A Wordnet from the Ground Up

4.5. Hybrid Combinations 135The next group of attributes is meant to tell the classifier directly about the possibilityof hypernymy or co-hyponymy between a and b. The co-ordination attribute (2) isbased on the lexico morpho-syntactic constraint NcC used for the MSR RW F extraction(Section 3.4.3, page 67). NcC looks for occurrences of syntactic co-ordination of aand b as constituents of the same composite noun phrase. It recognises only a limitedset of conjunctions: ani (neither, nor), albo (or), czy (whether), i (and), lub (or),oraz (and). All these were manually identified as marking semantic coordination ofthe linked nominal LUs, possibly indirect co-hyponyms (“coordinated terms” in (Snowet al., 2005)).During matrix construction, occurrences of NcC are recorded for a LU x with allnominal lexical elements, very often more than 100000. Here, we pay attention onlyto nominal LUs in the classified pairs – potentially all LUs described by the givenMSR. The value of (2) is the frequency with which the constraint is met for a and bco-occurring in the same sentence. 11 We assumed that co-ordination is more frequentfor potential co-hyponyms and hypernyms.A manual investigation of instance pairs of hypernyms in the IPI PAN Corpus ofPolish 12 [IPIC] (Przepiórkowski, 2004) showed that, surprisingly, they often occur asthe noun phrase head and its noun modifier in the genitive case. Even more frequent ismeronymy expressed by the genitive modification. The classifier receives informationon the frequency of this syntactic relation in both directions, when a is modified (3)and is the modifier (4). Both attributes are based on the same lexico-morphosyntacticconstraint NmgC used for MSR extraction, presented in Figure 3.6 and discussed inSection 3.4.3. NmgC is based more on the relative positions of both nominal LUs thanon agreement. Just as attribute (2), NmgC was used only to detect associations betweenLUs described by the MSR.The idea of the precision of repeating b’s features by a’s features, used in attributes5 and 7, is modelled after the MSR in (Weeds and Weir, 2005). We want to analyse theadditive precision with which, using a’s features, we refer to (“retrieve”) b’s features.The precision is defined as follows:∑P add i∈F (a)∩F (b)M[a, i](a, b) = ∑j∈F (a) M[a, j] (4.10)• F (x) is the set of features occurring frequently enough with x, according to atest of statistical significance, e.g., a t-score test,• M is a co-incidence matrix that represents the given set of features; for attribute11 The corpus is processed with the granularity of sentences – identified by a simple sentencer.12 Especially in the part called HC (Section 4.1) – sentences that contain pairs of known hypernyms.HC has been extracted to facilitate manual construction of lexico-syntactic patterns.