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Ubiquity’s proposed new parser design is based on a principles and parameters philosophy: we can build an underlying universal parser and, for each individual language, we simply set some “parameters” to tell the parser how to act. As we consider the design’s pros and cons, it’s important to reflect back on the linguistic data and see if this architecture can adequately handle the range of linguistic data attested in our languages.

Today I’ll examine highlight some disparate typological data to help us understand these questions: where’s the verb? and what does the verb look like? (more…)

A week or two ago while visiting California, Jono and I had a productive charrette, resulting in a new architecture proposal for the Ubiquity parser, as laid out in Ubiquity Parser: The Next Generation. The new architecture is designed to support (1) the use of overlord verbs, (2) writing verbs by semantic roles, and (3) better suggestions for verb-final languages and other argument-first contexts. I’m happy to say that I’ve spent some time putting a proof-of-concept together.

I’ve implemented the basic algorithm of this parser for left-branching languages (like English) and also implemented some fake English verbs, noun types, and semantic roles. This demo should give you a basic sense of how this parser will attempt to identify different types of arguments and check their noun types even without clearly knowing the verb. This should make the suggestion ranking much smarter, particularly for verb-final contexts. (For a good example, try from Tokyo to San Francisco.)

➔ Check out the Ubiquity next-gen parser demo

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