Marek Maziarz


2023

pdf bib
Data Augmentation Method for Boosting Multilingual Word Sense Disambiguation
Arkadiusz Janz | Marek Maziarz
Proceedings of the 12th Global Wordnet Conference

Recent advances in Word Sense Disambiguation suggest neural language models can be successfully improved by incorporating knowledge base structure. Such class of models are called hybrid solutions. We propose a method of improving hybrid WSD models by harnessing data augmentation techniques and bilingual training. The data augmentation consist of structure augmentation using interlingual connections between wordnets and text data augmentation based on multilingual glosses and usage examples. We utilise language-agnostic neural model trained both with SemCor and Princeton WordNet gloss and example corpora, as well as with Polish WordNet glosses and usage examples. This augmentation technique proves to make well-known hybrid WSD architecture to be competitive, when compared to current State-of-the-Art models, even more complex.

pdf bib
Lexicalised and non-lexicalized multi-word expressions in WordNet: a cross-encoder approach
Marek Maziarz | Łukasz Grabowski | Tadeusz Piotrowski | Ewa Rudnicka | Maciej Piasecki
Proceedings of the 12th Global Wordnet Conference

Focusing on recognition of multi-word expressions (MWEs), we address the problem of recording MWEs in WordNet. In fact, not all MWEs recorded in that lexical database could with no doubt be considered as lexicalised (e.g. elements of wordnet taxonomy, quantifier phrases, certain collocations). In this paper, we use a cross-encoder approach to improve our earlier method of distinguishing between lexicalised and non-lexicalised MWEs found in WordNet using custom-designed rule-based and statistical approaches. We achieve F1-measure for the class of lexicalised word combinations close to 80%, easily beating two baselines (random and a majority class one). Language model also proves to be better than a feature-based logistic regression model.

2022

pdf bib
Multi-word Lexical Units Recognition in WordNet
Marek Maziarz | Ewa Rudnicka | Łukasz Grabowski
Proceedings of the 18th Workshop on Multiword Expressions @LREC2022

WordNet is a state-of-the-art lexical resource used in many tasks in Natural Language Processing, also in multi-word expression (MWE) recognition. However, not all MWEs recorded in WordNet could be indisputably called lexicalised. Some of them are semantically compositional and show no signs of idiosyncrasy. This state of affairs affects all evaluation measures that use the list of all WordNet MWEs as a gold standard. We propose a method of distinguishing between lexicalised and non-lexicalised word combinations in WordNet, taking into account lexicality features, such as semantic compositionality, MWE length and translational criterion. Both a rule-based approach and a ridge logistic regression are applied, beating a random baseline in precision of singling out lexicalised MWEs, as well as in recall of ruling out cases of non-lexicalised MWEs.

2021

pdf bib
Discriminating Homonymy from Polysemy in Wordnets: English, Spanish and Polish Nouns
Arkadiusz Janz | Marek Maziarz
Proceedings of the 11th Global Wordnet Conference

We propose a novel method of homonymy-polysemy discrimination for three Indo-European Languages (English, Spanish and Polish). Support vector machines and LASSO logistic regression were successfully used in this task, outperforming baselines. The feature set utilised lemma properties, gloss similarities, graph distances and polysemy patterns. The proposed ML models performed equally well for English and the other two languages (constituting testing data sets). The algorithms not only ruled out most cases of homonymy but also were efficacious in distinguishing between closer and indirect semantic relatedness.

pdf bib
Testing agreement between lexicographers: A case of homonymy and polysemy
Marek Maziarz | Francis Bond | Ewa Rudnicka
Proceedings of the 11th Global Wordnet Conference

In this paper we compare Oxford Lexico and Merriam Webster dictionaries with Princeton WordNet with respect to the description of semantic (dis)similarity between polysemous and homonymous senses that could be inferred from them. WordNet lacks any explicit description of polysemy or homonymy, but as a network of linked senses it may be used to compute semantic distances between word senses. To compare WordNet with the dictionaries, we transformed sample entry microstructures of the latter into graphs and cross-linked them with the equivalent senses of the former. We found that dictionaries are in high agreement with each other, if one considers polysemy and homonymy altogether, and in moderate concordance, if one focuses merely on polysemy descriptions. Measuring the shortest path lengths on WordNet gave results comparable to those on the dictionaries in predicting semantic dissimilarity between polysemous senses, but was less felicitous while recognising homonymy.

