Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Morphology and reranking for the statistical parsing of Spanish
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Using machine-learning to assign function labels to parser output for Spanish
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Design of a multi-lingual, parallel-processing statistical parsing engine
HLT '02 Proceedings of the second international conference on Human Language Technology Research
A tree-to-tree model for statistical machine translation
A tree-to-tree model for statistical machine translation
The naproche project controlled natural language proof checking of mathematical texts
CNL'09 Proceedings of the 2009 conference on Controlled natural language
MathAbs: a representational language for mathematics
Proceedings of the 8th International Conference on Frontiers of Information Technology
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
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Informal Mathematical Discourse (IMD) is characterized by the mixture of natural language and symbolic expressions in the context of textbooks, publications in mathematics and mathematical proof. We focused the IMD processing at the low level of discourse. In this paper, we proposed the preprocessing phase before the IMD structure analysis within the context of Controlled Natural Language (CNL). Our contribution is defined in context of the IMD processing and the use of machine learning; first, we present a CNL, a pure corpus and Matemathical Treebank for processing IMD; second, we present a preprocessing phase for IMD analysis with connectives disambiguation and verbs treatment, finally, we found a satisfactory result on input text parsing using a statistical parsing model. We will propagate these results for classification of argumentative informal practices via the low level discourse in IMD processing.