Lauma Pretkalniņa

Also published as: Lauma Pretkalnina, Lauma Pretkalnin̨a


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A Computational Model of Latvian Morphology
Peteris Paikens | Lauma Pretkalniņa | Laura Rituma
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

In this paper we describe a computational model of Latvian morphology that provides a formal structure for Latvian word form inflection and has been implemented in software for generation, analysis and lemmatization of Latvian word forms. The work was motivated by the need for a NLP inflection model that can cover all the complexity of Latvian language and explicitly enumerate and handle the many exceptions to the general Latvian inflection principles. This is an evolution of earlier work, extending the initial proof of concept model to properly cover Latvian language. We provide a set of morphological paradigms that differ from current linguistic tradition, a set of systematic stem changes and combine it with an extensive lexicon that includes paradigm information and structured morphological attributes for 118 000 lexemes. This model has been applied on both dictionary and corpora data, demonstrating that it provides a good coverage for modern Latvian literary language. We also consider that there is a good potential to extend this also to the related Latgalian language.


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Latvian WordNet
Peteris Paikens | Agute Klints | Ilze Lokmane | Lauma Pretkalniņa | Laura Rituma | Madara Stāde | Laine Strankale
Proceedings of the 12th Global Wordnet Conference

This paper describes the recently developed Latvian WordNet and the main linguistic principles used in its development. The inventory of words and senses is based on the Te̅ online dictionary, restructuring the senses of the most frequently used words based on corpus evidence. The semantic linking methodology adapts Princeton WordNet principles to fit the Latvian language usage and existing linguistic tradition. The semantic links include hyponymy, meronymy, antonymy, similarity, conceptual connection and gradation. We also measure inter-annotator agreement for different types of semantic links. The dataset consists of 7609 words linked in 6515 synsets. 1266 of these words are considered fully completed as they have all the outgoing semantic links annotated, corpus examples assigned for each sense, as well as links to the English Princeton WordNet formed. The data is available to the public on Te̅ as an addition to the general dictionary data, and is also published as a downloadable dataset.


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Towards Latvian WordNet
Peteris Paikens | Mikus Grasmanis | Agute Klints | Ilze Lokmane | Lauma Pretkalniņa | Laura Rituma | Madara Stāde | Laine Strankale
Proceedings of the Thirteenth Language Resources and Evaluation Conference

In this paper we describe our current work on creating a WordNet for Latvian based on the principles of the Princeton WordNet. The chosen methodology for word sense definition and sense linking is based on corpus evidence and the existing online dictionary, ensuring a foundation that fits the Latvian language usage and existing linguistic tradition. We cover a wide set of semantic relations, including gradation sets. Currently the dataset consists of 6432 words linked in 5528 synsets, out of which 2717 synsets are considered fully completed as they have all the outgoing semantic links annotated, annotated with corpus examples for each sense and links to the English Princeton WordNet.

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Latvian National Corpora Collection –
Baiba Saulite | Roberts Darģis | Normunds Gruzitis | Ilze Auzina | Kristīne Levāne-Petrova | Lauma Pretkalniņa | Laura Rituma | Peteris Paikens | Arturs Znotins | Laine Strankale | Kristīne Pokratniece | Ilmārs Poikāns | Guntis Barzdins | Inguna Skadiņa | Anda Baklāne | Valdis Saulespurēns | Jānis Ziediņš
Proceedings of the Thirteenth Language Resources and Evaluation Conference

LNCC is a diverse collection of Latvian language corpora representing both written and spoken language and is useful for both linguistic research and language modelling. The collection is intended to cover diverse Latvian language use cases and all the important text types and genres (e.g. news, social media, blogs, books, scientific texts, debates, essays, etc.), taking into account both quality and size aspects. To reach this objective, LNCC is a continuous multi-institutional and multi-project effort, supported by the Digital Humanities and Language Technology communities in Latvia. LNCC includes a broad range of Latvian texts from the Latvian National Library, Culture Information Systems Centre, Latvian National News Agency, Latvian Parliament, Latvian web crawl, various Latvian publishers, and from the Latvian language corpora created by Institute of Mathematics and Computer Science and its partners, including spoken language corpora. All corpora of LNCC are re-annotated with a uniform morpho-syntactic annotation scheme which enables federated search and consistent linguistics analysis in all the LNCC corpora, as well as facilitates to select and mix various corpora for pre-training large Latvian language models like BERT and GPT.


