Expressing rhetorical relations in instructional text: a case study of the purpose relation
Computational Linguistics
Learning features that predict cue usage
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
The rhetorical parsing of natural language texts
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
A support tool for writing multilingual instructions
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
OKBC: a programmatic foundation for knowledge base interoperability
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Integrating discourse markers into a pipelined natural language generation architecture
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Disambiguating temporal-contrastive discourse connectives for machine translation
HLT-SS '11 Proceedings of the ACL 2011 Student Session
Multilingual annotation and disambiguation of discourse connectives for machine translation
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
| Hi-index | 0.00 |
Discourse markers ('cue words') are lexical items that signal the kind of coherence relation holding between adjacent text spans; for example, because, since, and for this reason are different markers for causal relations. Discourse markers are a syntactically quite heterogeneous group of words, many of which are traditionally treated as function words belonging to the realm of grammar rather than to the lexicon. But for a single discourse relation there is often a set of similar markers, allowing for a range of paraphrases for expressing the relation. To capture the similarities and differences between these, and to represent them adequately, we are developing DiMLex, a lexicon of discourse markers. After describing our methodology and the kind of information to be represented in DiMLex, we briefly discuss its potential applications in both text generation and understanding.