Marek Maziarz

In this paper we argue in favor of the radial semantic structure of polysemous entries from the New Oxford Dictionary of English (NODE) and the Merriam-Webster dictionary. We formalized four polysemy theories as algorithms linking word senses into polysemy networks, considering the semantic similarity of dictionary definitions calculated using large language models. Chaining algorithms maximized similarity within polysemy nets and adequately distinguished senses that in the two dictionaries are directly related from those more distant.

One of the main research questions concerning multi-word expressions (MWEs) is which of them are transparent word combinations createdad hocand which are multi-word lexical units (MWUs). In this paper, we use selected corpus-linguistic and machine-learning methods to determine which lexicalization criteria guide Polish and English lexicographers in deciding which MWEs (bigrams such as adjective+noun and noun+noun combinations) should be treated as lexical units recorded in dictionaries as MWUs. We analyzed two samples: MWEs extracted from Polish and English monolingual dictionaries, and those created by the annotators, and tested two custom-designed criteria, i.e., intuition and paraphrase, also by using statistical methods (measures of collocational strength: PMI and Jaccard). We revealed that Polish lexicographers have a tendency not to include compositional MWEs as lexical entries in their dictionaries and that the criteria of paraphrase and intuition are important for them: if MWEs are not clearly and unambiguously paraphrasable and compositional, then they are recorded in dictionaries. We found that in contrast to Polish lexicographers English lexicographers tend to record also compositional and partly compositional MWEs.

Marek Maziarz, Łukasz Grabowski, Tadeusz Piotrowski, Ewa Rudnicka, Maciej Piasecki. Proceedings of the 12th Global Wordnet Conference. 2023.

Expanding WordNet with Gloss and Polysemy Links for Evocation Strength Recognition Evocation – a phenomenon of sense associations going beyond standard (lexico)-semantic relations – is difficult to recognise for natural language processing systems. Machine learning models give predictions which are only moderately correlated with the evocation strength. It is believed that ordinary graph measures are not as good at this task as methods based on vector representations. The paper proposes a new method of enriching the WordNet structure with weighted polysemy and gloss links, and proves that Dijkstra’s algorithm performs equally as well as other more sophisticated measures when set together with such expanded structures. Rozszerzenie WordNetu o glosy i relacje polisemiczne na potrzeby rozpoznawania siły ewokacji Ewokacja – zjawisko skojarzeń zmysłowych wykraczających poza standardowe (leksykalne) relacje semantyczne – jest trudne do rozpoznania dla systemów przetwarzania języka naturalnego. Modele uczenia maszynowego dają prognozy tylko umiarkowanie skorelowane z siłą ewokacji. Uważa się, że zwykłe miary grafowe nie są tak dobre w tym zadaniu, jak metody oparte na reprezentacjach wektorowych. Proponujemy nową metodę wzbogacania struktury WordNet o polisemie ważone i linki połysku i udowadniamy, że algorytm Dijkstry zestawiony z tak rozbudowanymi strukturami działa a także inne, bardziej wyrafinowane środki.

Semantic relations between verbs in Polish WordNet 2.0 The noun dominates wordnets. The lexical semantics of verbs is usually under-represented, even if it is essential in any semantic analysis which goes beyond statistical methods. We present our attempt to remedy the imbalance; it begins by designing a sufficiently rich set of wordnet relations for verbs. We discuss and show in detail such a relation set in the largest Polish wordnet. Our design decisions, while as general and language-independent as possible, are mainly informed by our desire to capture the nature and peculiarities of the verb system in Polish.

Semantic relations among nouns in Polish WordNet grounded in lexicographic and semantic tradition The paper describes a system of lexico-semantic relations proposed for the nominal part of plWordNet 2.0 – the largest Polish wordnet. We briefly introduce a wordnet as a large electronic thesaurus. We discuss sixteen nominal relations together with many sub-types proposed for plWordNet 2.0. Each relation is based on linguistic intuition and supported by a set of tests which facilitate its identification. There are two main groups: pure lexico-semantic relations and semantic-derivational relations.

Semantic relations among adjectives in Polish WordNet 2.0: a new relation set, discussion and evaluation Adjectives in wordnets are often neglected: there are many fewer of them than nouns, and relations among them are sometimes not as varied as those among nouns or verbs. Polish WordNet 1.0 was no exception. Version 2.0 aims to correct that. We present an overview of a much larger set of lexical-semantic relations which connect adjectives to the other parts of the network. Our choice of relations has been motivated by linguistic considerations, especially the concerns of the Polish lexical semantics, and by pragmatic reasons. The discussion includes detailed substitution tests, meant to ensure consistency among wordnet editors.