Miloš Jakubíček


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ShadowSense: A Multi-annotated Dataset for Evaluating Word Sense Induction
Ondřej Herman | Miloš Jakubíček
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

In this paper we present a novel bilingual (Czech, English) dataset called ShadowSense developed for the purposes of word sense induction (WSI) evaluation. Unlike existing WSI datasets, ShadowSense is annotated by multiple annotators whose inter-annotator agreement represents key reliability score to be used for evaluation of systems automatically inducing word senses. In this paper we clarify the motivation for such an approach, describe the dataset in detail and provide evaluation of three neural WSI systems showing substantial differences compared to traditional evaluation paradigms.


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Current Challenges in Web Corpus Building
Miloš Jakubíček | Vojtěch Kovář | Pavel Rychlý | Vit Suchomel
Proceedings of the 12th Web as Corpus Workshop

In this paper we discuss some of the current challenges in web corpus building that we faced in the recent years when expanding the corpora in Sketch Engine. The purpose of the paper is to provide an overview and raise discussion on possible solutions, rather than bringing ready solutions to the readers. For every issue we try to assess its severity and briefly discuss possible mitigation options.


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English-French Document Alignment Based on Keywords and Statistical Translation
Marek Medveď | Miloš Jakubíček | Vojtech Kovář
Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers

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European Union Language Resources in Sketch Engine
Vít Baisa | Jan Michelfeit | Marek Medveď | Miloš Jakubíček
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Several parallel corpora built from European Union language resources are presented here. They were processed by state-of-the-art tools and made available for researchers in the corpus manager Sketch Engine. A completely new resource is introduced: EUR-Lex Corpus, being one of the largest parallel corpus available at the moment, containing 840 million English tokens and the largest language pair English-French has more than 25 million aligned segments (paragraphs).


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Extrinsic Corpus Evaluation with a Collocation Dictionary Task
Adam Kilgarriff | Pavel Rychlý | Miloš Jakubíček | Vojtěch Kovář | Vít Baisa | Lucia Kocincová
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

The NLP researcher or application-builder often wonders “what corpus should I use, or should I build one of my own? If I build one of my own, how will I know if I have done a good job?” Currently there is very little help available for them. They are in need of a framework for evaluating corpora. We develop such a framework, in relation to corpora which aim for good coverage of ‘general language’. The task we set is automatic creation of a publication-quality collocations dictionary. For a sample of 100 headwords of Czech and 100 of English, we identify a gold standard dataset of (ideally) all the collocations that should appear for these headwords in such a dictionary. The datasets are being made available alongside this paper. We then use them to determine precision and recall for a range of corpora, with a range of parameters.

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Finding Terms in Corpora for Many Languages with the Sketch Engine
Miloš Jakubíček | Adam Kilgarriff | Vojtěch Kovář | Pavel Rychlý | Vít Suchomel
Proceedings of the Demonstrations at the 14th Conference of the European Chapter of the Association for Computational Linguistics


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Building a 70 billion word corpus of English from ClueWeb
Jan Pomikálek | Miloš Jakubíček | Pavel Rychlý
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This work describes the process of creation of a 70 billion word text corpus of English. We used an existing language resource, namely the ClueWeb09 dataset, as source for the corpus data. Processing such a vast amount of data presented several challenges, mainly associated with pre-processing (boilerplate cleaning, text de-duplication) and post-processing (indexing for efficient corpus querying using the CQL -- Corpus Query Language) steps. In this paper we explain how we tackled them: we describe the tools used for boilerplate cleaning (jusText) and for de-duplication (onion) that was performed not only on full (document-level) duplicates but also on the level of near-duplicate texts. Moreover we show the impact of each of the performed pre-processing steps on the final corpus size. Furthermore we show how effective parallelization of the corpus indexation procedure was employed within the Manatee corpus management system and during computation of word sketches (one-page, automatic, corpus-derived summaries of a word's grammatical and collocational behaviour) from the resulting corpus.


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Through Low-Cost Annotation to Reliable Parsing Evaluation
Marek Grác | Miloš Jakubíček | Vojtěch Kovář
Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation

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Fast Syntactic Searching in Very Large Corpora for Many Languages
Miloš Jakubíček | Adam Kilgarriff | Diana McCarthy | Pavel Rychlý
Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation