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Supercombinator Set Construction from a Context-Free Representation of Text
- Source :
- Annals of computer science and information systems, Vol 8, Pp 503-512 (2016), FedCSIS
- Publication Year :
- 2016
- Publisher :
- Polish Information Processing Society, 2016.
-
Abstract
- Grammars might be used for various other aspects, than just to represent a language. Grammar inference is a large field which main goal is the construction of grammars from various sources. Written text might be analysed indirectly with the use of such inferred grammars. Grammars acquired from processed text might grow into large structures as the inference process could be continuous. We present a method to decompose and store grammars into a non-redundant set of lambda calculus supercombinators. Grammars decomposition is based on their structure and each distinct element is stored only once in such a structure. We present a method that can create such a set from any context-free grammar. To prove this and to show the possible applications in the field of natural language processing we present a case study performed on samples from two books. Those samples are the entire Book of Genesis from The King James Bible and the first 24 chapters of War and peace by Tolstoy. We obtain context-free grammars with the Sequitur algorithm and then we process them with our method. The results show significant decline in the number of grammar elements in all cases.
- Subjects :
- lcsh:T58.5-58.64
business.industry
Programming language
Computer science
lcsh:Information technology
Context-sensitive grammar
020207 software engineering
02 engineering and technology
Context-free grammar
computer.software_genre
lcsh:QA75.5-76.95
Tree-adjoining grammar
Ambiguous grammar
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Indexed grammar
Definite clause grammar
Artificial intelligence
lcsh:Electronic computers. Computer science
L-attributed grammar
business
Phrase structure grammar
computer
Natural language processing
Subjects
Details
- Language :
- English
- ISSN :
- 23005963
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- Annals of computer science and information systems
- Accession number :
- edsair.doi.dedup.....13a9545b9227cd54a69fc25ca65c79c7