To build such systems, we train a family of Naive Bayes classifiers on a large set of examples that are generated automatically from two corpora: a corpus of 41,147,805 English sentences that have no annotations, and BLIPP, a corpus of 1,796,386 automatically parsed English sentences (Charniak, 2000), which is available from the Linguistic Data Consortium (www.ldc.upenn.edu).
given as input sentence pairs such as those shown in (1)-(2), we develop techniques and programs that label the relations that hold between these sentence pairs as CONTRAST, CAUSE-EXPLANATION-EVIDENCE, CONDITION, ELABO-RATION or NONE-OF-THE-ABOVE, even when the discourse relations are not explicitly signalled by discourse markers.