Sentence examples for parser provides from inspiring English sources
The DOM parser provides a tree structure for the XML format of the student's and teacher's Word documents to serve the next steps of the assessment process.
The parser provides Stanford Dependencies output as well as phrase structure trees.
Next to lexical features, dependency parsing (created using Stanford parser) provides an insight into the entire grammatical structure of the sentence and was performed using the Stanford CoreNLP library (http://nlp.stanford.edu/software/corenlp.shtml).shtml
The following pointed text has been modified in the manuscript: Next to lexical features, dependency parsing (created using Stanford parser) provides an insight into the entire grammatical structure of the sentence 37 and was performed using the Stanford CoreNLP library (http://nlp.stanford.edu/software/corenlp.shtml ).shtml
An efficient alternative to implementing custom-made parsers is provided by parser generators (e.g., Yacc, Bison, ANTLR).
For each format, apart from parsers, BioClojure provides accessors specific to that format (see https://github.com/s312569/clj-biosequence for detailed documentation).
The grammar formalisms that come with parser generators provide different approaches for defining operator precedence.
Each parser is provided as a class whose objects are tied to a file name or open file or stream and work as iterator generators, i.e. they may be used in the head of a for loop and will yield a sequence of record objects that are taken up by the loop variable.
Parsers are provided for reading, amongst others, Blast reports (Altschul et al., 1997), ABI chromatograms and NCBI taxonomy definitions.
However, alternative occupancies or models can be read, and parsers are provided for key header records; CONECT and MASTER records are correctly handled if atom numbering changes.
Similarly to GoR, NAGA enables users to create more precise queries than in the case of using natural language parsers, however, it provides more functionality.
