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- W3034429229 abstract "One of the missing pieces before image schemas can be used in conceptual blending and artificial intelligence is a method to automatically identify image schemas in natural language. In order to investigate this problem, the PATHfollowing family introduced in Chapter 3 will be empirically investigated by using a natural language corpus to detect existing members of the family and detect possible additional candidates. The experiment relies on a method of syntactic pattern matching using words strongly associated with movement and processes. The experiment includes four different languages to strengthen the idea that PATH-following in abstract domains (here finance) is not only found in one language but universal as assumed through their embodied manifestation. The experiment found that approximately 1/3 of extracted words could be image-schematic and could not only provide linguistic support for the members of the PATH family but also provide additional candidates." @default.
- W3034429229 created "2020-06-19" @default.
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- W3034429229 date "2020-01-01" @default.
- W3034429229 modified "2023-09-27" @default.
- W3034429229 title "Identifying Image Schemas: Towards Automatic Image Schema Extraction1" @default.
- W3034429229 doi "https://doi.org/10.1007/978-3-030-47329-7_8" @default.
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