| Abstract | In this paper, we develop an RST—style text-level discourse parser, based on the HILDA discourse parser (Hernault et al., 2010b). |
| Abstract | We also analyze the difficulty of extending traditional sentence-level discourse parsing to text-level parsing by comparing discourse-parsing performance under different discourse conditions. |
| Introduction | Research in discourse parsing aims to unmask such relations in text, which is helpful for many downstream applications such as summarization, information retrieval, and question answering. |
| Introduction | However, most existing discourse parsers operate on individual sentences alone, whereas discourse parsing is more powerful for text-level analysis. |
| Introduction | Therefore, in this work, we aim to develop a text-level discourse parser . |
| Related work | Discourse parsing was first brought to prominence by Marcu (1997). |
| Related work | Here we briefly review two fully implemented text-level discourse parsers with the state-of-the-art performance. |
| Related work | The HILDA discourse parser of Hemault and his colleagues (duVerle and Prendinger, 2009; Hernault et al., 2010b) is the first fully-implemented feature-based discourse parser that works at the full text level. |