# Methods of Annotating and Identifying Metaphors in the Field of Natural Language Processing
## 4 Identifying Metaphors
### Hand Coded Knowledge and Use of Lexical Resources  
In their paper, \"The structure of a semantic theory\" [52], [PERSON] and [PERSON] when discussing the form of semantic theory and emphasizing the importance of semantics in the very understanding of language, introduce the theory of _slectional restrictions_. A selectional restriction is a restriction in the relations between words in a sentence, particularly the predicate and its associated arguments. In his papers from 1975 [53] and 1978 [54], [PERSON], one of the pioneers of natural language processing, notes that rather than being restrictions, these are preferences, and introduces the theory of _slectional preferences_. It is the theories of [PERSON] and [PERSON] and [PERSON] that form the basis of the [PERSON]'s [55] system for machine metaphor recognition, met* (read as _met star_), and inspired most other early approaches to machine metaphor identification. In his paper, [PERSON] provides an overview of previous research dealing with metaphor identification and proposes that they can be divided into four different approaches--(1) metaphor as comparison, (2) metaphor as an interaction, (3) violation of selectional restrictions/preferences and, finally, (4) the conventional metaphor. He bases his met* system on selectional restrictions/preferences, and finds, like [PERSON], that the metaphor violates selectional restrictions/preferences and can, therefore, be recognized. However, [PERSON] does not ignore other approaches to identifying a metaphor, and his met* system also takes into account the importance of other approaches, which are implemented in the system. The met* system recognizes metonymy in addition to metaphors. [PERSON] himself continued to work on the theory of selectional preferences to develop a method of identifying metaphors based on that theory. In [PERSON] et al. [56], the authors present an algorithm for metaphor recognition using WordNet as a lexical resource. The hypothesis of the paper is that we have a metaphor on our hands if the first meaning that a word has in WordNet is not the one that would correspond to the selectional preferences that are needed in the place in the sentence where the word is found, but has some less common meaning. The CorMet system [57], proposed by [PERSON], also finds its foundations in selectional preferences and recognizes cross-domain mapping. CorMet analyzes a large number of documents, organized by domain, and learns the selectional preferences of verbs that are characteristic for a certain domain. By discovering the selectional preferences of verbs in one domain, the CorMet system can also recognize differences in selectional preferences between domains--for example, the CorMet system recognizes the difference in the selectional preferences of verbs used in the finance domain from those used in the laboratory domain (an example given by the author is \"Funds poured into his bank account.\"), and can conclude that this is a cross-domain mapping. The system learns selectional preferences in two steps--the first step is [PERSON]'s [58] algorithm for learning selectional preferences in order for CorMet to learn the selectional preferences of verbs in a certain domain, and in the second step WordNet nodes are clustered using the nearest neighbor method in order to compare selectional preferences and determine similarities. [PERSON] and [PERSON] [59] limit their work to metaphors containing nouns and divide metaphors into three types, depending on the connections in the sentence. Type I is the relationship between subject and object, type II is the relationship between verb and noun, and type III is the relationship between adjective and noun. To identify a type I metaphor, the authors use WordNet to identify whether there is a hyponym relationship between the subject and the object, that is the words used to express the subject and the object, and if such a connection does not exist, the sentence is considered a metaphor.