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	title        = {ShrdLite: Semantic Parsing Using a Handmade Grammar},
	abstract     = {This paper describes my approach for parsing robot commands, which was task 6 at SemEval 2014. My solution is to manually create a compact unification grammar. The grammar is highly ambiguous, and relies heavily on filtering the parse results by checking their consistency with the current world.

The grammar is small, consisting of not more than 25 grammatical and 60 lexical rules. The parser uses simple error correction together with a straightforward iterative deepening search. Nevertheless, with these very basic algorithms, the system still managed to get 86.1% correctness on the evaluation data. Even more interesting is that by making the parser slightly more robust, the accuracy of the system rises to 93.5%, and by adding one single word to the lexicon, the accuracy is boosted to 98.0%.},
	booktitle    = {SemEval-2014 Task 6: Supervised Semantic Parsing of Robotic Spatial Commands},
	author       = {Ljunglöf, Peter},
	year         = {2014},