Abstract
Tree adjoining grammars (TAGs) are mildly context-sensitive psycholinguistic formalisms that are hard to parse. All standard TAG parsers have a worst-case complexity of O(n6), despite being one of the most linguistically relevant grammars. For comprehensive syntax analysis, especially of ambiguous natural language constructs, most TAG parsers will have to run exhaustively, bringing them close to worst-case runtimes, in order to derive all possible parse trees. In this paper, we present a new and intuitive genetic algorithm, a few fitness functions and an implementation strategy for lexicalised-TAG parsing, so that we might get multiple ambiguous derivations efficiently.
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Menon, V.K., Soman, K.P. (2018). A New Evolutionary Parsing Algorithm for LTAG. In: Sa, P., Sahoo, M., Murugappan, M., Wu, Y., Majhi, B. (eds) Progress in Intelligent Computing Techniques: Theory, Practice, and Applications. Advances in Intelligent Systems and Computing, vol 518. Springer, Singapore. https://doi.org/10.1007/978-981-10-3373-5_45
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