2004 SupportVectorMAppToTheClasOfSemRels

• (Girju et al., 2004) ⇒ Roxana Girju, A.M. Giuglea, M. Olteanu, O. Fortu, Dan Moldovan. (2004). “Support Vector Machines Applied to the Classification of Semantic Relations in Nominalized Noun Phrases.” In: Proceedings of HLT/NAACL 2004 Workshop on Computational Lexical Semantics.

Subject Headings: Semantic Relation Mention, Nominalized Noun Phrase.

Quotes

Abstract

• The discovery of semantic relations in text plays an important role in many NLP applications. This paper presents a method for the automatic classification of semantic relations in nominalized noun phrases. Nominalizations represent a subclass of NP constructions in which either the head or the modifier noun is derived from a verb while the other noun is an argument of this verb. Especially designed features are extracted automatically and used in a Support Vector Machine learning model. The paper presents preliminary results for the semantic classification of the most representative NP patterns using four distinct learning models.

1. Introduction

• …

2. Semantic Relations in Nominalized Noun Phrases

• In this paper we study the behavior of semantic relations at the noun phrase level when one of the nouns is nominalized. The following NP level constructions are considered: complex nominals, genitives, adjective phrases, and adjective clauses.
• …

Complex Nominals

• Levi (Levi 1979) defines complex nominals (CNs) as expressions that have a head noun preceded by one or more modifying nouns, or by adjectives derived from nouns (usually called denominal adjectives). Each sequence of nouns, or possibly adjectives and nouns, has a particular meaning as a whole carrying an implicit semantic relation; for example, “parental refusal” (AGENT). The main tasks are the recognition, and the interpretation of complex nominals. The recognition task deals with the identification of CN constructions in text, while the interpretation of CNs focuses on the detection and classification of a comprehensive set of semantic relations between the noun constituents.

Genitives

• In English there are two kinds of genitives; in one, the modifier is morphologically linked to the possessive clitic ’s and precedes the head noun (s-genitive e.g. “John’s conclusion”), and in the second one the modifier is syntactically marked by the preposition of and follows the head noun (of-genitive, e.g. “declaration of independence”). Adjective Phrases are prepositional phrases attached to nouns and act as adjectives (cf. (Semmelmeyer and Bolander 1992)). Prepositions play an important role both syntactically and semantically ((Dorr 1997). Prepositional constructions can encode various semantic relations, their interpretations being provided most of the time by the underlying context. For instance, the preposition “with” can encode different semantic relations: (1) It was the girl with blue eyes (MERONYMY), (2) The baby with the red ribbon is cute (POSSESSION), (3) The woman with triplets received a lot of attention (KINSHIP). The conclusion for us is that in addition to the nouns semantic classes, the preposition and the context play important roles here.
• Adjective Clauses are subordinate clauses attached to nouns (cf. (Semmelmeyer and Bolander 1992)). Often they are introduced by a relative pronoun/adverb (ie that, which, who, whom, whose, where) as in the following examples: (1) Here is the book which I am reading (book is the THEME of reading) (2) The man who was driving the car was a spy (man is the AGENT of driving). Adjective clauses are inherently verb-argument structures, thus their interpretation consists of detecting the semantic role between the head noun and the main verb in the relative clause. This is addressed below.

3.1 Nominalizations

• A further analysis of various examples of noun - noun pairs encoded by the first three major types of NP-level constructions shows the need for a different taxonomy based on the syntactic and grammatical roles the constituents have in relation to each other. The criterion in this classification splits the noun - noun examples (respectively, adjective - noun examples in complex nominals) into nominalizations and non-nominalizations.
• Nominalizations represent a particular subclass of NP constructions that in general have “a systematic correspondence with a clause structure” (Quirk et al. 1985). The head or modifier noun is derived from a verb while the other noun (the modifier, or respectively, the head) is interpreted as an argument of this verb. For example, the noun phrase “car owner” corresponds to “he owns a car”. The head noun owner is morphologically related to the verb own. Otherwise said, the interpretation of this class of NPs is reduced to the automatic detection and interpretation of semantic roles mapped on the corresponding verb-argument structure.
• As in (Hull and Gomez 1996), in this paper we use the term nominalization to refer only to those senses of the nominalized nouns which are derived from verbs. For example, the noun “decoration” has three senses in WordNet 2.0: an ornament (#1), a medal (#2), and the act of decorating (#3). Only the last sense is a nominalization. However, there are more complex situations when the underlying verb has more than one sense that refers to an action/event. This is the case of “examination” which has five senses of which four are action-related. In this case, the selection of the correct sense is provided by the context.
• We are interested in answering the following questions: (1) What is the best set of features that can capture the meaning of noun - noun nominalization pairs for each NP-level construction? and (2) What is the semantic behavior of nominalization constructions across NP levels?

