Papers by Simone Teufel
ChainNet: Structured Metaphor and Metonymy in WordNet (2024.lrec-main)
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| Challenge: | In a typical lexicon, word senses are encoded as a list, without inter-sense relations. |
| Approach: | They propose a lexical resource which explicitly identifies the senses of a word's senses by expressing how they are derived from one another. |
| Outcome: | The proposed resource expresses how senses in the Open English Wordnet are derived from one another. |
Faithful Knowledge Graph Explanations in Commonsense Question Answering (2022.emnlp-main)
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| Challenge: | Knowledge graphs are used to express explanations for the model's answer choice. |
| Approach: | They propose to use knowledge graphs to encode facts separately from the question and combine them to select an answer. |
| Outcome: | The proposed architectures can be used to express the facts used to answer a question in a graph-based explanation, but they will not include reasoning done by the transformer encoding the question, and will be incomplete. |
Scansion-based Lyrics Generation (2024.lrec-main)
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| Challenge: | a new method for generating lyrics for Mandarin songs is based on scansion . the number of syllables required is variable due to the number and number of notes . |
| Approach: | They propose a method to generate Mandarin lyrics with a good match between melody and tonal contour. |
| Outcome: | The proposed system outperforms all other systems in lyric-melody fit and uses proxies for quantifying creativity. |
End-to-End Argument Mining as Biaffine Dependency Parsing (2021.eacl-main)
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| Challenge: | Argumentation mining (AM) is a new field of research that uses dependency parsing to analyse arguments. |
| Approach: | They propose a neural end-to-end approach to argument mining based on dependency parsing . their model is biaffine dependency parsed and outperforms the current state-of-the-art . |
| Outcome: | The proposed model outperforms the state-of-the-art in component identification and relation identification. |
It’s All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution (D19-1)
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| Challenge: | Existing attempts to mitigate gender bias rely on operationalisation of gender bias as a projection over a linear subspace. |
| Approach: | They propose to operationalise gender bias as a linear subspace and augmented a corpus to remove bias by swapping all inherently-gendered words in the copy. |
| Outcome: | The proposed approach outperforms projection-based methods at the task of drawing non-biased gender analogies by an average of 19% across both corpora. |
Variable Typing: Assigning Meaning to Variables in Mathematical Text (N18-1)
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| Challenge: | Scientific documents rely on mathematics to communicate ideas and results . textual contexts are strong domainspecific conventions governing how content is presented . |
| Approach: | They introduce a task of assigning one mathematical type to each variable in a sentence . they also introduce 'variable typing' task that focuses on assignment of meaning to variables . |
| Outcome: | The proposed model is the best performing model on an extrinsic task, the authors show . their model is compared to a formula index only containing raw symbols . |
On the Role of Negative Precedent in Legal Outcome Prediction (2023.tacl-1)
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| Challenge: | Legal outcome prediction is an increasingly popular task in AI. |
| Approach: | They propose to use the dynamics of a court process to develop two new models inspired by the dynamics. |
| Outcome: | The proposed model improves positive outcome prediction score to 77.15 F1 and doubles negative outcome prediction performance to 24.01 F1. |
A surprisal–duration trade-off across and within the world’s languages (2021.emnlp-main)
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| Challenge: | Throughout human evolution, countless languages have evolved, each with unique features. |
| Approach: | They analysed a corpus of 600 languages to find strong evidence for a surprisal–duration trade-off between languages and languages. |
| Outcome: | The proposed model shows that phones are produced faster in languages where they are less surprising and vice versa. |
TIARA: A Tool for Annotating Discourse Relations and Sentence Reordering (2020.lrec-1)
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| Challenge: | Existing tools for discourse relations and sentence reordering are difficult to use and clutter the display. |
| Approach: | They propose to use TIARA to simplify the annotation process by offering interactive visualisation, including coloured links, indentation, and dual-view. |
