 Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue
Using syntax to disambiguate explicit discourse connectives in text
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
A novel discourse parser based on support vector machine classification
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Automatic sense prediction for implicit discourse relations in text
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Recognizing implicit discourse relations in the Penn Discourse Treebank
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Probabilistic head-driven parsing for discourse structure
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Creating local coherence: an empirical assessment
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Kernel based discourse relation recognition with temporal ordering information
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Predicting discourse connectives for implicit discourse relation recognition
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Discourse structure and computation: past, present and future
ACL '12 Proceedings of the ACL-2012 Special Workshop on Rediscovering 50 Years of Discoveries
Discourse structure and language technology
Natural Language Engineering
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We present the first algorithms to automatically identify explicit discourse connectives and the relations they signal for Arabic text. First we show that, for Arabic news, most adjacent sentences are connected via explicit connectives in contrast to English, making the treatment of explicit discourse connectives for Arabic highly important. We also show that explicit Arabic discourse connectives are far more ambiguous than English ones, making their treatment challenging. In the second part of the paper, we present supervised algorithms to address automatic discourse connective identification and discourse relation recognition. Our connective identifier based on gold standard syntactic features achieves almost human performance. In addition, an identifier based solely on simple lexical and automatically derived morphological and POS features performs with high reliability, essential for languages that do not have high-quality parsers yet. Our algorithm for recognizing discourse relations performs significantly better than a baseline based on the connective surface string alone and therefore reduces the ambiguity in explicit connective interpretation.