jurafsky&martin_3rdEd_17 (1).pdf

The price of bananas increased arg2 5 2218 arg1 the

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The price of bananas] increased [ Arg2 5%]. (22.18) [ Arg1 The price of bananas] rose [ Arg2 5%]. (22.19) There has been a [ Arg2 5%] rise [ Arg1 in the price of bananas]. Note that the second example uses the different verb rise , and the third example uses the noun rather than the verb rise . We’d like a system to recognize that the
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22.5 F RAME N ET 383 price of bananas is what went up, and that 5% is the amount it went up, no matter whether the 5% appears as the object of the verb increased or as a nominal modifier of the noun rise . The FrameNet project is another semantic-role-labeling project that attempts FrameNet to address just these kinds of problems ( Baker et al. 1998 , Fillmore et al. 2003 , Fillmore and Baker 2009 , Ruppenhofer et al. 2010 ). Whereas roles in the PropBank project are specific to an individual verb, roles in the FrameNet project are specific to a frame . What is a frame? Consider the following set of words: reservation, flight, travel, buy, price, cost, fare, rates, meal, plane There are many individual lexical relations of hyponymy, synonymy, and so on between many of the words in this list. The resulting set of relations does not, however, add up to a complete account of how these words are related. They are clearly all defined with respect to a coherent chunk of common-sense background information concerning air travel. We call the holistic background knowledge that unites these words a frame (Fill- frame more, 1985) . The idea that groups of words are defined with respect to some back- ground information is widespread in artificial intelligence and cognitive science, where besides frame we see related works like a model (Johnson-Laird, 1983) , or model even script (Schank and Abelson, 1977) . script A frame in FrameNet is a background knowledge structure that defines a set of frame-specific semantic roles, called frame elements , and includes a set of predi- frame elements cates that use these roles. Each word evokes a frame and profiles some aspect of the frame and its elements. The FrameNet dataset includes a set of frames and frame elements, the lexical units associated with each frame, and a set of labeled example sentences. For example, the change position on a scale frame is defined as follows: This frame consists of words that indicate the change of an Item’s posi- tion on a scale (the Attribute) from a starting point (Initial value) to an end point (Final value). Some of the semantic roles (frame elements) in the frame are defined as in Fig. 22.3 . Note that these are separated into core roles , which are frame specific, and Core roles non-core roles , which are more like the Arg-M arguments in PropBank, expressed Non-core roles more general properties of time, location, and so on. Here are some example sentences: (22.20) [ I TEM Oil] rose [ A TTRIBUTE in price] [ D IFFERENCE by 2%].
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