Deverbal vs verbal noun.

• (Quirk et al.1985) generally classify nominalizations based on the morphological formation of the nominalized noun. They distinguish between deverbal nouns, i.e. those derived from the underlying verb through word formation; e.g., “student examination”, and verbal nouns, i.e. those derived from the verb by adding the gerund suffix “-ing”; e.g.: “cleaning woman”. Most of the time, verbal nouns are derived from verbs which don’t have a deverbal correspondent.

References

• C. Baker, C. Fillmore, and J. Lowe. (1998). The Berkeley FrameNet Project. In: Proceedings of COLLING/ACL.
• D. Blaheta and Eugene Charniak. (2000). Assigning function tags to parsed text. In: Proceedings of the NAACL.
• Eugene Charniak. (2001). Immediate-head parsing for language models. In: Proceedings of ACL, Toulouse, France.
• N. Chomsky. 1970. Remarks on Nominalization. In Readings in English Transformational Grammar. Jacobs,
• R. A., and Rosenbaum, P.S. (eds), Ginn and Company.
• B. Dorr. (1997). Large-scale dictionary construction for foreign language tutoring and interlingual machine translation. In Machine Translation, 12(4).
• Daniel Gildea, and Daniel Jurafsky. (2002). Automatic Labeling of Semantic Roles. In Computational Linguistics, 28(3).
• Daniel Gildea, and M. Palmer. (2002). The Necessity of Parsing for Predicate Argument Recognition. In ACL.
• R. Grishman, C. Macleod, and A. Meyers. (1994). Comlex syntax: Building a computational lexicon. In: Proceedings of COLING, Kyoto, Japan.
• R. Hull and F. Gomez. (1996). Semantic interpretation of nominalizations. In: Proceedings of AAAIconference, Oregon.
• K. Kipper, H. T. Dang, and M. Palmer. (2000). Class-based construction of a verb lexicon. In AAAI, Austin, Texas.
• P. Kingsbury, M. Palmer, and M. Marcus. (2002). Adding Semantic Annotation to the Penn TreeBank. In: Proceedings of HLT, California.
• P. Kingsbury and M. Palmer. (2002). From Treebank to Propbank. In Third International Conference on Language Resources and Evaluation, LREC-02, Las Palmas, Canary Islands.
• Judith Levi. 1979. The Syntax and Semantics of Complex Nominals. New York: Academic Press.
• C. Macleod, R. Grishman, A. Meyers, L. Barrett, and R. Reeves. (1998). Nomlex: A lexicon of nominalizations. In: Proceedings of the 8th International Congress of the European Association for Lexicography, Belgium.
• Dan Moldovan, A. Badulescu, M. Tatu, D. Antohe, and R. Girju. (2004). Semantic Classification of Non-nominalized Noun Phrases. In: Proceedings of HLT/NAACL 2004 - Computational Lexical Semantics workshop, Boston, MA.
• S. Pradhan, K. Hacioglu, V. Krugler, W. Ward, J. Martin, and Daniel Jurafsky. (2003). Semantic role parsing: Adding semantic structure to unstructured text. In ICDM, Florida.
• (Quirk et al., 1985) ⇒ Randolph Quirk, S. Greenbaum, Geoffry Leech, and Jan Svartvik. (1985). “A Comprehensive Grammar of English Language.” Longman, Harlow.
• S. Siegel and N.J. Castellan. 1988. Non Parametric Statistics for the behavioral science. New York: McGraw-Hill.
• M. Semmelmeyer and D. Bolander. (1992). The New Webster’s Grammar Guide. Lexicon Publications, Inc.
• S. Tong and Daphne Koller. (2001). Support Vector Machine Active Learning with Applications to Text Classification. In Journal of Machine Learning Research.
• V. Vapnik. 1982. Estimation of Dependences Based on Empirical Data. In Springer Verlag.

---

,

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2004 SupportVectorMAppToTheClasOfSemRels	Roxana Girju A.M. Giuglea M. Olteanu O. Fortu Dan I. Moldovan			Support Vector Machines Applied to the Classification of Semantic Relations in Nominalized Noun Phrases		Proceedings of HLT/NAACL 2004 Workshop on Computational Lexical Semantics	http://www.aclweb.org/anthology-new/W/W04/W04-2610.pdf			2004