Polymeaning Words: Word Character Division, Frequent Binding and Inter-sentential Congruency

What is it about?

From 2015 to now, it has been formulated by Cai the semantic/syntactic/ episodic(words/grammar/episodic) model of native language, corresponding to the declarative remote memory, procedural memory and declarative immediate/recent episodic memory, respectively, with the N400-related episodic congruency of word-meaning necessary to determine one congruent meaning for some polymeaning words in sentence and paragraph. Herein, it is aimed to apply this model to machine translation, as follows: (a) From the words/grammar/episodic components, it is derived three principles for machine translation, as word/phrase dictionary, procedural grammar input/output, and episodic congruency of polymeaning-words, respectively. (b) It is classified the episodic congruency of word-meaning in sentences and paragraphs into three types as stepwise congruent comprehension by gamma increment; frequent word binding from phrases, idioms, etc; and inter-sentential association of polymeaning-word in a simple sentence with other sentences in a paragraph. (c) For stepwise congruent comprehension, it is classified the pronouns/nouns into the categories of behaviorally alive human/animal and naturally changing matter, and further classified such nouns/pronouns into the zoological/organizational/ range/relation/logic/physical/categorical characters, and the sententially stepwise following verbs into affective/behavioral/range/relation/ logic/characteristic/ changing characters, the adjectives/adverbs into affective/behavioral/ range/ relation/logic/characteristic/changing/spatial/temporal characters, restricting their meanings by congruency of word category of characters in sentence. (d) For frequent word bindings, it is suggested to make a databank to collect and use them. (e) Finally, it is suggested to further adopt statistical translation by paragraph to determine the polymeaning-word in simple sentences. In conclusion, it is feasible to progress significantly with such applications to machine translation.

Featured Image

Photo by Brett Jordan on Unsplash

Photo by Brett Jordan on Unsplash

Why is it important?

(a) It is a comprehensive summarization on how the polymeaning words in sentence and paragraph are understood, as stepwise congruent comprehension, frequent word binding, and inter-sentential congruency. (b) it is classified the pronouns/nouns into the categories of behaviorally alive human/animal and naturally changing matter, and further classified such nouns/pronouns into the zoological/organizational/ range/relation/logic/physical/categorical characters, and the sententially stepwise following verbs into affective/behavioral/range/relation/ logic/characteristic/ changing characters, the adjectives/adverbs into affective/behavioral/ range/ relation/logic/characteristic/changing/spatial/temporal characters, restricting their meanings by congruency of word category of characters in sentence.

Perspectives