2025 NAACL NAACL 2025

An evaluation of Named Entity Recognition tools for detecting person names in philosophical text

Abstract

AbstractFor philosophers, mentions of the names of other philosophers and scientists are an important indicator of relevance and influence. However, they don’t always come in neat citations, especially in older works. We evaluate various approaches to named entity recognition for person names in 20th century, English-language philosophical texts. We use part of a digitized corpus of the works of W.V. Quine, manually annotated for person names, to compare the performance of several systems: the rule-based edhiphy, spaCy’s CNN-based system, FLAIR’s BiLSTM-based system, and SpanBERT, ERNIE-v2 and ModernBERT’s transformer-based approaches. We also experiment with enhancing the smaller models with domain-specific embedding vectors. We find that both spaCy and FLAIR outperform transformer-based models, perhaps due to the small dataset sizes involved.

🌉 Interdisciplinary Bridge — Deep Learning and Interdisciplinary and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio