Predicting the Growth of Morphological Families from Social and Linguistic Factors
Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze
2020年份
13被引次数
4顶会引用
摘要
We present the first study that examines the evolution of morphological families, i.e., sets of morphologically related words such as "trump", "antitrumpism", and "detrumpify", in social media. We introduce the novel task of Morphological Family Expansion Prediction (MFEP) as predicting the increase in the size of a morphological family. We create a ten-year Reddit corpus as a benchmark for MFEP and evaluate a number of baselines on this benchmark. Our experiments demonstrate very good performance on MFEP.
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引用它的顶会 Paper4
- A Graph Auto-encoder Model of Derivational MorphologyValentin Hofmann, Hinrich Schütze, Janet B. PierrehumbertACL 2020 · 被引用 10 次
- Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language ModelLeonie Weissweiler, Valentin Hofmann, Anjali Kantharuban, Anna Cai 等EMNLP 2023 · 被引用 10 次
- DagoBERT: Generating Derivational Morphology with a Pretrained Language ModelValentin Hofmann, Janet B. Pierrehumbert, Hinrich SchützeEMNLP 2020 · 被引用 1 次
- Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex WordsValentin Hofmann, Janet B. Pierrehumbert, Hinrich SchützeACL 2021
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