| { |
| "paper_id": "J06-1008", |
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| { |
| "text": "view that \"a linguistic system is inherently probabilistic in nature.\" Halliday sees no distinction between corpus linguistics and theoretical linguistics, adapting the principle that \"frequency in text instantiates probability in the system.\" But he criticizes early MT work that gets involved with \"the counting of orthographic words in isolation\" and believes that corpora should be as useful for grammarians as they have been for lexicologists. But \"the grammar is much harder to get at\" and \"the main limitation on the use of corpuses [sic] for probabilistic grammar is the familiar catch that what is easy to recognize is usually too trivial to be worth recognizing.\" So the joint work with James referred to above has to use a number of complex heuristics (in a way that will be familiar to computational linguists) to extract the desired grammatical information from the corpus. Recent developments in wide-coverage parsing and the exploitation of huge corpora should mean that the boundaries are moving very fast in this area, if there are grammarians out there willing to have a go . . .", |
| "cite_spans": [ |
| { |
| "start": 540, |
| "end": 545, |
| "text": "[sic]", |
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| "text": "There are a number of intriguing ideas and comments to be found in the papers. For instance, there is the hypothesis (with some empirical support) that binary choice systems in languages tend to have either equal probabilities for the two options (\"equiprobable\") or with probabilities around 0.1 and 0.9 (\"skew\"). Interestingly, the latter case corresponds to where the information-theoretic entropy is about 0.5 (which is also about the figure for the entropy for English in terms of characters, as calculated by Shannon and Weaver). Also there are some interesting speculations about how language changes that manifest themselves initially through probabilities might eventually lead to changes in the underlying systems themselves.", |
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| "text": "Although I don't think that computational linguists will find any ideas in this book that will directly inspire computational implementation, I found it an interesting read that gave me a number of insights into the history of linguistics and into how Halliday's thinking relates to computational issues. Halliday's writing is erudite and clear, but it is also quite dense and uses terminology that has to be mastered. The examples and grammar fragments help a lot to make the ideas precise, but I'd have liked there to be more of these.", |
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| "back_matter": [], |
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