| Challenge: | Bantu languages are still computationally under-resourced due to their complex grammatical structure . morphological analyzers, text generation tools and a morphology analyzer are among the tools used . |
| Approach: | They propose a syntactic and semantic method to disambiguate among singular nouns . they use the nearest neighbors of a query word as semantic generalizations based on Runyankore . |
| Outcome: | The proposed method improves accuracy in three Bantu languages compared to using only the syntactic or semantic approach. |
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Pluralizing Nouns across Agglutinating Bantu Languages (C18-1)
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| Challenge: | Pluralization of nouns is a challenge for the Bantu language family . results show that the language's definition of noune classes is inadequate for computational purposes due to non-determinism in prefixes. |
| Approach: | They investigated the approach to pluralization in isiZulu and Runyankore for seven languages across three different Guthrie language zones. |
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A Tour of Explicit Multilingual Semantics: Word Sense Disambiguation, Semantic Role Labeling and Semantic Parsing (2022.aacl-tutorials)
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| Challenge: | a recent advent of pretrained language models has sparked a revolution in NLP . but, there are still questions about whether current approaches capture explicit, symbolic meaning . this tutorial will review efforts to tackle three key open problems in lexical and sentence-level semantics . |
| Approach: | This tutorial reviews recent efforts to shed light on meaning in NLP . it will focus on three key open problems in lexical and sentence-level semantics . |
| Outcome: | This tutorial reviews recent efforts to shed light on meaning in NLP . it focuses on three key open problems in lexical and sentence-level semantics . |
The Interplay between Metaphors and NLP (2026.acl-tutorials)
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| Challenge: | This tutorial will provide an overview of the metaphor processing field. |
| Approach: | This tutorial will provide an overview of the metaphor processing field . it will focus on recent directions opened by LLMs for metaphor interpretation . |
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Huge Automatically Extracted Training-Sets for Multilingual Word SenseDisambiguation (L18-1)
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| Challenge: | Word Sense Disambiguation is a crucial task in Natural Language Processing . supervised systems need to be trained on word-by-word basis, a problem that is beyond reach for resource-rich languages like English. |
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SANDWiCH: Semantical Analysis of Neighbours for Disambiguating Words in Context ad Hoc (2025.naacl-long)
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| Challenge: | Recent studies show that language understanding offered by chat-based Large Language Models is limited and far from human-like performance. |
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Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: Tutorial Abstracts (2022.aacl-tutorials)
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| Challenge: | . - (EN) |
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Towards a Standardized Dataset for Noun Compound Interpretation (L18-1)
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| Challenge: | Noun compounds are interesting constructs in Natural Language Processing . lack of standardized set of relation inventories and annotated datasets hinders interpretation . |
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SyntagNet: Challenging Supervised Word Sense Disambiguation with Lexical-Semantic Combinations (D19-1)
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| Challenge: | Current research in knowledge-based Word Sense Disambiguation (WSD) indicates that performances depend heavily on the Lexical Knowledge Base (LKB) employed. |
| Approach: | They propose to use a Lexical Knowledge Base to capture syntagmatic relations to enable knowledge-based WSD systems to achieve a new state of the art. |
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Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Tutorial Abstracts (2021.acl-tutorials)
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| Challenge: | . - (EN) |
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A Survey on Automatically-Constructed WordNets and their Evaluation: Lexical and Word Embedding-based Approaches (L18-1)
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| Challenge: | WordNets are lexical databases in which groups of synonyms are stored according to the semantic relationships between them. |
| Approach: | This paper describes various approaches to constructing WordNets automatically by leveraging traditional lexical resources and newer trends such as word embeddings. |
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