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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