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Creation of a Balanced State-of-the-Art Multilayer Corpus for NLU
Normunds Gruzitis | Lauma Pretkalnina | Baiba Saulite | Laura Rituma | Gunta Nespore-Berzkalne | Arturs Znotins | Peteris Paikens
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


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Tē the Largest Open Lexical Database for Latvian
Andrejs Spektors | Ilze Auzina | Roberts Dargis | Normunds Gruzitis | Peteris Paikens | Lauma Pretkalnina | Laura Rituma | Baiba Saulite
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

We describe an extensive and versatile lexical resource for Latvian, an under-resourced Indo-European language, which we call Tezaurs (Latvian for ‘thesaurus’). It comprises a large explanatory dictionary of more than 250,000 entries that are derived from more than 280 external sources. The dictionary is enriched with phonetic, morphological, semantic and other annotations, as well as augmented by various language processing tools allowing for the generation of inflectional forms and pronunciation, for on-the-fly selection of corpus examples, for suggesting synonyms, etc. Tezaurs is available as a public and widely used web application for end-users, as an open data set for the use in language technology (LT), and as an API ― a set of web services for the integration into third-party applications. The ultimate goal of Tezaurs is to be the central computational lexicon for Latvian, bringing together all Latvian words and frequently used multi-word units and allowing for the integration of other LT resources and tools.


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Dependency parsing representation effects on the accuracy of semantic applications — an example of an inflective language
Lauma Pretkalniņa | Artūrs Znotiņš | Laura Rituma | Didzis Goško
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

In this paper we investigate how different dependency representations of a treebank influence the accuracy of the dependency parser trained on this treebank and the impact on several parser applications: named entity recognition, coreference resolution and limited semantic role labeling. For these experiments we use Latvian Treebank, whose native annotation format is dependency based hybrid augmented with phrase-like elements. We explore different representations of coordinations, complex predicates and punctuation mark attachment. Our experiments shows that parsers trained on the variously transformed treebanks vary significantly in their accuracy, but the best-performing parser as measured by attachment score not always leads to best accuracy for an end application.


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Morphological Analysis with Limited Resources: Latvian Example
Pēteris Paikens | Laura Rituma | Lauma Pretkalniņa
Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013)

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Statistical Syntactic Parsing for Latvian
Lauma Pretkalniņa | Laura Rituma
Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013)


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A Prague Markup Language profile for the SemTi-Kamols grammar model
Lauma Pretkalniņa | Gunta Nešpore | Kristīne Levāne-Petrova | Baiba Saulīte
Proceedings of the 18th Nordic Conference of Computational Linguistics (NODALIDA 2011)


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Towards Improving English-Latvian Translation: A System Comparison and a New Rescoring Feature
Maxim Khalilov | José A. R. Fonollosa | Inguna Skadin̨a | Edgars Brālītis | Lauma Pretkalnin̨a
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Translation into the languages with relatively free word order has received a lot less attention than translation into fixed word order languages (English), or into analytical languages (Chinese). At the same time this translation task is found among the most difficult challenges for machine translation (MT), and intuitively it seems that there is some space in improvement intending to reflect the free word order structure of the target language. This paper presents a comparative study of two alternative approaches to statistical machine translation (SMT) and their application to a task of English-to-Latvian translation. Furthermore, a novel feature intending to reflect the relatively free word order scheme of the Latvian language is proposed and successfully applied on the n-best list rescoring step. Moving beyond classical automatic scores of translation quality that are classically presented in MT research papers, we contribute presenting a manual error analysis of MT systems output that helps to shed light on advantages and disadvantages of the SMT systems under consideration.