Download JAR files tagged by grammars with all dependencies

Eidos is an open-domain machine reading system designed by the Computational Language Understanding (CLU) Lab at the University of Arizona for the World Modelers DARPA program. It uses a cascade of Odin grammars to extract events from free text.

Eidos is an open-domain machine reading system designed by the Computational Language Understanding (CLU) Lab at the University of Arizona for the World Modelers DARPA program. It uses a cascade of Odin grammars to extract events from free text.

parboiled is a mixed Java/Scala library providing for lightweight and easy-to-use, yet powerful and elegant parsing of arbitrary input text based on Parsing expression grammars (PEGs). This bundle wraps two different libraries, parboiled-core and parboiled-java, as they offer classes in the same package path

This project is a parser, validator and normalizer implementation for shorthand lipid nomenclatures, base on the Grammar of Succinct Lipid Nomenclatures project. Goslin defines multiple grammers compatible with ANTLRv4 for different sources of shorthand lipid nomenclature. This allows to generate parsers based on the defined grammars, which provide immediate feedback whether a processed lipid shorthand notation string is compliant with a particular grammar, or not.

BNFParser is a Backus-Naur Form Framework (https://en.wikipedia.org/wiki/Backus%E2%80%93Naur_Form) for Java The BNFParser Framework offers 3 basic services of general interest to developers: 1. String Tokenization via the BNFTokenizerFactory and BNFToken classes 2. Property Key/Value mapper via PropertyParser 3. Text Parsing/Validation via Grammars

This is an open source library for parsing text-based inputs. PARSER makes use of context-free grammars to validate and parse sentences. Having specified such a grammar, the library takes care of parsing text-based inputs and returns a tree of nodes that represents the parsed sentence. Furthermore, it provides ways for interpreting and refining the returned tree of nodes. In essence, the library aims to remove the pain of parsing and instead allow focusing on processing and interpreting parsed results.

This module contains a more general approach to construct AlignmentAlgorithms by relying on the theoretical concept of Algebraic Dynamic Programming (ADP) as developed by Giegerich et al. ADP defines four ingredients for an alignment algorithm: 1.) A signature that defines the permitted alignment operations. Operations are just function templates with an associated arity, meaning the number of arguments it takes from the left sequence and from the right sequence. In the TCSAlignmentToolbox we have a fixed signature with the following operations: REPLACEMENT(1, 1), DELETION(1, 0), INSERTION(0, 1), SKIPDELETION(1, 0) and SKIPINSERTION(0, 1) 2.) A regular tree grammar that produces alignments, that is: sequences of operations, in a restricted fashion. 3.) An algebra that can translate such trees to a cost. In the TCSAlignmentToolbox this is a Comparator. 4.) A choice function, in case of the TCSAlignmentToolbox: the strict minimum or the soft minimum. An alignment algorithm in the TCSAlignmentToolbox sense of the word then is the combination of choice function and grammar. While we provide hardcoded versions of these combinations in the main package, the adp package allows you to create your own grammars. You can combine them with a choice function by instantiating one of the Algorithm classes provided in this package with a grammar of your choice. For example: AlignmentAlgorithm algo = new SoftADPScoreAlgorithm(my_grammar, comparator); creates an alignment algorithm that implicitly produces all possible alignments your grammar can construct with the given input, translates them to a cost using the algebra/comparator you provided and applies the soft minimum to return the score. This all gets efficient by dynamic programming. Note that there is runtime overhead when using this method in comparison with the hardcoded algorithms. But for complicated grammars this is a much easier way to go. For more information on the theory, please refer to my master's thesis: "Adaptive Affine Sequence Alignment using Algebraic Dynamic Programming"