On throwing out the baby with the bathwater: A reply to Black and Wilensky's evaluation of story grammars

A number of criticisms of a recent paper byare made. (1) In attempting to assess the observational adequacy of story grammars, they state that a context-free grammar cannot handle discontinuous elements; however, they do not show that such elements occur in the domain to which the grammars apply. Further, they do not present adequate evidence for their claim that there are acceptable stories not accounted for by existing grammars and that the grammars will accept nonstories such as procedures. (2) They state that it has been proven that under natural conditions children cannot learn transformational grammars, which is a misrepresentation of the learnability proofs which have been offered. (3) Most important, they take an unduly narrow approach to story understanding by claiming that people only understand story content and do not have knowledge of story structure which is useful in comprehension or memory. Counterevidence from the literature is cited which indicates that such knowledge is both useful and used, and a number of methods for assessing the psychological adequacy of structural models are discussed.     

The Role of Simple Semantics in the Process of Artificial Grammar Learning

This study investigated the effect of semantic information on artificial grammar learning (AGL). Recursive grammars of different complexity levels (regular language, mirror language, copy language) were investigated in a series of AGL experiments. In the with-semantics condition, participants acquired semantic information prior to the AGL experiment; in the without-semantics control condition, participants did not receive semantic information. It was hypothesized that semantics would generally facilitate grammar acquisition and that the learning benefit in the with-semantics conditions would increase with increasing grammar complexity. Experiment 1 showed learning effects for all grammars but no performance difference between conditions. Experiment 2 replicated the absence of a semantic benefit for all grammars even though semantic information was more prominent during grammar acquisition as compared to Experiment 1. Thus, we did not find evidence for the idea that semantics facilitates grammar acquisition, which seems to support the view of an independent syntactic processing component.     

Categorial grammars determined from linguistic data by unification

We provide an algorithm for determining a categorial grammar from linguistic data that essentially uses unification of type-schemes assigned to atoms. The algorithm presented here extends an earlier one restricted to rigid categorial grammars, introduced in [4] and [5], by admitting non-rigid outputs. The key innovation is the notion of an optimal unifier, a natural generalization of that of a most general unifier.     

Varieties of crossing dependencies: structure dependence and mild context sensitivity

Four different kinds of grammars that can define crossing dependencies in human language are compared here: (i) context sensitive rewrite grammars with rules that depend on context, (ii) matching grammars with constraints that filter the generative structure of the language, (iii) copying grammars which can copy structures of unbounded size, and (iv) generating grammars in which crossing dependencies are generated from a finite lexical basis. Context sensitive rewrite grammars are syntactically, semantically and computationally unattractive. Generating grammars have a collection of nice properties that ensure they define only “mildly context sensitive” languages, and Joshi has proposed that human languages have those properties too. But for certain distinctive kinds of crossing dependencies in human languages, copying or matching analyses predominate. Some results relevant to the viability of mildly context sensitive analyses and some open questions are reviewed.     

Perceptual constraints and the learnability of simple grammars

Cognitive processes are often attributed to statistical or symbolic general-purpose mechanisms. Here we show that some spontaneous generalizations are driven by specialized, highly constrained symbolic operations. We explore how two types of artificial grammars are acquired, one based on repetitions and the other on characteristic relations between tones ("ordinal" grammars). Whereas participants readily acquire repetition-based grammars, displaying early electrophysiological responses to grammar violations, they perform poorly with ordinal grammars, displaying no such electrophysiological responses. This outcome is problematic for both general symbolic and statistical models, which predict that both types of grammars should be processed equally easily. This suggests that some simple grammars are acquired using perceptual primitives rather than general-purpose mechanisms; such primitives may be elements of a "toolbox" of specialized computational heuristics, which may ultimately allow constructing a psychological theory of symbol manipulation.     

On Learnability of Restricted Classes of Categorial Grammars

In this paper we present learning algorithms for classes of categorial grammars restricted by negative constraints. We modify learning functions of Kanazawa [10] and apply them to these classes of grammars. We also prove the learnability of intersection of the class of minimal grammars with the class of k-valued grammars. Presented by Wojciech Buszkowski     

Processing local transitions versus long-distance syntactic hierarchies

A recent study by Fitch and Hauser reported that finite-state grammars can be learned by non-human primates, whereas phrase-structure grammars cannot. Humans, by contrast, learn both grammars easily. This species difference is taken as the critical juncture in the evolution of the human language faculty. Given the far-reaching relevance of this conclusion, the question arises as to whether the distinction between these two types of grammars finds its reflection in different neural systems within the human brain.     

Parsing Pregroup Grammars and Lambek Calculus Using Partial Composition

The paper presents a way to transform pregroup grammars into contextfree grammars using functional composition. The same technique can also be used for the proof-nets of multiplicative cyclic linear logic and for Lambek calculus allowing empty premises.     

Applying a logical interpretation of semantic nets and graph grammars to natural language parsing and understanding

In this paper a logical interpretation of semantic nets and graph grammars is proposed for modelling natural language understanding and creating language understanding computer systems. An example of parsing a Finnish question by graph grammars and inferring the answer to it by a semantic net representation is provided.     

Gaifman's theorem on categorial grammars revisited

The equivalence of (classical) categorial grammars and context-free grammars, proved by Gaifman [4], is a very basic result of the theory of formal grammars (an essentially equivalent result is known as the Greibach normal form theorem [1], [14]). We analyse the contents of Gaifman's theorem within the framework of structure and type transformations. We give a new proof of this theorem which relies on the algebra of phrase structures and exhibit a possibility to justify the key construction used in Gaifman's proof by means of the Lambek calculus of syntactic types [15].     

A re-evaluation of story grammars

Black and Wilensky (1979) have made serious methodological errors in analyzing story grammars, and in the process they have committed additional errors in applying formal language theory. Our arguments involve clarifying certain aspects of knowledge representation crucial to a proper treatment of story understanding. Particular criticisms focus on the following shortcomings of their presentation: 1) an erroneous statement from formal language theory, 2) misapplication of formal language theory to story grammars, 3) unsubstantiated and doubtful analogies with English grammar, 4) various non sequiturs concerning the generation of non-stories, 5) a false claim based on the artificial distinction between syntax and semantics, and 6) misinterpretation of the role of story grammars in story understanding. We conclude by suggesting appropriate criteria for the evaluation of story grammars.     

Extending Free Pregroups with Lower Bounds

In this paper, we propose an extension of free pregroups with lower bounds on sets of pregroup elements. Pregroup grammars based on such pregroups provide a kind of an algebraic counterpart to universal quantification over type-variables. In particular, we show how our pregroup extensions can be used for pregroup grammars expressing natural-language coordination and extraction.     

Intentional control based on familiarity in artificial grammar learning

It is commonly held that implicit learning is based largely on familiarity. It is also commonly held that familiarity is not affected by intentions. It follows that people should not be able to use familiarity to distinguish strings from two different implicitly learned grammars. In two experiments, subjects were trained on two grammars and then asked to endorse strings from only one of the grammars. Subjects also rated how familiar each string felt and reported whether or not they used familiarity to make their grammaticality judgment. We found subjects could endorse the strings of just one grammar and ignore the strings from the other. Importantly, when subjects said they were using familiarity, the rated familiarity for test strings consistent with their chosen grammar was greater than that for strings from the other grammar. Familiarity, subjectively defined, is sensitive to intentions and can play a key role in strategic control.     

A direct proof of the equivalence of free categorial grammars and simple phrase structure grammars

In [2], Bar-Hillel, Gaifman, and Shamir prove that the simple phrase structure grammars (SPGs) defined by Chomsky are equivalent in a certain sense to Bar-Hillel's bidirectional categorial grammars (BCGs). On the other hand, Cohen [3] proves the equivalence of the latter ones to what the calls free categorial grammars (FCGs). They are closely related to Lambek's syntactic calculus which, in turn, is based on the idea due to Ajdukiewicz [1]. For the reasons which will be discussed in the last section, Cohen's proof seems to be at least incomplete. This paper yields a direct proof of the equivalence ofFCGs andSPGs.Allatum est die S Marlii 1976     

A Bayesian Model of Biases in Artificial Language Learning: The Case of a Word‐Order Universal

In this article, we develop a hierarchical Bayesian model of learning in a general type of artificial language‐learning experiment in which learners are exposed to a mixture of grammars representing the variation present in real learners’ input, particularly at times of language change. The modeling goal is to formalize and quantify hypothesized learning biases. The test case is an experiment ( Culbertson, Smolensky, & Legendre, 2012 ) targeting the learning of word‐order patterns in the nominal domain. The model identifies internal biases of the experimental participants, providing evidence that learners impose (possibly arbitrary) properties on the grammars they learn, potentially resulting in the cross‐linguistic regularities known as typological universals. Learners exposed to mixtures of artificial grammars tended to shift those mixtures in certain ways rather than others; the model reveals how learners’ inferences are systematically affected by specific prior biases. These biases are in line with a typological generalization—Greenberg's Universal 18—which bans a particular word‐order pattern relating nouns, adjectives, and numerals.     

