A Wordnet from the Ground Up

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2.4. The First 7000 Lexical Units 37morphosyntactic tagger used in IPIC 1.0 misinterpreted the following two situations:• the word form maj, which represents two lemmas: May case=nom , but also theimperative form of maić,• the word form mają: to have num=sg,per=3rd – “non-past form” (Przepiórkowski,2006), but also the non-past, singular, third-person form of maić.The tagger only recognised the latter, causing a completely wrong high frequency of theverb maić. Such lemmas were not included in the final list. Proper names, pronouns,numerals and foreign words were excluded from the list, too. Another problem wasa bias introduced by the lack of balance in IPIC 1.0. Many lemmas appeared to beunexpectedly frequent while others did not occur at the analysed top positions. Forexample, there were almost no animal names, but lis ‘fox’ was excessively frequent: itis the surname of a well-known journalist.Lemmas were acquired as separate tokens, so we had to attach the reflexive markersię to some verbs. A few examples: dziać had to be “reconstructed” as dziać się‘to happen’; oglądać ‘watch’ and oglądać się ‘look back’ were both necessary. Wehad to reconstruct some multiword lemmas (representing fixed multiword expressions)which were separated into several tokens or from which only one constituent tokenwas present on the list – for example, piłka nożna ‘football’.Putting LUs in general domains gave us a kind of initial sense disambiguation.Even inside a domain, more disambiguation was occasionally required. For example,białko denotes ‘egg white’ or ‘protein’.The top-level hierarchy in PWN 1.5 consists of 26 nominal, 15 verbal and fouradjectival domains. We decided to extend the adjectival domains by adding gradual anddeverbal adjectives to the original two domains of relational and descriptive adjectives.The first of the new domains contains adjectives which signal the intensity of a feature(for example, maluśki ‘tiny’); the second domain contains participles. We found thetop-level hierarchy not perfectly suited to Polish, but in the end the division turned outto be unnecessary. The domains only helped distribute work among linguists. Theywere never meant to be a tool of semantic description. Every linguist was given onedomain at a time to work on.After the initial LU list has been established, a group of linguists – with twoexperienced coordinators – constructed the first collection of synsets. The synsets,understood quite broadly, grouped closely related LUs. We needed that first versionfast to help develop automatic methods (to base evaluation on, see Section 3.3) and tomake some applications of the wordnet possible soon. This, however, has turned outto be a wrong decision. It influenced negatively the subsequent steps of plWordNetdevelopment. Constructed in a few months, the initial set of broad synsets becamea “fact on the ground” which made it quite hard for the coordinators to introduce the
38 Chapter 2. Building a Wordnet Corehypernymy structure. Hypernymy among broadly conceived synset had not actuallybeen a primary concern: various other dependencies had been introduced instead. Itis our experience that it would have been much better to build simultaneously thestructure of all wordnet relations.At this stage, further disambiguation and correction of the original list of LUs wasperformed. The linguists worked out synsets wide enough for some hypernyms andquasi-synonyms to be listed as synonyms. The substitution test – the possibility ofusing two words in the same context – is not always precise enough to help distinguishthese relations. Also, expressive and vulgar vocabulary was relocated to hyponymicsynsets, obsolete vocabulary – removed.The team of linguists was located in different cities, so we needed a system tosupport distributed work. A support system should not only enable flexible access andkeep the integrity of the database, but, we assumed, also protect against inconsistenciesand facilitate some management of the work, including options for reporting errors andtracing corrections. Both assumption have been heavily revised by practice, as it willbe discussed shortly.The story of wordnet editors begins with Grinder (Tengi, 1998), a software toolthat checked the PWN source files and converted them into the lexical database. Linguistshad to edit the source files. Syntactic and structural errors, such as pointers tononexistent database elements, were identified only during compilation.The EWN project (Vossen, 2002) constructed Polaris, an editor, and Periscope,a graphical database viewer. Both were commercial tools, tightly coupled with certainproperties of the EWN database structure. The limitations of Polaris prompted theimplementation of a new tool, VisDic, for the Czech WordNet project (Horák and Smrž,2004). In VisDic, relation definitions are still written in text windows, but an XMLformat is used and some immediate browsing is possible in the tool, for example bidirectionalbrowsing of graphs of semantic relations. VisDic is available for research.VisDic was a monolithic application that worked directly on XML files. DEBVis-Dic (Horák et al., 2006), is a lexical database editor that reimplements and extendsthe functionality of VisDic. It is based on the client-server architecture and an XMLdatabase server. Both tools are oriented toward editing a wordnet synchronized withwordnets for other languages by the Interlingua Index (Vossen, 2002). That complicatestheir basic structure and user interface. Those characteristic features wentbeyond our needs, and anyhow DEBVisDic was not known to be available yet at thestart of the plWordNet project. We decided, therefore, to build our own wordnet editor,plWordNetApp [plWNApp] (Piasecki and Koczan, 2007).The plWordNetApp user interface was intended to support the division of work onplWordNet construction into the steps originating from the assumed plan of the wholeprocess. The DEBVisDic tool is much more general: we designed plWNApp screens
Page 1 and 2: A Wordnetfrom the Ground Up
Page 3 and 4: Work financed by the Polish Ministr
Page 7 and 8: 6 Prefaceheartfelt thanks go to all
Page 9: 8 Chapter 1. Motivation, Goals, Ear
Page 12 and 13: 1.1. Motivation 11[a] special form
Page 14 and 15: 1.1. Motivation 13Affect (Strappara
Page 16 and 17: 1.2. The Goals of the plWordNet Pro
Page 18 and 19: 1.2. The Goals of the plWordNet Pro
Page 20 and 21: 1.3. Early Decisions 19Merge Model:
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88 Chapter 3. Discovering Semantic
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102 Chapter 4. Extracting Relation
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166 Chapter 5. Polish WordNet Today
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Appendix ATests for Lexico-semantic
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187Test for adjectives (T. IX)1. p1
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189RelatednessTest for nouns (T. XV
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BibliographyAgarwal, Abhaya and Alo
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Bibliography 193on Deep Lexical Acq
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Bibliography 195Derwojedowa, Magdal
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Bibliography 197Grefenstette, Grego
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Bibliography 199Kurc, Roman. (2008)
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Bibliography 201Mohammad, Saif and
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Bibliography 203. (2006) “The pot
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Bibliography 205and Technology 7(1-
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List of Tables2.1 The size of the c
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List of Figures2.1 The LU perspecti
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List of Figures 2114.16 Completely
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Index 213CBC, see Clustering by Com
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Index 215169, 177, 178, 180, 182hyp
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Index 217mutual hypernymy, 24Mutual
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Index 219SUMO, 14Supported Vector M
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A language without a wordnet is at
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A Wordnet from the Ground Up

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