As mentioned in Section 1, MSRSeg is designed as an adaptive segmenter that consists of two components: (1) a generic segmenter that can adapt to different domain vocabularies, and (2) a set of output adaptors, learned from application data, for adapting to different application-specific standards.
we evaluate MSRSeg using five corpora, each corresponding to a different standard, and consistent train-test splits, as shown in Table 4.