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

4.3. Discussion 77
Figure 4.5: Lexical network where ambiguity arises.
Given that they share the same structure, the utility of a resource as CARTÃO is supported by the number of works using PAPEL. So far, PAPEL has been used
as a gold standard for computing similarity between lexical items (Sarmento, 2010),
in the adaptation of textual contents for poor literacy readers (Amancio et al.,
2010), in the automatic generation of distractors for cloze questions (Correia et al.,
2010), as a knowledge base for QA (Saias, 2010; Rodrigues et al., 2011) and question
generation (Marques, 2011) systems, to validate terms describing places (Oliveira
Santos et al., 2012), and in the enrichment (Silva et al., 2012b) and creation (Paulo-
Santos et al., 2012) of sentiment lexicons. CARTÃO has already been used in the
automatic generation of poetry (Gonçalo Oliveira, 2012).
On the other hand, lexical resources based on words, identified by their orthographical
form, are not practical for several computational applications. This
happens because words have different senses that go from tightly related, as in
polysemy (e.g. bank, institution and building) or metonymy (e.g. bank, the building
or its employers), to completely different, as in homonymy (e.g. bank, institution
or slope). Moreover, there are words with completely different orthographical forms
denoting the same concept (e.g. car and automobile).
Ambiguities may lead to serious inconsistencies in tasks where handling word
senses is critical, as in inference. In figure 4.5, we present an example of a termbased
lexical network with several ambiguous Portuguese words, namely:
• pasta, which might refer to a briefcase, paste, pasta or money (figuratively);
• massa, which might refer to pasta, to people or money (both figuratively);
• pastel might be a cake or money (figuratively);
• cacau might refer to cocoa (a fruit) or to money (also figuratively).
It is not hard to imagine that, if these ambiguities are not handled, erroneous
inferences can be made, such as:
• massa synonym-of povo ∧ massa hypernym-of tortellini
→ povo hypernym-of tortellini (people hypernym-of tortellini)
• dinheiro synonym-of cacau ∧ fruto hypernym-of cacau
→ fruto hypernym-of dinheiro (fruit hypernym-of money)
A real example of these problems is presented in Gonçalo Oliveira et al. (2010b),