Title: Learning Auxiliary Fronting with Grammatical Inference
Abstract: Learning Auxiliary Fronting with Grammatical Inference Alexander Clark ([email protected]) Department of Computer Science Royal Holloway University of London Egham, Surrey TW20, UK R´ emi Eyraud ([email protected]) EURISE 23, rue du Docteur Paul Michelon 42023 Saint- Etienne Cedex 2, France Abstract We present a simple context-free grammatical inference algorithm, and prove that it is capable of learning an interesting subclass of context-free languages. We also demonstrate that an implementation of this algorithm is capable of learning auxiliary fronting in polar inter- rogatives (AFIPI) in English. This has been one of the most important test cases in language acquisition over the last few decades. We demonstrate that learning can proceed even in the complete absence of examples of particular constructions, and thus that debates about the frequency of occurrence of such constructions are ir- relevant. We discuss the implications of this on the type of innate learning biases that must be hypothesized to explain first language acquisition. about language; no knowledge of X-bar schemas, no hid- den sources of information to reveal the structure. It operates purely on unannotated strings of raw text. Ob- viously, as all learning algorithms do, it has an implicit learning bias. This very simple algorithm has a particu- larly clear bias, with a simple mathematical description, that allows a remarkably simple characterisation of the set of languages that it can learn. This algorithm does not use a statistical learning paradigm that has to be tested on large quantities of data. Rather it uses a sym- bolic learning paradigm, that works efficiently with very small quantities of data, while being very sensitive to noise. We discuss this choice in some depth below. For reasons that were first pointed out by Chomsky (Chomsky, 1975, pages 129–137), algorithms of this type are not capable of learning all of natural language. It turns out, however, that algorithms based on this ap- proach are sufficiently strong to learn some key prop- erties of language, such as the correct rule for forming polar questions. In the next section we shall describe the dispute briefly; in the subsequent sections we will describe the al- gorithm we use, and the experiments we have performed. Introduction For some years, a particular set of examples has been used to provide support for nativist theories of first lan- guage acquisition (FLA). These examples, which hinge around auxiliary inversion in the formation of questions in English, have been considered to provide a strong ar- gument in favour of the nativist claim: that FLA pro- ceeds primarily through innately specified domain spe- cific mechanisms or knowledge, rather than through the operation of general-purpose cognitive mechanisms. A key point of empirical debate is the frequency of occur- rence of the forms in question. If these are vanishingly rare, or non-existent in the primary linguistic data, and yet children acquire the construction in question, then the hypothesis that they have innate knowledge would be supported. But this rests on the assumption that examples of that specific construction are necessary for learning to proceed. In this paper we show that this as- sumption is false: that this particular construction can be learned without the learner being exposed to any examples of that particular type. Our demonstration is primarily mathematical/computational: we present a simple experiment that demonstrates the applicability of this approach to this particular problem neatly, but the data we use is not intended to be a realistic representa- tion of the primary linguistic data, nor is the particular algorithm we use suitable for large scale grammar induc- tion. We present a general purpose context-free grammat- ical algorithm that is provably correct under a certain learning criterion. This algorithm incorporates no do- main specific knowledge: it has no specific information The Dispute We will present the dispute in traditional terms, though later we shall analyse some of the assumptions implicit in this description. In English, polar interrogatives (yes/no questions) are formed by fronting an auxiliary, and adding a dummy auxiliary “do” if the main verb is not an auxiliary. For example, Example 1a The man is hungry. Example 1b Is the man hungry? When the subject NP has a relative clause that also contains an auxiliary, the auxiliary that is moved is not the auxiliary in the relative clause, but the one in the main (matrix) clause. Example 2a The man who is eating is hungry. Example 2b Is the man who is eating hungry? An alternative rule would be to move the first occur- ring auxiliary, i.e. the one in the relative clause, which would produce the form
Publication Year: 2006
Publication Date: 2006-01-01
Language: en
Type: article
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Cited By Count: 11
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