Editing Link grammar (section)

==Applications==
[[File:Abiword grammar.jpg|thumb|[[AbiWord]] checks grammar using link grammar]] 
[[AbiWord]],<ref name="AbiWord — Link Grammar Parser"/> a [[Free software|free]] [[word processor]], uses link grammar for on-the-fly grammar checking. Words that cannot be linked anywhere are underlined in green.

The semantic relationship extractor RelEx,<ref>{{Cite web |url=http://opencog.org/wiki/RelEx_Dependency_Relationship_Extractor |title=RelEx Dependency Relationship Extractor |access-date=2013-11-21 |archive-url=https://web.archive.org/web/20090728162235/http://opencog.org/wiki/RelEx_Dependency_Relationship_Extractor |archive-date=2009-07-28 |url-status=dead }}</ref> layered on top of the link grammar library, generates a [[dependency grammar]] output by making explicit the semantic relationships between words in a sentence. Its output can be classified as being at a level between that of SSyntR and DSyntR of [[Meaning-Text Theory]]. It also provides framing/grounding, [[anaphora resolution]], head-word identification, [[lexical chunk]]ing, part-of-speech identification, and tagging, including entity, date, money, gender, etc. tagging. It includes a compatibility mode to generate dependency output compatible with the [[Stanford parser]],<ref>[http://nlp.stanford.edu/software/lex-parser.shtml The Stanford Parser: A statistical parser]</ref> and Penn [[Treebank]]<ref>[http://www.cis.upenn.edu/~treebank/ The Penn Treebank Project] {{webarchive|url=https://web.archive.org/web/20131109202842/http://www.cis.upenn.edu/~treebank/ |date=2013-11-09 }}</ref>-compatible [[Part-of-speech tagging|POS tagging]].

Link grammar has also been employed for [[information extraction]] of 
biomedical texts<ref>{{Cite conference |author1=Jing Ding |author2=Daniel Berleant |author3=Jun Xu |author4=Andy W. Fulmer |title=Extracting biochemical interactions from MEDLINE using a link grammar parser |book-title=Proceedings of the Fifteenth IEEE Conference on Tools with Artificial Intelligence (ICTAI), 2003 |date=November 2003 |pages=467&ndash;471 |isbn=0-7695-2038-3 |url=https://ualr.edu/jdberleant/papers/LGPmanuscript8-8-03a.pdf |archive-url=https://wayback.archive-it.org/all/20110331201726/http://ifsc.ualr.edu/jdberleant/papers/LGPmanuscript8-8-03a.pdf |url-status=dead |archive-date=2011-03-31 |access-date=2023-08-27 }}</ref><ref>Sampo Pyysalo, Tapio Salakoski, Sophie Aubin and Adeline Nazarenko, "[http://www.biomedcentral.com/1471-2105/7/S3/S2 Lexical Adaptation of Link Grammar to the Biomedical Sublanguage: a Comparative Evaluation of Three Approaches]", ''BMC Bioinformatics'' '''7'''(Suppl 3):S2 (2006).</ref> and 
events described in news articles,<ref>{{Cite conference
 |author1=Harsha V. Madhyastha |author2=N. Balakrishnan |author3=K. R. Ramakrishnan | title = Event Information Extraction Using Link Grammar
 | book-title = 13th International WorkShop on Research Issues in Data Engineering: Multi-lingual Information Management (RIDE'03)
 | pages = 16
 | doi = 10.1109/RIDE.2003.1249841 
 | year = 2003
}}</ref> as well as experimental [[machine translation]] systems from English to German, Turkish, Indonesian.<ref>{{Cite conference
 |author1=Teguh Bharata Adji |author2=Baharum Baharudin |author3=Norshuhani Zamin | title = Applying Link Grammar Formalism in the Development of English-Indonesian Machine Translation System
 | book-title = Intelligent Computer Mathematics, 9th International Conference, AISC 2008, 15th Symposium, Calculemus 2008, 7th International Conference, Birmingham, UK, Proceedings
 | pages = 17–23
 | doi = 10.1007/978-3-540-85110-3_3
 | year = 2008
 }}</ref> and [[Persian language|Persian]].<ref>A.Sajadi and M.R Borujerdi, "Machine Translation Using Link Grammar", Submitted
to the ''Journal of Computational Linguistics'', MIT Press (Feb 2009)</ref><ref>Sajadi, A., Borujerdi, M. "Machine Translation Based on Unification Link Grammar" ''Journal of Artificial Intelligence Review''. DOI=10.1007/s10462-011-9261-7, Pages 109-132, 2013.</ref>

The link grammar link dictionary is used to generate and verify the syntactic correctness of three different [[natural language generation]] systems: NLGen,<ref>Ruiting Lian, ''et al'', "Sentence generation for artificial brains: a glocal similarity matching approach", Neurocomputing (Elsevier) (2009, submitted for publication).</ref> NLGen2<ref>Blake Lemoine, [http://www.louisiana.edu/~bal2277/NLGen2.doc NLGen2: A Linguistically Plausible, General Purpose Natural Language Generation System] (2009)</ref> and microplanner/surreal.<ref>[http://wiki.opencog.org/w/Microplanner Microplanner] and [http://wiki.opencog.org/w/Surface_Realization_(SuReal) Surface Realization (SuReal)]</ref> It is also used as a part of the NLP pipeline in the [[OpenCog]] AI project.