Onto.PT: Towards the Automatic Construction of a Lexical Ontology ...

Chapter 2
Background Knowledge
The topic of Natural Language Processing (NLP), described extensively by Jurafsky
and Martin (2009), is commonly presented with the help of pop-culture futuristic visions,
where robots are capable of keeping a conversation with people, using human
language. Those visions are typically impersonated by movie or television characters,
such as HAL9000 in the Stanley Kubrick’s classic 2001: A Space Odyssey 1 , or
Bender and other robots in Matt Groening’s Futurama 2 .
NLP is a field of artificial intelligence (AI, Russell and Norvig (1995)) whose
main purpose is to enable machines to understand the language of people and thus to
communicate with us, in our own language, as if machines were a person themselves.
Given that natural language, used by humans for communication, is probably the
most natural way of encoding, transmitting and reasoning about knowledge, most
knowledge repositories are in written form (Santos, 1992). Therefore, the emergence
of the NLP field from AI is not surprising.
One of the main problems concerning natural language is that it differs from
formal languages (e.g. programming languages) because, in the latter, each symbol
has only one meaning while, in the former, a symbol may have different meanings,
depending on the context where it is used. Ambiguity occurs when it is not possible
to assign a single meaning to a form of communication, because it can be interpreted
in more than one way.
In the work described in this thesis, several NLP techniques are applied in order
to obtain language resources, structured in words, which can later be used in various
NLP tasks. This chapter provides background knowledge that introduces two important
topics for this thesis: lexical semantics, a subfield of NLP; and information
extraction, a NLP task. The representation and organisation of lexical-semantic
knowledge is also discussed, between the previous topics. In the end, we add some
remarks in order to connect the described background knowledge with the work developed
in the scope of this thesis. We decided to keep this chapter more theoretical,
while the next chapter describes practical work, including existing lexical-semantic
resources as well as works on information extraction from text.
1 See http://www.imdb.com/title/tt0062622/ (August 2012)
2 See http://www.imdb.com/title/tt0149460/ (August 2012)