Features and Values

Features and Values Lauri Karttunen University of Texas at Austin Artificial Intelligence Center SRI International and Center for the Study of Language and Information Stanford University Abstract The paper discusses the linguistic aspects of a new gen- eral purpose facility for computing with features. The pro- gram was developed in connection with the course I taught at the University of Texas in the fall of 1983. It is a general- ized and expanded version of a system that Stuart Shieber originally designed for the PATR-II project at SRI in the spring of 1983 with later modifications by Fernando Pereira and me. Like its predecessors, the new Texas version of the "DG {directed graph}" package is primarily intended for representing morphological and syntactic information but it may turn out to be very useful for semantic representa- tions too. 1. Introduction Most schools of linguistics use some type of feature no- tation in their phonological, morphological, syntactic, and semantic descriptions. Although the objects that appear in rules and conditions may have atomic names, such as "k," "NP," "Subject," and the like, such high-level terms typically stand for collections of features. Features, in this sense of the word, are usually thought of as attribute-value pairs: [person: lst], [number: sg], although singleton fea- tures are also admitted in some theories. The values of phonological and morphological features are traditionally atomic; e.g. 1st, 2nd, 3rd; they are often binary: +, -. Most current theories also allow features that have com- plex values. A complex value is a collection of features, for example: Isgreement: r per$°n: 3rdll Lnumber: sgJJ Lexical Functional Grammar (LFG) [Kaplan and Bres- nan, 83], Unification Grammar (UG) [Kay, 79], General- ized Phrase Structure Grammar (GPSG) [Gazdar and Pul- lum, 82l, among others, use complex features. Another way to represent feature matrices is to think of them as directed graphs where values correspond to nodes and attributes to vectors: "lag reement numb~/~eri°n sg 3rd In graphs of this sort, values are reached by traversing paths of attribute names. We use angle brackets to mark expressions that designate paths. With that convention, the above graph can also be represented as a set of equa- tions: <agreement number> = sg <agreement person> = 3rd Such equations also provide a convenient way to ex- press conditions on features. This idea lies at the heart of UG, LFG, and the PATR-II grammar for English [Shieber, et al., 83] constructed at SRI. For example, the equation <subject agreement> = <predicate agreement> states that subject and predicate have the same value for agreement. In graph terms, this corresponds to a lattice where two vectors point to the same node: subject ~ I predicate agreement ~~agreement numb~erson sg 3rd 28 In a ca~'~e like this, the values of the two paths have been "unified." To represent unification in terms of feature ma- trices we need to introduce some new convention to distin- guish between identity and mere likeness. Even that would not quite suffice because the graph formalism also allows …

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