| Outcome: | The proposed tool simplifies the annotation process and offers visualisations including coloured links, indentation, and dual-view. |
Synthetic Textual Features for the Large-Scale Detection of Basic-level Categories in English and Mandarin (2021.emnlp-main)
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| Challenge: | Basic-level categories are an important psycholinguistic concept introduced by Rosch et al. . an at-scale algorithm for the automatic determination of BLC exists, but it operates without Rosch-style semantic features. |
| Approach: | They propose a method for the detection of BLC at scale that makes use of Rosch-style semantic features. |
| Outcome: | The proposed method outperforms the current SoA in detecting basic-level categories with an accuracy of 75.0% in English and 80.7% in Mandarin. |
What About the Precedent: An Information-Theoretic Analysis of Common Law (2021.naacl-main)
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| Challenge: | In common law, the outcome of a new case is determined mostly by precedent cases, rather than by existing statutes. |
| Approach: | They propose to model the argumentation of precedent cases and compare them to a case out-come classification task to determine how the precedent influences the outcome of a new case. |
| Outcome: | The proposed method compared arguments of two longstanding jurisprudential views on the European Court of Human Rights (ECtHR) and the precedent cases. |
On Homophony and Rényi Entropy (2021.emnlp-main)
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| Challenge: | Recent theories of language optimality have tried to justify its prevalence, arguing that homophony enables the reuse of efficient wordforms and is thus beneficial for languages. |
| Approach: | They propose a new information-theoretic quantification of a language’s homophony: the sample Rényi entropy. |
| Outcome: | The proposed method is more nuanced than either Piantadosi et al.'s or Trott and Bergen's results. |
Problem-solving Recognition in Scientific Text (2022.lrec-1)
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| Challenge: | Existing work on problem-solving is not computational, is not adapted to scientific text, or has been narrow in scope. |
| Approach: | They propose an algorithm which can generate virtual instructors from automatically annotated texts. |
| Outcome: | The proposed algorithm can recognise problem-solving expressions in scientific texts with high accuracy. |
Metaphorical Polysemy Detection: Conventional Metaphor Meets Word Sense Disambiguation (2022.coling-1)
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| Challenge: | Linguists distinguish between novel and conventional metaphors, a distinction which the metaphor detection task in NLP does not take into account. |
| Approach: | They propose a method which treats conventional metaphors as a property of word senses in a lexicon and combines metaphor detection with word sense disambiguation to train it. |
| Outcome: | The proposed model outperforms a state-of-the-art model in annotating metaphor in two subsets of WordNet and achieves .78 ROC-AUC score compared to baseline model . |
Semantic Map-based Generation of Navigation Instructions (2024.lrec-main)
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| Challenge: | Existing approaches to navigation instruction generation use a sequence of panorama images as visual input. |
| Approach: | They propose a new approach to navigation instruction generation using semantic maps as visual input and frame it as an image captioning task. |
| Outcome: | The proposed model is based on a dataset of a human vision and language navigation task and human subjects are asked to manually assess the quality of the generated instructions. |
Minimal Pair-Based Evaluation of Code-Switching (2025.acl-long)
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| Challenge: | Existing methods do not have wide language coverage, fail to account for the diverse range of CS phenomena, or do not scale. |
| Approach: | They propose to use minimal pairs of CS to estimate the extent to which large language models (LLMs) use code-switching in the same way as bilinguals. |
| Outcome: | The proposed model assigns higher probability to the naturally occurring CS sentence than to the variant for every language pair. |
Code-Switching and Syntax: A Large-Scale Experiment (2025.findings-acl)
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| Challenge: | Existing theories of code-switching (CS) have been refuted in subsequent investigations. |
| Approach: | They propose to use syntactic information to predict where bilinguals switch languages . they find that syntax alone is sufficient for an automatic system to distinguish between sentences in minimal pairs of CS, to the same degree as bilingual humans. |
| Outcome: | The proposed model can explain why bilinguals switch languages more often than in others, but there is no large-scale, multi-language, cross-phenomena experiment that tests this claim. |