Human language understanding: which strategies do people naturally use to overcome ambiguity and variability in everyday natural language?

Introduction / Context:
Natural language is ambiguous, context-sensitive, and shaped by shared experiences. Humans resolve ambiguity by leveraging context and familiarity rather than relying only on formal symbolic structures. Recognizing these strategies clarifies why purely rule-based language processing can struggle without pragmatic knowledge.

Given Data / Assumptions:

• The question contrasts human strategies with formal AI constructs.
• We focus on context and familiarity as core human tools.
• Frames (a) are an AI representation technique, not a human cognitive description per se.

Concept / Approach:
People disambiguate words by considering the surrounding discourse, situation, intent, and world knowledge (context). They also map new utterances to familiar scenarios (schemas), enabling rapid inference. While AI adopts frame-like structures, everyday human understanding operates flexibly through context and analogies rather than explicit attribute-grouping schemas.

Step-by-Step Solution:

Verification / Alternative check:
Linguistics and psycholinguistics emphasize context and schema activation in comprehension, supporting the selected strategies as the most naturalistic for humans.

Why Other Options Are Wrong:

• (a) Frames are useful in AI knowledge representation but are not the intuitive descriptor of human strategy.
• (b) or (c) alone omit the complementary role of familiarity.
• (e) Incorrect; humans clearly use context and familiarity.

Common Pitfalls:
Assuming a single mechanism explains comprehension; neglecting the interplay of context, world knowledge, and experience.

Final Answer:
both (b) and (c)