Papers by Susanna Rücker
Evaluating Design Decisions for Dual Encoder-based Entity Disambiguation (2025.acl-long)
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| Challenge: | Entity disambiguation (ED) is the task of linking mentions in text to corresponding entries in a knowledge base. |
| Approach: | They propose a document-level Dual Encoder model that embeds mentions and label candidates in a shared embedding space and applies a similarity metric to predict the correct label. |
| Outcome: | The proposed model improves the disambiguation of ambiguous mentions of entities in text to their respective KB entries. |
CleanCoNLL: A Nearly Noise-Free Named Entity Recognition Dataset (2023.emnlp-main)
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| Challenge: | Existing models achieve F1-scores comparable to or exceed noise level in CoNLL-03 . current models have significant annotation errors, incompleteness, and inconsistencies in the data . |
| Approach: | They propose to add a layer of entity linking annotation to the CoNLL-03 corpus to correct 7.0% of all labels. |
| Outcome: | The proposed approach corrects 7.0% of all labels in the English CoNLL-03 dataset. |
Learning and Evaluating Emotion Lexicons for 91 Languages (2020.acl-main)
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| Challenge: | Emotion lexicons describe the affective meaning of words but are limited in coverage for most languages. |
| Approach: | They propose a method for creating arbitrarily large emotion lexicons for any target language. |
| Outcome: | The proposed method exceeds human reliability for some languages and variables. |