A Wordnet from the Ground Up

152 Chapter 4. Extracting Relation Instances3. Remove from synAtt(y) all S such that maxScore(x, S) < minMSR4. Return the top maxSens subgraphs from synAtt(x) according to theirmaxScore values; in each, mark the synset S with the highest score(x, S)The radius r was set to 2 (Phase I), because we observed that no extractionmethod used can distinguish between direct hypernyms and just close hypernyms.The δ function is a mean of non-linear quantisation from the strength of evidence tothe decision. We require more yes votes for larger synsets, fewer votes for smallersynsets, but always more than one ‘full vote’ must be given – more than one synsetmember voting yes. The parameter h of the δ template relates the function to what isconsidered to be a ‘full vote’. For weak fit, h is set to the value which signals a veryhigh relatedness for the MSR used.In Phase II we identify continuous areas (connected subgraphs) in the hypernymygraph, those which fit the new lemma x. For each area we find the local maximumof the score function for x. We keep all subgraphs with the synset of the maximumscore based on the strong fit (the detail omitted above). From those based on theweak fit, we only keep the subgraphs above some heuristic threshold of the reliableMSR result. We also save for the linguists only a limited number of the best-scoringsubgraphs (maxSens = 5 – it can be a parameter of the application). We do presentall subgraphs with the top synset fit based on the strong fit.The WordNet Weaver applicationThe WordNet Weaver [WNW] is an expansion of plWordNetApp (Piasecki and Koczan,2007), a wordnet editor developed for the plWordNet project and used in its construction(Section 2.4). A separate screen groups most of the added user-perceived functionality– see Fig. 4.8. A linguist sees a list of new lemmas (not yet in the wordnet). A userselectednew lemma u is shown as a green oval. The existing LUs that u fits appearin yellow, orange, red and vivid purple in the increasing order of fitness score. Strongand weak fit is also distinguished by shapes, respectively octagon and rectangle. Allfitting synsets together with hypo/hypernymy (arrows point to the hypernyms) links areinitially visible to the user: this presents the context of the system’s every attachmentdecision. Only one local maximum per a connected hypernymy subgraph is markedby a blue border. Local maxima – the proposed attachment centres – are graphicallylinked with the green oval of the new lemma (marked by lines ending with smallcircles).The linguist can select any synset present on the screen and then choose a type oflexico-semantic relation, including synonymy, by which it will be associated with thenew lemma. A wrong proposal can be rejected, too; in that case, the linguist is asked toselect a type and a possible cause of the error. Adding and rejecting removes the circle-