AI language models need more than statistical analysis to truly understand language. They need to grasp the meaning of word pairs and identify relationships like antonyms, where words have opposite meanings. This requires a deeper understanding than simply recognizing co-occurrence. A thesaurus-like resource and human-validated tests for semantic relationships (like identifying antonyms or confirming sentiments are opposite) are crucial for development. Just as foreigners struggle with idioms, language models need to learn these nuanced expressions and relationships to truly grasp logic and meaning.