MetaLab is a growing database of meta-analyses, shared in a github repository and via an interactive website. This website contains interactive tools for community-augmented metaanalyses, power analyses, and experimental planning. It currently contains a dozen meta-analyses spanning a number of phenomena in early language acquisition research, including infants’ vowel discrimination, acoustic w...

Distributional models of semantics capture word meaning very effectively, and they have been recently extended to account for compositionally-obtained representations of phrases made of content words. We explore whether compositional distributional semantic models can also handle a construction in which grammatical terms play a crucial role, namely determiner phrases (DPs). We introduce a new p...

Poetry is rarely a focus of linguistic investigation. This is far from surprising, as poetic language, especially in modern and contemporary literature, seems to defy the general rules of syntax and semantics. This paper assumes, however, that linguistic theories should ideally be able to account for creative uses of language, down to their most difficult incarnations. It proposes that at the s...

We prove a distributional limit theorem conjectured in Clark (J Stat Phys 174(6):1372–1403, 2019) for partition functions defining models of directed polymers on diamond hierarchical graphs with disorder variables placed at the graphical edges. The limiting regime involves joint scaling which number layers, \(n\in {\mathbb {N}}\), grows as inverse temperature, \(\beta \equiv \beta (n)\), vanish...

We present a factorized compositional distributional semantics model for the representation of transitive verb constructions. Our model first produces (subject, verb) and (verb, object) vector representations based on the similarity of the nouns in the construction to each of the nouns in the vocabulary and the tendency of these nouns to take the subject and object roles of the verb. These vect...

The question of how to compose meaning in distributional representations of meaning has recently been recognised as a central issue in computational linguistics. In this paper we describe three general and powerful tools that can be used to describe composition in distributional semantics: quotient algebras, learning of finite dimensional algebras, and the construction of algebras from semigroups.

In this article, we explore an integration of a formal semantic approach to lexical meaning and an approach based on distributional methods. First, we outline a formal semantic theory that aims to combine the virtues of both formal and distributional frameworks. We then proceed to develop an algebraic interpretation of that formal semantic theory and show how at least two kinds of distributiona...

Approaches to determining the factuality of diagnoses and findings in clinical text tend to rely on dictionaries of marker words for uncertainty and negation. Here, a method for semi-automatically expanding a dictionary of marker words using distributional semantics is presented and evaluated. It is shown that ranking candidates for inclusion according to their proximity to cluster centroids of...

We introduce two ways to detect entailment using distributional semantic representations of phrases. Our first experiment shows that the entailment relation between adjective-noun constructions and their head nouns (big cat |= cat), once represented as semantic vector pairs, generalizes to lexical entailment among nouns (dog |= animal). Our second experiment shows that a classifier fed semantic...

The paper presents a procedure of building an evaluation dataset1. for the validation of compositional distributional semantics models estimated for languages other than English. The procedure generally builds on steps designed to assemble the SICK corpus, which contains pairs of English sentences annotated for semantic relatedness and entailment, because we aim at building a comparable dataset...