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

48 Chapter 3. Related Work
6. {,} especially { ,}* {and | or}
... most European countries, especially France, England, and Spain.
⇒ {France hyponym of European country}, {England hyponym of European country},
{Spain hyponym of European country}
Inspired by the work of Hearst (1992), Freitas (2007) discusses the extraction of
hypernymy relations from Portuguese corpora. In her work, some Hearst patterns
were adapted to Portuguese, which resulted in the following:
• {tais} como {, ... , (e | ou) }
A tentativa posterior de clonar outros mamíferos tais como camundongos, porcos,
bezerros,....
⇒ {camundongos hyponym of mamíferos}, {porcos hyponym of mamíferos},
{bezerros hyponym of mamíferos}
• {, }* {,} (e | ou) outros
... a experiência subjetiva com o LSD-25 e outros alucinógenos.
⇒ {LSD-25 hyponym of alucinógeno}
• tipos de : { , ... ,} (e | ou)
Existem dois tipos de cromossomos gigantes: cromossomos politênicos e cromossomos
plumulados.
⇒ {cromossomos politênicos hyponym of cromossomos}, {cromossomos plumulados
hyponym of cromossomos}
• chamad(o|os|a|as) {de}
... a alta frequência da doença mental chamada esquizofrenia.
⇒ {esquizofrenia hyponym of doença mental}
Also for the extraction of hypernyms, Caraballo (1999) proposed a combination
of pattern detection and a clustering method where noun candidates are obtained
from a corpus using data on conjunctions and appositives. A co-occurrence matrix
for all nouns is used. It contains a vector for each noun in the corpus, with the
number of times it co-occurs, in a conjunction or appositive, with each other noun.
If v and w are the vectors of two nouns, similarity between them is calculated as
below, which can be see as a variant of LSA (cosine similarity):
cos(v, w) =
v. w
|v|.| w|
(3.3)
In a post-processing step, Hearst-like patterns are used for finding hypernym
candidates, which, if appropriate, are placed as common parent nodes for clusters.
Cederberg and Widdows (2003) used a similar variant of LSA to improve the
precision and recall of hyponymy relations, extracted from a corpus using Hearstlike
patterns. Having in mind that a hyponym and its hypernym are expected to be
similar, LSA is used to compute the similarity of terms in the extracted relations.
While the precision of a random sample of extracted relations was 40%, the precision
of the 100 relations with higher similarity was 58%, which suggests the effectiveness
of this method for reducing errors.
Furthermore, as most of the potential hyponymy relations that could be extracted
are not expressed by the six Hearst patterns, Cederberg and Widdows (2003)
improved the recall of their method using coordination as a cue for similarity. They