Semi-Automatic Recognition of Noun Modifier Relationships

Semi-Automatic Recognition of Noun Modifier Relationships Ken BARKER and Stan SZPAKOWICZ School of Information Technology and Engineering University of Ottawa Ottawa, Canada K1N 6N5 {kbarker, szpak}@site.uottawa.ca Abstract Semantic relationships among words and phrases are often marked by explicit syntactic or lexical clues that help recognize such rela~ tionships in texts. Within complex nominals, however, few overt clues are available. Sys- tems that analyze such nominals must com- pensate for the lack of surface clues with other information. One way is to load the system with lexical semantics for nouns or adjectives. This merely shifts the problem elsewhere: how do we define the lexical se- mantics and build large semantic lexicons? Another way is to find constructions similar to a given complex nominal, for which the relationships are already known. This is the way we chose, but it too has drawbacks. Similarity is not easily assessed, similar ana- lyzed constructions may not exist, and if they do exist, their analysis may not be appropriate for the current nominal. We present a semi-automatic system that identifies semantic relationships in noun phrases without using precoded noun or ad- jective semantics. Instead, partial matching on previously analyzed noun phrases leads to a tentative interpretation of a new input. Proc- essing can start without prior analyses, but the early stage requires user interaction. As more noun phrases are analyzed, the system learns to find better interpretations and reduces its reliance on the user. In experiments on Eng- lish technical texts the system correctly iden- tiffed 60-70% of relationships automatically. 1 Introduction Any system that extracts knowledge from text cannot ignore complex noun phrases. In technical domains especially, noun phrases carry much of the information. Part of that information is con- tained in words; cataloguing the semantics of sin- gle words for computational purposes is a difficult task that has received much attention. But part of the information in noun phrases is contained in the relationships between components. We have built a system for noun modifier re- lationship (NMR) analysis that assigns semantic relationships in complex noun phrases. Syntactic analysis finds noun phrases in a sentence and pro- vides a flat list of premodifiers and postmodifying prepositional phrases and appositives. The NMR analyzer first brackets the flat list of premodifiers into modifier-head pairs. Next, it assigns NMRs to each pair. NMRs are also assigned to the relation- ships between the noun phrase and each post- modifying phrase. 2 Background 2.1 Noun Compounds A head noun along with a noun premodifier is often called a noun compound. Syntactically a noun compound acts as a noun: a modifier or a head may again be a compound. The NMR ana- lyzer deals with the semantics of a particular kind of compound, namely those that are transparent and endocentric. The meaning of a transparent compound can be derived from the meaning of its elements. For example, laser printer is transparent (a printer that uses a laser). Guinea pig is opaque: there is no obvious direct relationship to guinea or to …

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