Representing Meaning with a Combination of Logical and Distributional Models

Understand

NLP tasks differ in the semantic information they require, and at this time no single se- mantic representation fulfills all requirements.

• Logic-based representations characterize sentence structure, but do not capture the graded aspect of meaning.
• Distributional models give graded similarity ratings for words and phrases, but do not capture sentence structure in the same detail as logic-based approaches.
• So it has been argued that the two are complementary.