Inferring descriptive generalisations of formal languages

In the present paper, we introduce a variant of Gold-style learners that is not required to infer precise descriptions of the languages in a class, but that must find descriptive patterns, i.e., optimal generalisations within a class of pattern languages. Our first main result characterises those indexed families of recursive languages that can be inferred by such learners, and we demonstrate that this characterisation shows enlightening connections to Angluin’s corresponding result for exact inference. Using a notion of descriptiveness that is restricted to the natural subclass of terminal-free E-pattern languages, we introduce a generic inference strategy, and our second main result characterises those classes of languages that can be generalised by this strategy. This characterisation demonstrates that there are major classes of languages that can be generalised in our model, but not be inferred by a normal Gold-style learner. Our corresponding technical considerations lead to deep insights of intrinsic interest into combinatorial and algorithmic properties of pattern languages

Inferring descriptive generalisations of formal languages

In the present paper, we introduce a variant of Gold-style learners that is not required to infer precise descriptions of the languages in a class, but that must nd descriptive patterns, i. e., optimal generalisations within a class of pattern languages. Our rst main result characterises those indexed families of recursive languages that can be inferred by such learners, and we demonstrate that this characterisation shows enlightening connections to Angluin's corresponding result for exact inference. Furthermore, this result reveals that our model can be interpreted as an instance of a natural extension of Gold's model of language identi cation in the limit. Using a notion of descriptiveness that is restricted to the natural subclass of terminal-free E-pattern languages, we introduce a generic inference strategy, and our second main result characterises those classes of languages that can be generalised by this strategy. This characterisation demonstrates that there are major classes of languages that can be generalised in our model, but not be inferred by a normal Gold-style learner. Our corresponding technical considerations lead to insights of intrinsic interest into combinatorial and algorithmic properties of pattern languages

Inferring inflection classes with description length

International audienceWe discuss the notion of an inflection class system, a traditional ingredient of the description of inflection systems of nontrivial complexity. We distinguish systems of microclasses, which partition a set of lexemes in classes with identical behavior, and systems of macroclasses, which group lexemes that are similar enough in a few larger classes. On the basis of the intuition that macroclasses should contribute to a concise description of the system, we propose one algorithmic method for inferring macroclasses from raw inflectional paradigms, based on minimisation of the description length of the system under a given strategy of identifying morphological alternations in paradigms. We then exhibit classifications produced by our implementation on French and European Portuguese conjugation data and argue that they constitute an appropriate systematisation of traditional classifications. To arrive at such a convincing systematisation, it was crucial for us to use a local approach to inflection class similarity (based on pairwise comparisons of paradigm cells) rather than a global approach (based on the simultaneous comparison of all cells). We conclude that it is indeed possible to infer inflectional macroclasses objectively

Revisiting Shinohara's algorithm for computing descriptive patterns

A pattern α is a word consisting of constants and variables and it describes the pattern language L(α) of all words that can be obtained by uniformly replacing the variables with constant words. In 1982, Shinohara presents an algorithm that computes a pattern that is descriptive for a finite set S of words, i.e., its pattern language contains S in the closest possible way among all pattern languages. We generalise Shinohara’s algorithm to subclasses of patterns and characterise those subclasses for which it is applicable. Furthermore, within this set of pattern classes, we characterise those for which Shinohara’s algorithm has a polynomial running time (under the assumption P 6= N P). Moreover, we also investigate the complexity of the consistency problem of patterns, i.e., finding a pattern that separates two given finite sets of words

Meaning and individual minds : the case of if

PhD ThesisTraditionally (e.g. Sperber & Wilson 1995, Levinson 2000, Jackendoff 2002, Chomsky 2005a), linguistic expressions have meaning in virtue of having linguistic semantic properties. It is often claimed that linguistic semantics is functionally distinct from but related to the semantics of thought. In particular, linguistic semantics is assumed to be deterministically (necessarily and always) decoded in utterance interpretation and fed, as a basic premise, to pragmatic processing. Linguistic semantics is supposed to aid (i.e. constrain) utterance interpretation insofar as it is at least ‘widely’ shared among speech community members (Carston 2002). However, it has been suggested that linguistic semantics is problematic (e.g. Burton-Roberts 2005, Gibbs 2002, Recanati 2005). This thesis argues that the notion of linguistic semantics, as well as the process of deterministic decoding of such content, is implausible and explores the consequences of this claim for a theory of meaning and utterance interpretation. In the first part, I raise questions about the nature of semantics (externalism or internalism) as well as its structure (atomism, molecularism or holism). In line with the Representational Hypothesis (e.g. Burton-Roberts 2012), I maintain that thought is the only locus of semantics and that meaning is not a property of linguistic expressions, but a cognitive relation between an uttered word and semantics (of thought). I argue that whereas semantic content is holistic, meaning (in the sense of Burton-Roberts) is locally – i.e. contextually – constrained to a degree which, all things being equal, allows for successful communication. I argue that utterance interpretation is a wholly pragmatic inferential process, immediately constrained by a personal (i.e. holistic) inference about the communicative intention of a particular speaker in a particular conversational context. I claim that such a process of utterance interpretation can be implemented in terms of Hintzman’s (1986) multiple-trace theory of memory. In the second part, I illustrate my argument by an analysis of the relation between the word if and Material Implication (MI). I show that the claim (e.g. Grice 1989, Noh 2000) that if semantically encodes MI cannot be maintained. I argue that the application of MI has to be pragmatically determined and, therefore, when MI applies, it does so at the level of (holistic) thought – not at the (anyway problematic) linguistic semantic level. I explain the interpretation of conditionals in terms of Horton & Gerrig’s (2005) extension of a multiple-trace theory of memory into the study of common ground. I also discuss the implications of a wholly pragmatic account of utterance interpretation for the distinction between explicit and implicit communication.PhD bursary I received from the School of English Literature, Language and Linguistics and for conference grants offered by the School and by the Centre for Research in Linguistics and Language Sciences

An Ontology Design Pattern to Define Explanations

In this paper, we propose an ontology design pattern for the concept of “explanation”. The motivation behind this work comes from our research, which focuses on automatically identifying explanations for data patterns. If we want to produce explanations from data agnostically from the application domain, we first need a formal definition of what an explanation is, i.e. which are its components, their roles or their interactions. We analysed and surveyed works from the disciplines grouped under the name of Cognitive Sciences, with the aim of identifying differences and commonalities in the way their researchers intend the concept of explanation. We then produced not only an ontology design pattern to model it, but also the instantiations of this in each of the analysed disciplines. Besides those contributions, the paper presents how the proposed ontology design pattern can be used to analyse the validity of the explanations produced by our, and other, frameworks

Local Patterns

A pattern is a word consisting of constants from an alphabet Sigma of terminal symbols and variables from a set X. Given a pattern alpha, the decision-problem whether a given word w may be obtained by substituting the variables in alpha for words over Sigma is called the matching problem. While this problem is, in general, NP-complete, several classes of patterns for which it can be efficiently solved are already known. We present two new classes of patterns, called k-local, and strongly-nested, and show that the respective matching problems, as well as membership can be solved efficiently for any fixed k