2019

pdf bib
Testing Zipf’s meaning-frequency law with wordnets as sense inventories
Francis Bond | Arkadiusz Janz | Marek Maziarz | Ewa Rudnicka
Proceedings of the 10th Global Wordnet Conference

According to George K. Zipf, more frequent words have more senses. We have tested this law using corpora and wordnets of English, Spanish, Portuguese, French, Polish, Japanese, Indonesian and Chinese. We have proved that the law works pretty well for all of these languages if we take - as Zipf did - mean values of meaning count and averaged ranks. On the other hand, the law disastrously fails in predicting the number of senses for a single lemma. We have also provided the evidence that slope coefficients of Zipfian log-log linear model may vary from language to language.

2018

pdf bib
Towards Mapping Thesauri onto plWordNet
Marek Maziarz | Maciej Piasecki
Proceedings of the 9th Global Wordnet Conference

plWordNet, the wordnet of Polish, has become a very comprehensive description of the Polish lexical system. This paper presents a plan of its semi-automated integration with thesauri, terminological databases and ontologies, as a further necessary step in its development. This will improve linking of plWordNet into Linked Open Data, and facilitate applications in, e.g., WSD, keyword extraction or automated metadata generation. We present an overview of resources relevant to Polish and a plan for their linking to plWordNet.

2016

pdf bib
plWordNet 3.0 – a Comprehensive Lexical-Semantic Resource
Marek Maziarz | Maciej Piasecki | Ewa Rudnicka | Stan Szpakowicz | Paweł Kędzia
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers

We have released plWordNet 3.0, a very large wordnet for Polish. In addition to what is expected in wordnets – richly interrelated synsets – it contains sentiment and emotion annotations, a large set of multi-word expressions, and a mapping onto WordNet 3.1. Part of the release is enWordNet 1.0, a substantially enlarged copy of WordNet 3.1, with material added to allow for a more complete mapping. The paper discusses the design principles of plWordNet, its content, its statistical portrait, a comparison with similar resources, and a partial list of applications.

pdf bib
Adverbs in plWordNet: Theory and Implementation
Marek Maziarz | Stan Szpakowicz | Michal Kalinski
Proceedings of the 8th Global WordNet Conference (GWC)

Adverbs are seldom well represented in wordnets. Princeton WordNet, for example, derives from adjectives practically all its adverbs and whatever involvement they have. GermaNet stays away from this part of speech. Adverbs in plWordNet will be emphatically present in all their semantic and syntactic distinctness. We briefly discuss the linguistic background of the lexical system of Polish adverbs. We describe an automated generator of accurate candidate adverbs, and introduce the lexicographic procedures which will ensure high consistency of wordnet editors’ decisions about adverbs.

pdf bib
plWordNet 3.0 – Almost There
Maciej Piasecki | Stan Szpakowicz | Marek Maziarz | Ewa Rudnicka
Proceedings of the 8th Global WordNet Conference (GWC)

It took us nearly ten years to get from no wordnet for Polish to the largest wordnet ever built. We started small but quickly learned to dream big. Now we are about to release plWordNet 3.0-emo – complete with sentiment and emotions annotated – and a domestic version of Princeton WordNet, larger than WordNet 3.1 by nearly ten thousand newly added words. The paper retraces the road we travelled and talks a little about the future.

