Techniques & Methods
Part-of-Speech Tagging (POS)
POS tagging assigns grammatical labels—noun (NN), verb (VB), adjective (JJ), determiner (DT), etc.—to each token in a sentence. It is a foundational NLP preprocessing step that enables downstream tasks like parsing, named entity recognition, and information extraction.
Modern neural POS taggers achieve over 97% accuracy on standard benchmarks. Transformers have largely replaced rule-based and CRF-based taggers, learning POS information implicitly during pre-training.
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Related Terms
Techniques & Methods
Dependency Parsing
Analyzing grammatical structure to identify dependency relationships between words in a sentence.
Techniques & Methods
Named Entity Recognition (NER)
Identifying and classifying named entities in text into predefined categories like people and places.
Techniques & Methods
Linguistic Annotation
Adding linguistic metadata—such as POS tags, parse trees, or coreferences—to text for analysis.
Core Concepts
Natural Language Processing (NLP)
Field focused on enabling computer-human interaction through natural language.