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Improvements to a Resource Analysis for Hume Hans-Wolfgang Loidl1 and Ste en Jost2 1 School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh EH14 4AS, Scotland, UK; Email:
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We apply our model to an existing (but not quite so mature) natural language implementation of the natural language processing system LIME, where most (around 70%) of the words and phrases have some natural language content. We find that, contrary to expectations based on other previous work, the LIME engine, though well-suited to the task, has significant resource bounds in its natural language input, that cannot be inferred statically. Furthermore, an alternative to Hume for a natural language interpreter of the type LIME uses amortized costs to infer resource bounds. This paper reports an extension of our resource analysis to support the analysis of other real-world languages. Keywords: Hume Hans-Wolfgang Lidl, resource analysis, amortized costs, natural language interpreters. 1. Introduction This is an overview of our resource analysis for Hume (hereafter, h Hume). Our resource analysis for Hume is based on the concept of amortized costs. The amortized cost approach differs from the common resource-based inference engine model due to the fact that it allows us to generate an inference model for a resource-free model. The resource analysis for Hume gives rise to many new concepts and a good understanding of the underlying logic of our framework. Many other resources have also been studied using the amortized costs approach. To summarize, Hume follows from a number of premises to construct the resource analysis that supports our resource analysis for h Hume. This premise is listed in the following table. Note that our resource analysis will also be applicable to other natural language languages. Table 1. Resource-generic amortized cost premises of the resource analysis for h Hume. The natural language input language h Hume is composed of words and phrases. Words and phrases have no well-defined grammatical meaning, but they have a syntactic meaning. Words have been defined as having the semantic value of their associated prefixes (e.g., “the”, “of”, “the” [of], “a”, “a”, “a”, “a”, “a” []) and suffixes (e.g., “the”, “of”, “the”, “a”, “of”, “of”, “a”). Phrases are specified using prepositions. Some phrases of the natural language input language h Hume have a syntactic meaning: i.e.

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