this model hypothesize that context determines which meaning will be accessed (the literal or the metaphorical one) and the metaphorical meaning is directly accessed when relevant to a given context.

The context-dependent model

The serial/hierarchical model of metaphor comprehension hypothesizes that individuals activate the metaphorical meaning of a sentence after having first activated its literal meaning.

Serial/Hierarchical Model of Metaphor Comprehension

The parallel/direct processing model hypothesizes that literal and metaphorical meanings are processed simultaneously during comprehension, since the metaphorical meaning is accessed directly without first passing through a literal interpretation stage.

Parallel/Direct Processing Model of Metaphor Comprehension

Three general categories of hypotheses have been proposed to explain the underlying cognitive mechanisms of metaphor comprehension:

1. The serial/hierarchical model
2. The parallel/direct processing model
3. The context-dependent model

DePaul University

Google

The comprehension of metaphors involves the ability to activate a broader, more flexible set of semantic associations in order to integrate the meanings of the weakly related parts of the metaphor into a meaningful linguistic expression.

Metaphor comprehension

Right hemisphere is thought to be able to comprehend words with multiple meanings and takes on the critical role for at least one important component of metaphor processing. Metaphors presented to the left visual field/right hemisphere are comprehended more accurate and faster than metaphor words presented to the right visual field/left hemisphere. This finding is consistent with both familiar and novel metaphors processing. 

Hemispheric differences

Guided by conceptual metaphor theory, this paper proposes to control the generation process by encoding conceptual mappings between cognitive domains to generate meaningful metaphoric expressions.

Metaphor Generation with Conceptual Mappings

This paper proposes metrics to evaluate the quality of automatically generated metaphors not restricted to similes. The metrics are metaphoricity, novelty, comprehensibility, and overall evaluation.

Evaluation Metrics for Automatically Generated Metaphorical Expressions

Metaphorical structure is often easier to expose by starting from source-domain language rather than from target-domain lexemes. Many target domains cannot be thoroughly investigated by searching a corpus for collocates of target lexemes, because not all target language occurs near source-domain triggers. How readily metaphorical structure can be exposed therefore depends on the relationship between source-domain language and the structural character of the target domain. Instead of relying on pre-specified semantic fields, corpus collocation patterns are used to gather candidate metaphor triggers.

Finding metaphorical triggers through source (not target) domain lexicalization patterns

Literal-to-metaphorical paraphrase generation masks a token in a literal sentence and uses a metaphor-focused language model to replace it with language intended to make the sentence metaphorical. The replacement can involve verbs, nouns, or adjectives rather than being limited to verbs.

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