This paper presents a brief description of Explanation-Based Learning (EBL), and argues that it is an approach to machine learning with signi cant potential for use in discourse processing. More speci cally, EBL can be used by systems that model discourse generation as goaldriven behavior, and that model discourse interpretation as recognizing the speaker's discourse goals. As evidence, we desc...

Discourse relation classification is an important component for automatic discourse parsing and natural language understanding. The performance bottleneck of a discourse parser comes from implicit discourse relations, whose discourse connectives are not overtly present. Explicit discourse connectives can potentially be exploited to collect more training data to collect more data and boost the p...

We present an implementation of a discourse parsing system for a lexicalized TreeAjoining Grammar for discourse, specifying the integration of sentence and discourse level processing. Our system is based on the assumption that the compositional aspects of semantics at the discourse-level parallel those at the sentence-level. This coupling is achieved by factoring away inferential semantics and ...

In this paper, we describe how the LIDAS System (Linguistic Discourse Analysis System), a discourse parser built as an implementation of the Unified Linguistic Discourse Model (U-LDM) uses information from sentential syntax and semantics along with lexical semantic information to build the Open Right Discourse Parse Tree (DPT) that serves as a representation of the structure of the discourse (P...

We present an implementation of a discourse parsing system for a lexicalized Tree-Ajoining Grammar for discourse, specifying the integration of sentence and discourse level processing. Our system is based on the assumption that the compositional aspects of semantics at the discourse-level parallel those at the sentence-level. This coupling is achieved by factoring away inferential semantics and...