A Wordnet from the Ground Up

3.5. Sense Discovery by Clustering 95• the ratio of committee importance:w(f i ) = w(f i ) − w(f i ) v c(f i )∑vc (•)In the minimal value heuristic, we make quite a strong assumption that a featureis associated only with one sense on one of the sides: LU or committee. The lowervalue identifies the right side. The ratio heuristic is based on a weaker assumption:the feature corresponds to the committee description only to some extent.3.5.4 Benefits of discovered senses for constructing a wordnetDuring the reimplementation of CBC for Polish we stumbled upon two problems. Thereare significant typological differences between Polish and English, and the availabilityof language tools differs. For example, Polish – unlike English – is generally a freeword-order language; much syntactic information is encoded by rich inflection. Thismakes the construction of even a shallow parser for Polish more difficult than forEnglish – and CBC begins by running a dependency parser on the corpus. As shownin Section 3.4 and in (Piasecki et al., 2007a, Broda et al., 2008), this similar problemcan be solved by applying several types of lexico-morphosyntactic constraints. Thisidentifies a subset of structural dependencies mainly from morphosyntactic agreementamong words in a sentence and a few positional features like noun-noun head/modifierpairs. The constructed MSR gave results comparable with the results achieved byhumans in the same task (Piasecki et al., 2007b). We therefore assumed that theconstructed MSR is at least comparable in quality to that used in (Pantel, 2003, Linand Pantel, 2002). We adopted the constraint-based approach here, applying a subset oflexico-morphosyntactic constraints as in Section 3.4.3: noun modification by a specificadjective or a specific adjectival participle (AdjC), and noun co-ordination with aspecific noun (NcC).Evaluation of the extracted word senses proposed in (Lin and Pantel, 2002, Pantel,2003) is based on comparing the extracted senses with those defined for the samewords in PWN. It is assumed that a correct sense of word w is described by a wordgroup c containing w if a PWN synset s containing w is sufficiently similar to c. Thelatter condition is represented by another threshold θ.Similarity between wordnet synsets is central to the evaluation proposed in (Linand Pantel, 2002, Pantel, 2003). Similarity was defined through probabilities assignedto synsets and derived from a corpus annotated with synsets. This kind of synsetsimilarity is very difficult to estimate for languages for which there is no such corpus,as is the case of Polish. In order to avoid any kind of unsupervised estimation of synset