… memory-based learning approaches to shallow parsing and … detection, noun phrase parsing
and full parsing. We use … the performance of the memory-based learner. Our approach is …

… present a memory-based learning (MBL) approach to shallow parsing in which POS tagging,
chunking, and identification of syntactic relations are formulated as memory-based modules…

… This paper presents a novel memorybased learning method that recognizes shallow
patterns in new text based on a bracketed training corpus. The examples are stored as-is, in …

… This paper presents a novel memorybased learning method that recognizes shallow patterns
in new text based on a bracketed training corpus. The examples are stored as-is, in e cient …

… Feature-Rich Memory-Based Classification for Information … In our approach to memory-based
shallow parsing, we carve up … Output of some memory-based modules is used as input by …

… to this thesis, memory-based shallow parsing has already been … In principle, however,
memory-based shallow parsing is … at adopting the memorybased shallow parsing method for …

… We describe a case study in which a memory-based learning algorithm is trained to
simultaneously chunk sentences and assign grammatical function tags to these chunks. We …

… In this paper, an existing memory-based shallow parsing method, which has been shown
to be effective for English, is applied to the CGN data to construct a shallow parser for spoken …

… Veenstra and Van den Bosch (2000) studied how the memory-based learning algorithm,
implemented in TiMBL software, performs with different settings. Memory-based learning …

… different parsing mechanisms, and the hypothesis that L2 learners adopt ‘shallow’ parsing
… In contrast to describing L1/L2 differences in terms of shallow parsing or capacity limitations, …