Poverty of the stimulus revisited

A central goal of modern generative grammar has been to discover invariant properties of human languages that reflect "the innate schematism of mind that is applied to the data of experience" and that "might reasonably be attributed to the organism itself as its contribution to the task of the acquisition of knowledge" (Chomsky, 1971). Candidates for such invariances include the structure dependence of grammatical rules, and in particular, certain constraints on question formation. Various "poverty of stimulus" (POS) arguments suggest that these invariances reflect an innate human endowment, as opposed to common experience: Such experience warrants selection of the grammars acquired only if humans assume, a priori, that selectable grammars respect substantive constraints. Recently, several researchers have tried to rebut these POS arguments. In response, we illustrate why POS arguments remain an important source of support for appeal to a priori structure-dependent constraints on the grammars that humans naturally acquire.     

Commutation-Augmented Pregroup Grammars and Mildly Context-Sensitive Languages

The paper presents a generalization of pregroup, by which a freely-generated pregroup is augmented with a finite set of commuting inequations, allowing limited commutativity and cancelability. It is shown that grammars based on the commutation-augmented pregroups generate mildly context-sensitive languages. A version of Lambek’s switching lemma is established for these pregroups. Polynomial parsability and semilinearity are shown for languages generated by these grammars. Special Issue Categorial Grammars and Pregroups Edited by Wojciech Buszkowski and Anne Preller     

The analytic and the synthetic as linguistic topics

The Analytic/Synthetic distinction did not originate in Kant, but in Port-Royal's logical theory. The key for the doctrine is the explicite recognition of two different kinds of relative clauses, e.g. explicative and determinative. In the middle eighteenth century the distinction becomes a topic within the grammars. Although we can find by grammarians different criteria for the distinction, these criteria (for which we can find medieval sources) are for the main predictable from the original theory of ideas, which was presented in Port-Royal's logical writings. The topic of the two relative clauses (somewhat broader than the analytic/synthetic distinction) can be used to give empirical criteria for analyticity and also for revisiting Quine's criticism of the topic. Analyticity yet appears as a master piece of classical linguistic philosophy and not as being the empty dogma of modern empiricism.     

Are the grammatical sentences of a language a recursive set?

Many believe that the grammatical sentences of a natural language are a recursive set. In this paper I argue that the commonly adduced grounds for this belief are inconclusive, if not simply unsound. Neither the native speaker's ability to classify sentences nor his ability to comprehend them requires it. Nor is there at present any reason to think that decidability has any bearing on first-language acquisition. I conclude that there are at present no compelling theoretical grounds for requiring that transformational grammars enumerate only recursive sets. Hence, the fact that proposed transformational grammars do not satisfy this requirement does not, as some have claimed, represent a shortcoming in current theory.     

Using ecphoric confidence ratings to discriminate seen from unseen faces: The effects of retention interval and distinctiveness

Theories of confidence processing for recognition judgments suggest that confidence indexes the degree of match between a presented stimulus and an image in memory (ecphoric similarity). Recent research has demonstrated that having participants rate their confidence that a face had been previously seen provides an equivalent or a better index of the stimulus's status than does eliciting a simple binary response (Sauer, Brewer, & Weber, Journal of Experimental Psychology: General 137: 528-547, 2008). Using a face recognition paradigm, we manipulated retention interval and stimulus distinctiveness to directly test the suggestion that confidence indexes ecphoric similarity and to probe the boundary conditions for using confidence ratings to discriminate seen from unseen faces. Consistent with the proposed ecphoric basis for confidence ratings, mean confidence was higher for previously seen than for unseen faces, and conditions conducive to the formation of strong memories improved confidence-based discrimination. In all conditions, after the application of a classification algorithm, confidence ratings provided a more sensitive index of face status (i.e., seen or unseen) than did binary responses.