Papers by Nina Tahmasebi
SenSALDO: Creating a Sentiment Lexicon for Swedish (L18-1)
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| Challenge: | sentiment analysis has seen an explosive expansion over the last decade or so . many theoretical and methodological questions remain unanswered and resource gaps unfilled . |
| Approach: | They develop a sentiment lexicon for written (standard) Swedish using an existing dataset . they assign a real value sentiment score in the range [-1,1] and produce a label for it . |
| Outcome: | The proposed sentiment lexicon is an open source resource from the Swedish Language Bank . it is based on an existing gold standard dataset and is available from Sprkbanken . |
Analyzing Semantic Change through Lexical Replacements (2024.acl-long)
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| Challenge: | Modern language models can contextualize words based on their surrounding contexts, but semantic change can compromise this capability. |
| Approach: | They propose a replacement schema where a target word is replaced with lexical replacements of varying relatedness . they leverage the replacement schema as a basis for a novel interpretable model for semantic change . |
| Outcome: | The proposed model is the first to evaluate LLaMa for semantic change detection . it shows that lexical replacements can detect unexpected contexts . |
Automatically Generated Definitions and their utility for Modeling Word Meaning (2024.emnlp-main)
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| Challenge: | Modern language models generate semantic representations for words based on context and context based models. |
| Approach: | They propose to use dictionary-like sense definitions to generate sentence embeddings . they evaluate the quality of the generated definitions on existing English benchmarks based on the results of their study . |
| Outcome: | The proposed model sets new state-of-the-art results on lexical semantics tasks compared to baselines . |
Superlim: A Swedish Language Understanding Evaluation Benchmark (2023.emnlp-main)
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Aleksandrs Berdicevskis, Gerlof Bouma, Robin Kurtz, Felix Morger, Joey Öhman, Yvonne Adesam, Lars Borin, Dana Dannélls, Markus Forsberg, Tim Isbister, Anna Lindahl, Martin Malmsten, Faton Rekathati, Magnus Sahlgren, Elena Volodina, Love Börjeson, Simon Hengchen, Nina Tahmasebi
| Challenge: | In this paper, we present a multi-task benchmark for Swedish language models . we address methodological challenges, such as mitigating the Anglocentric bias when creating datasets for a less-resourced language . |
| Approach: | They propose a multi-task NLP benchmark for Swedish language models . they propose to use superlim to evaluate Swedish language model performance . |
| Outcome: | The proposed benchmark does not approach ceiling performance on any of the tasks, suggesting it is difficult to implement. |
A Systematic Comparison of Contextualized Word Embeddings for Lexical Semantic Change (2024.naacl-long)
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| Challenge: | Contextualized embeddings are the preferred tool for modeling Lexical Semantic Change (LSC) current evaluations focus on a specific task known as Graded Change Detection (GCD) however, performance comparisons between different approaches are often misleading due to diverse settings. |
| Approach: | They evaluate the performance of contextualized embeddings for Lexical Semantic Change (LSC) they break the problem into Word-in-Context (WiC) and Word Sense Induction (WSI) tasks . |
| Outcome: | The proposed model outperforms other models on eight available benchmarks for Lexical Semantic Change (LSC) while comparable to GPT-4. |
(Chat)GPT v BERT Dawn of Justice for Semantic Change Detection (2024.findings-eacl)
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| Challenge: | In the universe of Natural Language Processing, Transformer-based language models like BERT and (Chat)GPT have emerged as lexical superheroes with great power to solve open research problems. |
| Approach: | They propose to use (Chat)GPT to solve two diachronic extensions of the Word-in-Context task: TempoWiC and HistoWic. |
| Outcome: | The proposed technology performs significantly worse than the foundational GPT version of (Chat)GPT for studying semantic change. |
Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change (P19-1)
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| Challenge: | State-of-the-art lexical semantic change detection models suffer from noise stemming from vector space alignment. |
| Approach: | They propose a method to simulate lexical semantic change and control for possible biases by avoiding alignment. |
| Outcome: | The proposed method outperforms state-of-the-art models on a synthetic task and a manual testset. |
Computational modeling of semantic change (2024.eacl-tutorials)
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| Challenge: | Languages change constantly over time, influenced by social, technological, cultural and political factors that affect how people express themselves. |
| Approach: | They propose to categorise the types of change, the causes and the mechanisms underlying the different types of changes using large diachronic corpora and evaluation benchmarks. |
| Outcome: | In historical linguistics, tools and methods have been developed to analyse the process . they include categorisations of types of change, causes and mechanisms . but traditional methods, while informative, are often based on small, carefully curated samples. |
More DWUGs: Extending and Evaluating Word Usage Graph Datasets in Multiple Languages (2024.emnlp-main)
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Dominik Schlechtweg, Pierluigi Cassotti, Bill Noble, David Alfter, Sabine Schulte Im Walde, Nina Tahmasebi
