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

58 Chapter 4. Acquisition of Semantic Relations
added to synsets are the target of a clustering algorithm, similar to the one
presented in chapter 5.
• Chapter 7 proposes several algorithms for moving from term-based semantic
relations to relations held between synsets, using only the extracted termbased
relations and the discovered synsets.
• After presenting all the steps, chapter 8 shows how they can be combined in the
ECO approach, in order to reach our final goal, Onto.PT, a lexical ontology
for Portuguese. In the same chapter, an overview of the current version of
Onto.PT is provided.
It is possible to integrate any kind of information, from any source, in Onto.PT,
as long as it is represented as term-based triples. Still, regarding the goal of
creating a broad-coverage lexical ontology, and despite some experiments using
Wikipedia (Gonçalo Oliveira et al., 2010a), electronic dictionaries were our main
target for exploitation, as in the MindNet project (Richardson et al., 1998; Vanderwende
et al., 2005). As referred in section 2, language dictionaries are the main
source of general lexical information of a language. They are structured on words
and senses and are more exhaustive on this field than other textual resources. At
the same time, they are systematic and thus easier to parse.
This chapter describes the extraction of semantic relations from three Portuguese
dictionaries, which resulted in the LKB named CARTÃO, a large lexical-semantic
network for Portuguese. Part of the work presented here is also reported in Gonçalo
Oliveira et al. (2011).
We start this chapter by introducing our approach to the acquisition of termbased
relational triples from dictionary definitions. Then, we describe the work
performed on the creation of CARTÃO, starting with a brief introduction about
the dictionaries used, some issues about their parsing and about the structure of
their definitions. After that, we present the contents of CARTÃO, we compare
the knowledge extracted from each of the three dictionaries, and evaluate it using
different procedures. We end this chapter with a brief discussion on the utility of a
LKB structured as CARTÃO. 4.1 Semantic relations from definitions
In our work, the extraction of semantic relations from dictionaries is based on a
fixed set of handcrafted rules, as opposing to state-of-the art bootstrapping algorithms
that learn relations given a small set of seeds (see more in section 3.2.2).
Although our approach is more time-consuming, especially in the construction of
the grammars, which have to be manually adapted to new situations, this is not
critical for dictionaries. As we will discuss in section 4.2.3, many regularities are
preserved along definitions in the same dictionary, and even in different dictionaries.
The vocabulary thus tends to be simple and easy to parse. Also, most bootstrapping
algorithms rely heavily on redundancy in large collections of text, while dictionaries
are smaller and much less redundant. Furthermore, our approach provides higher
control over the discriminating patterns.
The extraction of semantic relations is inspired by the construction of PAPEL,
reported in Gonçalo Oliveira et al. (2009, 2010b), and consists of one manual step,