Edward Grefenstette

Also published as: E. Grefenstette


2018

pdf bib
The NarrativeQA Reading Comprehension Challenge
Tomáš Kočiský | Jonathan Schwarz | Phil Blunsom | Chris Dyer | Karl Moritz Hermann | Gábor Melis | Edward Grefenstette
Transactions of the Association for Computational Linguistics, Volume 6

Reading comprehension (RC)—in contrast to information retrieval—requires integrating information and reasoning about events, entities, and their relations across a full document. Question answering is conventionally used to assess RC ability, in both artificial agents and children learning to read. However, existing RC datasets and tasks are dominated by questions that can be solved by selecting answers using superficial information (e.g., local context similarity or global term frequency); they thus fail to test for the essential integrative aspect of RC. To encourage progress on deeper comprehension of language, we present a new dataset and set of tasks in which the reader must answer questions about stories by reading entire books or movie scripts. These tasks are designed so that successfully answering their questions requires understanding the underlying narrative rather than relying on shallow pattern matching or salience. We show that although humans solve the tasks easily, standard RC models struggle on the tasks presented here. We provide an analysis of the dataset and the challenges it presents.

2017

pdf bib
Deep Learning for Semantic Composition
Xiaodan Zhu | Edward Grefenstette
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts

Learning representation to model the meaning of text has been a core problem in NLP. The last several years have seen extensive interests on distributional approaches, in which text spans of different granularities are encoded as vectors of numerical values. If properly learned, such representation has showed to achieve the state-of-the-art performance on a wide range of NLP problems.In this tutorial, we will cover the fundamentals and the state-of-the-art research on neural network-based modeling for semantic composition, which aims to learn distributed representation for different granularities of text, e.g., phrases, sentences, or even documents, from their sub-component meaning representation, e.g., word embedding.

pdf bib
Proceedings of the 2nd Workshop on Representation Learning for NLP
Phil Blunsom | Antoine Bordes | Kyunghyun Cho | Shay Cohen | Chris Dyer | Edward Grefenstette | Karl Moritz Hermann | Laura Rimell | Jason Weston | Scott Yih
Proceedings of the 2nd Workshop on Representation Learning for NLP

2016

pdf bib
Semantic Parsing with Semi-Supervised Sequential Autoencoders
Tomáš Kočiský | Gábor Melis | Edward Grefenstette | Chris Dyer | Wang Ling | Phil Blunsom | Karl Moritz Hermann
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

pdf bib
Latent Predictor Networks for Code Generation
Wang Ling | Phil Blunsom | Edward Grefenstette | Karl Moritz Hermann | Tomáš Kočiský | Fumin Wang | Andrew Senior
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

pdf bib
Proceedings of the 1st Workshop on Representation Learning for NLP
Phil Blunsom | Kyunghyun Cho | Shay Cohen | Edward Grefenstette | Karl Moritz Hermann | Laura Rimell | Jason Weston | Scott Wen-tau Yih
Proceedings of the 1st Workshop on Representation Learning for NLP

2015

pdf bib
Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning
Edward Grefenstette | Mehrnoosh Sadrzadeh
Computational Linguistics, Volume 41, Issue 1 - March 2015

pdf bib
Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality
Alexandre Allauzen | Edward Grefenstette | Karl Moritz Hermann | Hugo Larochelle | Scott Wen-tau Yih
Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality

2014

pdf bib
A Convolutional Neural Network for Modelling Sentences
Nal Kalchbrenner | Edward Grefenstette | Phil Blunsom
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

pdf bib
New Directions in Vector Space Models of Meaning
Edward Grefenstette | Karl Moritz Hermann | Georgiana Dinu | Phil Blunsom
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: Tutorials

pdf bib
A Type-Driven Tensor-Based Semantics for CCG
Jean Maillard | Stephen Clark | Edward Grefenstette
Proceedings of the EACL 2014 Workshop on Type Theory and Natural Language Semantics (TTNLS)

pdf bib
Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality (CVSC)
Alexandre Allauzen | Raffaella Bernardi | Edward Grefenstette | Hugo Larochelle | Christopher Manning | Scott Wen-tau Yih
Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality (CVSC)

pdf bib
A Deep Architecture for Semantic Parsing
Edward Grefenstette | Phil Blunsom | Nando de Freitas | Karl Moritz Hermann
Proceedings of the ACL 2014 Workshop on Semantic Parsing

2013

pdf bib
Multi-Step Regression Learning for Compositional Distributional Semantics
E. Grefenstette | G. Dinu | Y. Zhang | M. Sadrzadeh | M. Baroni
Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers

pdf bib
“Not not bad” is not “bad”: A distributional account of negation
Karl Moritz Hermann | Edward Grefenstette | Phil Blunsom
Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality

pdf bib
Towards a Formal Distributional Semantics: Simulating Logical Calculi with Tensors
Edward Grefenstette
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity

2011

pdf bib
Experimental Support for a Categorical Compositional Distributional Model of Meaning
Edward Grefenstette | Mehrnoosh Sadrzadeh
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

pdf bib
Concrete Sentence Spaces for Compositional Distributional Models of Meaning
Edward Grefenstette | Mehrnoosh Sadrzadeh | Stephen Clark | Bob Coecke | Stephen Pulman
Proceedings of the Ninth International Conference on Computational Semantics (IWCS 2011)

pdf bib
Experimenting with transitive verbs in a DisCoCat
Edward Grefenstette | Mehrnoosh Sadrzadeh
Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics