{"type":"ScholarlyArticle","title":"Description-directed Natural Language Generation","authors":[{"name":"David D. McDonald","slug":"david-d-mcdonald-2","given":"David D.","family":"McDonald","affiliation":""},{"name":"James Pustejovsky","slug":"james-pustejovsky","given":"James","family":"Pustejovsky","affiliation":""}],"abstract":"We report here on a äpificant new set of capabilities tbat we have incorporated into our J.anauage generation system MUMBLE. Their impact will be to greatly limplify tbe work of any text planner tbat uaes MUMBLE as ih linguistic:s component linc:e MUMBLE can now take on many of tbe planner's text orpnization and decision-making problems witb markedly lesa han~tailoring of algoritbms in eitber component. Briefly tbese new capabilies are tbe followinJ: (a) A1TACBMENT. A new proceaina stap witbin MUMBLE tbat allows us to readily Implement tbe c:onventiOill tbat ao into definina a text's intended proee style, e.g. whetber tbe text lbould have complex sentences or simple ones, compounds or embeddinp, reduc:ed or fuU relative clauaes, etc. Stylistic c:onventi001 are given as independently stated rules tbat can be changed accordina to tbe lituation. (b) REALIZATION CLASSES are a mechanism for organizing both tbe transfonnational and lexical choices for linguistically rea1izing a c:onceptual objec:t. The mechanism highligbts tbe intentional criteria which c:ontrol telection ctedsi001. 'ibese criteria effectively constitute an \"interlingua\" between planner and linguistic component, desc:ribing tbe rhetorical uses to wbich a text choic:e can be put wbile allowinJ its lingustk: detaill to be encapsulated. The fint part of our paper (secti001 2 and 3) descn'bes our generat approacb to generation; the rest Wustrates the new capabilldes througb examples from tbe UMUI COUNSELOR Projec:t. Thil projec:t il a larp new effort to develop a natural J.anauage diJCOUne system bued on the HYPO system [R.issland cl Albley 1984], wbich act1 as a legal advisor suggestina relevant dimenäons and c:ase referenc:es for arJUin1 hypothetical legal cues in tradHec:ret law. At various relevant pointl we briefly c:ontrast our work witb tbat of Appelt, Danloil, Gabriel, Jacobl, Mann and Mattbeillen, and McKeown and Derr.","doi":null,"url":"https://ijcai.org/proceedings/1985/158","pdf":"https://ijcai.org/proceedings/1985/0158.pdf","markdown":"https://ijcai.org/proceedings/1985/158.md","bibtex":"https://ijcai.org/proceedings/1985/bibtex/158","volume":{"slug":"1985","title":"Proceedings of the Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1985","url":"https://ijcai.org/proceedings/1985/","year":1985,"location":"Los Angeles, California, USA","dates":"","editors":"Aravind Joshi","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Natural Language","track":"Natural Language","number":158,"pages":{"first":799,"last":804},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}