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1	AGGREGATION
	Gracheva, Varya; Crowgey, Joshua; Bender, Emily M.; O'Hara, Kelly; Wax, David; Zamaraeva, Olga; Ramaswamy, Swetha; Curtis, Chris; Oepen, Stephan; Flickinger, Dan; Bateman, Emma; Nordlinger, Rachel; Song, Sanghoun; Zhang, Claude; Lepp, Haley; Dermer, Laurie; Goodman, Michael Wayne; Howell, Kristen; Packard, Woodley; Lockwood, Michael Wayne; Fokkens, Antske; Hou, Joshua; Haeger, Mike; Burrel, Alex; Mills, Daniel P.; Halgrim, Scott; Heath, Jeff; Poulson, Laurie; Nielsen, Elizabeth; Drellishak, Scott; Inman, David; Xia, Fei; Trimble, TJ. - 2020
	Abstract: This archive is associated with the AGGREGATION project, which seeks to automatically generate HPSG grammars on the basis of Interlinnear Glossed Text data. For a detailed description of this project see Chapter 3 of Inferring Grammars from Interlinear Glossed Text: Extracting Typological and Lexical Properties for the Automatic Generation of HPSG Grammars, PhD thesis by Kristen Howell 2020. This archive includes the following: The AGGREGATION/BASIL syntactic inference repository from https://git.ling.washington.edu/agg/aggregation The MOM morphological inference repository from https://git.ling.washington.edu/agg/mom The Xigt framework for eXtensible Interlinear Glossed Text release 1.1 from https://github.com/xigt/xigt The Grammar Matrix Customization system http://matrix.ling.washington.edu/index.html Code, dependencies and sample data for running the AGGREGATION pipeline end to end. ; The AGGREGATION Project aims to bring the benefits of grammar engineering to language documentation without requiring field linguists to become grammar engineers. We achieve this by automatically creating precision grammars on the basis of analyses and annotations already produced by field linguists together with a typologically-grounded cross-linguistic grammar resource (the LinGO Grammar Matrix) and natural language processing techniques developed for high-resource languages. Precision grammars are machine-readable encodings of mutually-consistent linguistic hypotheses, in our case, concerning morphotactics, morphosyntax and the syntax-semantics interface. They can be used to automatically process text, assigning structures to input strings and strings to input semantic representations. Text processed in this way can then be searched for sentences or word forms with structures of interest or items that are not covered by the grammar (i.e. fall outside current hypotheses). ; National Science Foundation under Grant No. BCS-1160274 (PI Bender) National Science Foundation under Grant No. BCS-1561833 (PI Bender)
	Keyword: Endangered Languages; Grammar Engineering; Grammar Inference; HPSG Syntax; Interlinear Glossed Text; Typology
	URL: http://hdl.handle.net/1773/46233
	BASE
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2	Beauty and the beast: what running a broad-coverage precision grammar over the BNC taught us about the grammar - and the corpus
	Baldwin, Timothy; Beavers, John; Bender, Emily M....
	In: Linguistic evidence. - Berlin [u.a.] : Mouton de Gruyter (2008), 49-69
	BLLDB
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3	Parallel Distributed Grammar Engineering for Practical Applications
	Oepen, Stephan; Bender, Emily M.; Callmeier, Uli...
	In: <Titel nicht gefunden> (2002)
	UB Frankfurt Linguistik
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