58 citations · 91 across the 5 of their papers we have counts for
5 papers
Distributional Inclusion Hypothesis for Tensor-based Composition
Dimitri Kartsaklis, Mehrnoosh Sadrzadeh
According to the distributional inclusion hypothesis, entailment between words can be measured via the feature inclusions of their distributional vectors. In recent work, we showed…
Investigating the Role of Prior Disambiguation in Deep-learning Compositional Models of Meaning
Jianpeng Cheng, Dimitri Kartsaklis, Edward Grefenstette
This paper aims to explore the effect of prior disambiguation on neural network- based compositional models, with the hope that better semantic representations for text compounds c…
Resolving Lexical Ambiguity in Tensor Regression Models of Meaning
Dimitri Kartsaklis, Nal Kalchbrenner, Mehrnoosh Sadrzadeh
This paper provides a method for improving tensor-based compositional distributional models of meaning by the addition of an explicit disambiguation step prior to composition. In c…
Evaluating Neural Word Representations in Tensor-Based Compositional Settings
Dmitrijs Milajevs, Dimitri Kartsaklis, Mehrnoosh Sadrzadeh +1
We provide a comparative study between neural word representations and traditional vector spaces based on co-occurrence counts, in a number of compositional tasks. We use three dif…
A Study of Entanglement in a Categorical Framework of Natural Language
Dimitri Kartsaklis, Mehrnoosh Sadrzadeh
In both quantum mechanics and corpus linguistics based on vector spaces, the notion of entanglement provides a means for the various subsystems to communicate with each other. In t…