Semantic Tagging at the Sense Level

Alina Andreevskaia, Sabine Bergler

This paper summarizes our research in the area of semantic tagging at the word and sense levels and sets the ground for a new approach to text-level sentiment annotation using a combination of machine learning and linguistically-motivated techniques. We describe a system for sentiment tagging of words and senses based on WordNet glosses and advance the treatment of sentiment as a fuzzy category.

Subjects: 13. Natural Language Processing

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