📄 A Comparative Study of English and Chinese Synonym Pairs : An Approach based on The Module-Attribute Representation of Verbal Semantics

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Summary

The authors test whether MARVS (Module-Attribute Representation of Verbal Semantics), a theory developed on Chinese data, carries over to other languages. To do so, they compare the English near-synonyms "put" and "set" with the Mandarin placement verbs bai3 and fang4. The data come from the two-million-word sampler of the British National Corpus (BNC). Each verb's usage examples are classified by syntactic function, argument structure type, aspect, and sentence type. The authors then look for cases of complementary distribution, which point to a semantic difference. The English pair turns out to differ on features other than those that separate the Chinese pair. With "put", the location must be a bounded, enclosed space. With "set", by contrast, what matters is that the theme has a definite position. In abstract uses, "set" takes a proposition role, so the authors treat it as a separate sense. The study shows that near-synonyms are a finer tool for uncovering lexical semantics than the verb classes of Levin (1993). It also shows that such distinctions should rest on corpus data rather than on the researcher's intuition alone.

Key points

• Data: 100 randomly selected examples each of "put" and "set" from the two-million-word BNC sampler. The sense under study is moving an object to a certain place, defined roughly according to WordNet.
• The Chinese pair: in MARVS, bai3 differs from fang4 by the role attribute [design] on the location role. The differences this produces in Mandarin (progressive, resultative object, orientational adjunct) do not appear in English.
• Concrete contexts: "put" has the roles <Agent, Theme, Location>, with the location attribute [bounded]. In 7 of the 9 concrete cases, the theme is placed inside something. "Set" has the same roles, but the attribute [positioned] belongs to the theme.
• Abstract contexts: with "put", the [bounded] attribute is kept in metaphorical uses. "Set" covers temporal locations, and in causative-resultative constructions it has the structure <Agent, Theme, Proposition>, so MARVS treats it as a separate sense.
• Methodological conclusion: analyzing pairs of near-synonyms on corpus data is more precise than analyzing diathesis alternations in large verb classes.