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

114 Chapter 7. Moving from term-based to synset-based relations
the tb-triples, DLP is proprietary, which means we cannot use the context of the
tb-triples of PAPEL. Not to refer that there are several small definitions that do not
provide enough context. Given this limitation, together with the need to map often
un-matching (Dolan, 1994; Peters et al., 1998) word sense definitions in different
resources, and to define extraction contexts for different heterogeneous resources,
we decided to ontologise without using the extraction context. This enables the creation
of IE systems with two completely independent modules: (i) one responsible
for extracting tb-triples; and (ii) another for ontologising them. In other words, the
second module attaches each term in a triple to a concept, represented, for instance,
as a synset in a broad-coverage lexical ontology. We believe that this approach is an
interesting way of coping with information sparsity, since it allows for the extraction
of knowledge from different heterogeneous sources (e.g. dictionaries, encyclopedias,
corpora), and provides a way to harmoniously integrate all the extracted information
in a common knowledge base.
In this chapter, we propose several algorithms for moving from tb-triples to
synset-based relational triples (hereafter, sb-triples), taking advantage of nothing
but the existing synsets and a lexical network with tb-triples. We start by presenting
the algorithms and then we describe how they were evaluated and compared. The
performance results supported the choice of this kind of algorithm in the creation
of Onto.PT. Also, given that the ontologising algorithms result in a set of synsets
related among themselves by semantic relations, they are suitable for the last step
of the ECO approach for creating wordnets. The core of this part of the work was
originally reported in Gonçalo Oliveira and Gomes (2012a). Its earlier stages had
been reported in Gonçalo Oliveira and Gomes (2011c).
7.1 Ontologising algorithms
Our work on ontologising semantic relations is similar to that presented by Pennacchiotti
and Pantel (2006). The main difference is that the previous authors
ontologise the semantic relations into WordNet, and exploit its structure, including
synsets and existing synset-relations. We, on the other hand, had in mind to ontologise
in a synset-base without synset-relations (TeP), so we had to find alternatives,
such as exploring all the extracted information.
The goal of the proposed algorithms is to ontologise tb-triples, {a R b}, in the
synsets of a thesaurus T . Instead of considering the context where the triples were
extracted from, or the synset glosses, they exploit the information in a given lexical
network N to select the best candidate synsets. A lexical network is established
by a set of tb-triples, and is defined as a graph, N = (V, E), with |V | nodes and
|E| edges. Each node vi ∈ V represents a term, and each edge connecting vi and
vj, E(vi, vj), indicates that one of the meanings of the term in vi is related to one
meaning of the term in vj. Furthermore, edges may be labelled according to the
type of relationship held, E(vi, vj, R).
By default, when a lexical network is needed, it is created from the tb-triples
given as input. So, the proposed algorithms are better suited to ontologise large
amounts of knowledge at once. Still, when there are few input tb-triples, they can
exploit an external and larger lexical network or, eventually, the ontology where the
triples are being attached to, if the former contains already ontologised triples.