| Challenge: | Word Usage Graphs (WUGs) represent word sense clusters from simple pairwise word use judgments. |
| Approach: | They propose to use a weighted graph to represent human semantic proximity judgments for pairs of word uses to infer word sense clusters from simple pairwise word use judgments. |
| Outcome: | The proposed approach can be applied in a Word Sense Induction (WSI) setting or for Word sense disambiguation (WSD) it is the first and to date largest manually annotated, diachronic WUG dataset. |
TRoTR: A Framework for Evaluating the Re-contextualization of Text Reuse (2024.emnlp-main)
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| Challenge: | Existing methods for detecting text reuse focus on recontextualization . current approaches focus on text reuse across a diachronic corpus . |
| Approach: | They propose a framework that relies on topic relatedness for evaluating the diachronic change of context in which text is reused. |
| Outcome: | The proposed framework evaluates biblical text reuse human-annotated with topic relatedness . it exhibits greater sensitivity to textual similarity than topic relatedity, the authors show . |
DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages (2021.emnlp-main)
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| Challenge: | Existing methods for graded contextual word meaning annotation have not been implemented yet. |
| Approach: | They propose a multi-round incremental annotation process and a clustering algorithm to group usages into senses to create a large-scale dataset. |
| Outcome: | The proposed method is the largest resource of graded contextualized, diachronic word meaning annotation in four different languages, based on 100,000 human semantic proximity judgments. |
Generating a Gold Standard for a Swedish Sentiment Lexicon (L18-1)
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| Challenge: | Existing sentiment lexicons are compiled by (machine) translation from English resources, obscuring language-specific characteristics of sentiment-loaded vocabulary. |
| Approach: | They propose a gold standard for sentiment annotation of Swedish terms using the SALDO lexicon and the Gigaword corpus. |
| Outcome: | The proposed model is based on the free SALDO lexicon and the Gigaword corpus and is compared with existing models using human annotations. |
Using Synchronic Definitions and Semantic Relations to Classify Semantic Change Types (2024.acl-long)
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| Challenge: | Existing models for detecting semantic change in corpora have been disregarded due to lack of knowledge of the nature of semantic change and the way it takes place. |
| Approach: | They propose a model that leverages synchronic lexical relations and definitions of word meanings to detect these types of change. |
| Outcome: | The proposed model can detect changes in a digitized version of Blank's dataset and improve human judgments of semantic relatedness and binary Lexical Semantic Change Detection. |
SenseRel: A Sense-Level Benchmark for Denotational and Connotational Meaning Relations (2026.acl-long)
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Pierluigi Cassotti, Naomi Baes, Stefano De Pascale, Jáder Martins Camboim de Sá, Francesco Periti, Nick Haslam, Dirk Geeraerts, Nina Tahmasebi
| Challenge: | Polysemy enables a single word to convey multiple related meanings . a word's sense is extended to new contexts and concepts, a process called semantic change is gradual . |
| Approach: | They propose a benchmark for modeling semantic relations between word senses . they use a model that distinguishes denotational and connotationally related aspects of meaning . |
| Outcome: | The proposed model is able to distinguish between denotational and connotationalist aspects of meaning . it is compared with models with GPT-4o, Llama 3.1, and DeepSeek . |
Definition Generation for Word Meaning Modeling: Monolingual, Multilingual, and Cross-Lingual Perspectives (2025.emnlp-main)
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| Challenge: | Recent advances in text generation have opened up new opportunities for word meaning modeling. |
| Approach: | They extend definition generation task beyond English to a suite of 22 languages . they use Llama-based models to evaluate models in monolingual, multilingual, cross-lingual settings . |
| Outcome: | The proposed model outperforms pretrained models in monolingual, multilingual, and cross-lingual settings. |
Elections go bananas: A First Large-scale Multilingual Study of Pluralia Tantum using LLMs (2026.eacl-long)
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| Challenge: | a large amount of annotated sentences for each feature can be used for in-depth analysis. |
| Approach: | They propose an annotation framework for lexicalization of pluralia tantum . they use an LLM to annotate each instance from the reference corpus . |
| Outcome: | The proposed framework provides useful annotators for semantic, syntactic and sense categories with accuracy ranging from 51% to 89% on a hand-annotated testset. |
The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change (2024.eacl-demo)
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Dominik Schlechtweg, Shafqat Mumtaz Virk, Pauline Sander, Emma Sköldberg, Lukas Theuer Linke, Tuo Zhang, Nina Tahmasebi, Jonas Kuhn, Sabine Schulte Im Walde
| Challenge: | DURel is an open source tool for semantic proximity between word uses. |
| Approach: | They present an open-source tool for the annotation of semantic proximity between word uses. |
| Outcome: | The proposed tool supports standardized human annotation and computational annotation, building on recent advances with Word-in-Context models. |