2015

pdf bib
A Procedural Definition of Multi-word Lexical Units
Marek Maziarz | Stan Szpakowicz | Maciej Piasecki
Proceedings of the International Conference Recent Advances in Natural Language Processing

pdf bib
Extraction of the Multi-word Lexical Units in the Perspective of the Wordnet Expansion
Maciej Piasecki | Michał Wendelberger | Marek Maziarz
Proceedings of the International Conference Recent Advances in Natural Language Processing

2014

pdf bib
plWordNet as the Cornerstone of a Toolkit of Lexico-semantic Resources
Marek Maziarz | Maciej Piasecki | Ewa Rudnicka | Stan Szpakowicz
Proceedings of the Seventh Global Wordnet Conference

pdf bib
Registers in the System of Semantic Relations in plWordNet
Marek Maziarz | Maciej Piasecki | Ewa Rudnicka | Stan Szpakowicz
Proceedings of the Seventh Global Wordnet Conference

2013

pdf bib
Recognizing semantic relations within Polish noun phrase: A rule-based approach
Paweł Kędzia | Marek Maziarz
Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013

pdf bib
Beyond the Transfer-and-Merge Wordnet Construction: plWordNet and a Comparison with WordNet
Marek Maziarz | Maciej Piasecki | Ewa Rudnicka | Stan Szpakowicz
Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013

2012

pdf bib
A Strategy of Mapping Polish WordNet onto Princeton WordNet
Ewa Rudnicka | Marek Maziarz | Maciej Piasecki | Stan Szpakowicz
Proceedings of COLING 2012: Posters

pdf bib
IKAR: An Improved Kit for Anaphora Resolution for Polish
Bartosz Broda | Łukasz Burdka | Marek Maziarz
Proceedings of COLING 2012: Demonstration Papers

pdf bib
Tools for plWordNet Development. Presentation and Perspectives
Bartosz Broda | Marek Maziarz | Maciej Piasecki
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

Building a wordnet is a serious undertaking. Fortunately, Language Technology (LT) can improve the process of wordnet construction both in terms of quality and cost. In this paper we present LT tools used during the construction of plWordNet and their influence on the lexicographer's work-flow. LT is employed in plWordNet development on every possible step: from data gathering through data analysis to data presentation. Nevertheless, every decision requires input from the lexicographer, but the quality of supporting tools is an important factor. Thus a limited evaluation of usefulness of employed tools is carried out on the basis of questionnaires.

pdf bib
Recognition of Polish Derivational Relations Based on Supervised Learning Scheme
Maciej Piasecki | Radoslaw Ramocki | Marek Maziarz
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

The paper presents construction of \emph{Derywator} -- a language tool for the recognition of Polish derivational relations. It was built on the basis of machine learning in a way following the bootstrapping approach: a limited set of derivational pairs described manually by linguists in plWordNet is used to train \emph{Derivator}. The tool is intended to be applied in semi-automated expansion of plWordNet with new instances of derivational relations. The training process is based on the construction of two transducers working in the opposite directions: one for prefixes and one for suffixes. Internal stem alternations are recognised, recorded in a form of mapping sequences and stored together with transducers. Raw results produced by \emph{Derivator} undergo next corpus-based and morphological filtering. A set of derivational relations defined in plWordNet is presented. Results of tests for different derivational relations are discussed. A problem of the necessary corpus-based semantic filtering is analysed. The presented tool depends to a very little extent on the hand-crafted knowledge for a particular language, namely only a table of possible alternations and morphological filtering rules must be exchanged and it should not take longer than a couple of working days.

pdf bib
KPWr: Towards a Free Corpus of Polish
Bartosz Broda | Michał Marcińczuk | Marek Maziarz | Adam Radziszewski | Adam Wardyński
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper presents our efforts aimed at collecting and annotating a free Polish corpus. The corpus will serve for us as training and testing material for experiments with Machine Learning algorithms. As others may also benefit from the resource, we are going to release it under a Creative Commons licence, which is hoped to remove unnecessary usage restrictions, but also to facilitate reproduction of our experimental results. The corpus is being annotated with various types of linguistic entities: chunks and named entities, selected syntactic and semantic relations, word senses and anaphora. We report on the current state of the project as well as our ultimate goals.