Resolving Ambiguity
A Practical Guide to Word Sense Disambiguation in Information Extraction
Words rarely mean just one thing. When extracting information from text, the same word can refer to completely different concepts depending on context—and this ambiguity can derail your entire extraction pipeline. Word sense disambiguation (WSD) is the computational solution to this fundamental problem, yet many practitioners treat it as an afterthought rather than a core component of their systems. This guide bridges the gap between theory and practice, showing you exactly how to identify when disambiguation matters, which techniques work best for different scenarios, and how to integrate them into your information extraction workflows. You'll explore knowledge-based methods that leverage existing linguistic resources, corpus-based approaches that learn from data, and cutting-edge neural techniques that achieve state-of-the-art results. Through practical examples and clear explanations, you'll understand the trade-offs between accuracy, speed, and complexity—and make informed decisions about which methods suit your specific needs. Whether you're building search systems, knowledge graphs, or content analysis tools, mastering word sense disambiguation will significantly improve your results.
Est. Length
207 pages (10 chapters)
Language
English
Publication date
May 1, 2026
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