Alternative Phrases and Natural Language Information Retrieval

Alternative Phrases and Natural Language Information Retrieval Gann Bierner Division of Informatics University of Edinburgh gbierner@cogsci.ed.ac.uk Abstract This paper presents a formal analysis for a large class of words called alternative markers, which includes other(than), such(as), and besides. These words appear frequently enough in dialog to warrant serious attention, yet present natural language search engines perform poorly on queries containing them. show that the performance of a searchI engine can be improved dramatically by incorporating an approximation of the formal analysis that is compatible with the search engine’s operational seman- tics. The value of this approach is that as the operational semantics of natural lan- guage applications improve, even larger improvements are possible. 1 Introduction Consider the following examples discovered in a corpus of queries submitted to the Electric Knowl- edge search engine12, the successor of the On Point natural language search system described in Cooper (1997). Each consists of a query, a re- sponse (not shown), and then a follow-up query. (1) What is the drinking age in Afghanistan? What is the drinking age in other countries? (2) Where can I find web browsers for download? Where can I find other web browsers than Netscape for download? (3) Where can I find a list of all the shoe manu- facturers in the world? Where can I find shoes made by Buffalino, such as the Bushwackers? (4) Where are online auctions indexed? Are there other auction search engines be- sides BidFind? 1formerly known as The Electric Monk 2http://www.electricknowledge.com In each case, particular words are used to con- strain the space of appropriate answers: e.g. such (as), other (than), and besides. I call these words, and others like them, alternative mark- ers, and alternative markers along with their syn- tactic argument (e.g. other countries), I call al- ternative phrases. Alternative phrases that are closely bound to the noun phrase to which they refer, like those above, I call connected alterna- tive phrases (modeled after similar terminology in Hoeksema (1995)). There are also free alternative phrases, such as Other than Fido, every dog likes going for walks, which are not discussed here but are discussed in depth in Bierner (2001). I have found queries containing all these forms despite the fact that no current NLIR system can han- dle them, either ignoring the alternative phrase or, worse, treating the queries as if the alternative marker were absent. The fact that these phrases define the space of correct answers makes it absolutely necessary to correctly interpret them in an IR application. The user requires countries that are not Afghanistan, web browsers that are not Netscape, shoes with similar properties to Bushwackers, and auction search engines that are not BidFind. Answers that do not conform are wrong. Another feature of alternative markers are their presuppositions. Through these presuppositions, alternative markers can provide a rich source of knowledge about the world, as Hearst (1992) has already recognized. For example, these queries im- ply that Afghanistan is a country, Netscape is a web browser, Bushwackers are …

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