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4 - Semantics What does this mean? Even with the most sophisticated grammar, we will always find sentences that will not be representable, either because they are too complex or simply because they are wrong. We should provide some methods to catch those cases. For this task, we need to take another dimension of texts into account, the semantics. Of course, the texts generated are not stand-alone, but rather want to express something, a meaning. This meaning in connection with the text is called semantics. So we need a powerful formalism to help us extracting a meaning. This can be achieved by augmenting the grammar, passing arguments to nonterminal symbols: you can use the additional information in the parameters to associate meanings with strings and to achieve contextsensitivity. The context-sensitive grammars are grammars that take the word's context into account (not the sentence's context - this would lead to discourse understanding problems which we will discuss later). This context-sensitivity is needed when you have to make NPs and VPs agree in case and number, for example in "I am taking it for me" instead of "I are taking it for I", which would be agrammatical in natural English. Now we want to have symbols that are more expressive. Take NP(semantics), for example. This should express its meaning (its semantics) already in this early stage of processing. NP(semantics) could, grammatically, be expanded to NP(semantics, string), a string representing certain semantics. Then, you also have to see that some verbs differ in their syntactic structure from others. Some accept objects, some don't, so you have to represent this distinction in your system, too. This is called verb subcategorization. verb subcategorization list example graze [] The horse grazes. sign [PP] I sign at you. translate [NP], [NP PREP NP] I translate English to Chinese. Many sentences can be very ambiguous, but usually one can extract the intended meaning by looking at the context of the phrase in question. All this plays a crucial role in the area of discourse understanding. Almost any text can be interpreted in different ways, and these can only be differentiated by knowing what the context is. This means that not only mere disambiguation on word and phrase level is important for text understanding, but incorporation that embraces world knowledge is significant, too. Natural Language Processing | Project of Multimedia Systems | EECS 579 | update: 22/12/2000 Daniele Quercia