Creation of a Balanced State-of-the-Art Multilayer Corpus for NLU (L18-1)

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Challenge: Using full stack of language resources, we are creating a balanced text corpus for Latvian.
Approach: They propose to create a syntactically and semantically annotated multilayered corpus for Latvian . they use widely acknowledged and cross-lingual representations for the corpus .
Outcome: The proposed corpus adopts widely recognized and cross-lingual representations for natural language understanding and generation in Latvian.

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Challenge: a paper aims at enriching the manually annotated part of National Corpus of Polish with a syntactic layer.
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MOSAICo: a Multilingual Open-text Semantically Annotated Interlinked Corpus (2024.naacl-long)

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Challenge: Existing approaches to integrate semantics into Natural Language Understanding (NLP) systems are cost-effective and environmental impact-related.
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BalsuTalka.lv - Boosting the Common Voice Corpus for Low-Resource Languages (2024.lrec-main)

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Challenge: Latvian is a low-resource language for many NLP tasks, but most speech corpora are closed data . a crowdsourcing campaign to create a relatively large, diverse and open speech corpus for Latvian has been launched .
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Data Augmentation and Learned Layer Aggregation for Improved Multilingual Language Understanding in Dialogue (2022.findings-acl)

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Challenge: Multi-SentAugment and LayerAgg are self-training methods that augment available training data with similar (automatically labelled) in-domain sentences from large monolingual Web-scale corpora.
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The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages (2020.lrec-1)

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Challenge: Until recently, language descriptions were available in paper form only, with indexes as the only search aid.
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AMR Beyond the Sentence: the Multi-sentence AMR corpus (C18-1)

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Challenge: Abstract Meaning Representation (AMR) is limited to capturing the semantics of individual sentences.
Approach: They propose a corpus that annotates coreference and similar phenomena on top of existing AMRs.
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Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection (2020.lrec-1)

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Challenge: Universal Dependencies is an open community effort to create cross-linguistically consistent treebank annotation for many languages.
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Cross-lingual Semantic Representation for NLP with UCCA (2020.coling-tutorials)

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Challenge: introductory tutorial to UCCA, a symbolic meaning representation for semantic representations.
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Towards AMR-BR: A SemBank for Brazilian Portuguese Language (L18-1)

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Challenge: Abstract Meaning Representation (AMR) is a recent and prominent meaning representation with good acceptance and several applications in the Natural Language Processing area.
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EmpiriST Corpus 2.0: Adding Manual Normalization, Lemmatization and Semantic Tagging to a German Web and CMC Corpus (2020.lrec-1)

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Challenge: EmpiriST corpus is a manually tokenized and part-of-speech tagged corpus of German web and CMC data.
Approach: They extend the corpus with manually tokenized annotation layers for word form normalization, lemmatization and lexical semantics.
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