Computational Linguistics: Publications

"Not not bad" is not "bad": A distributional account of negation

Karl Moritz Hermann‚ Edward Grefenstette and Phil Blunsom

In Proceedings of the 2013 Workshop on Continuous Vector Space Models and their Compositionality. August, 2013.

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A Bayesian Model for Learning SCFGs with Discontiguous Rules

Abby Levenberg‚ Chris Dyer and Phil Blunsom

In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. Pages 223–232. Association for Computational Linguistics. July, 2012.

Details about A Bayesian Model for Learning SCFGs with Discontiguous Rules | BibTeX data for A Bayesian Model for Learning SCFGs with Discontiguous Rules

A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations

Mehrnoosh Sadrzadeh and Edward Grefenstette

In Lecture Notes in Computer Science. Vol. 7052. Pages 35–47. 2011.

Details about A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations | BibTeX data for A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations | Link to A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations

A Convolutional Neural Network for Modelling Sentences

Nal Kalchbrenner‚ Edward Grefenstette and Phil Blunsom

In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. June, 2014.

Details about A Convolutional Neural Network for Modelling Sentences | BibTeX data for A Convolutional Neural Network for Modelling Sentences | Link to A Convolutional Neural Network for Modelling Sentences

A Deep Architecture for Semantic Parsing

Edward Grefenstette‚ Phil Blunsom‚ Nando de Freitas and Karl Moritz Hermann

In Proceedings of the ACL 2014 Workshop on Semantic Parsing. June, 2014.

Details about A Deep Architecture for Semantic Parsing | BibTeX data for A Deep Architecture for Semantic Parsing | Link to A Deep Architecture for Semantic Parsing

A Discriminative Latent Variable Model for Statistical Machine Translation

Phil Blunsom‚ Trevor Cohn and Miles Osborne

In Proc. of the 46th Annual Conference of the Association for Computational Linguistics: Human Language Technologies (ACL−08:HLT). Pages 200–208. Columbus‚ Ohio. June, 2008.

Details about A Discriminative Latent Variable Model for Statistical Machine Translation | BibTeX data for A Discriminative Latent Variable Model for Statistical Machine Translation | Link to A Discriminative Latent Variable Model for Statistical Machine Translation

A Fast and Simple Online Synchronous Context Free Grammar Extractor

Paul Baltescu and Phil Blunsom

In The Prague Bulletin of Mathematical Linguistics. Vol. 102. No. 1. Pages 17–26. October, 2014.

Details about A Fast and Simple Online Synchronous Context Free Grammar Extractor | BibTeX data for A Fast and Simple Online Synchronous Context Free Grammar Extractor | Download (pdf) of A Fast and Simple Online Synchronous Context Free Grammar Extractor

A Hierarchical Pitman−Yor Process HMM for Unsupervised Part of Speech Induction

Phil Blunsom and Trevor Cohn

In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies. Pages 865–874. Portland‚ Oregon‚ USA. June, 2011. Association for Computational Linguistics.

Details about A Hierarchical Pitman−Yor Process HMM for Unsupervised Part of Speech Induction | BibTeX data for A Hierarchical Pitman−Yor Process HMM for Unsupervised Part of Speech Induction | Link to A Hierarchical Pitman−Yor Process HMM for Unsupervised Part of Speech Induction

A Note on the Implementation of Hierarchical Dirichlet Processes

Phil Blunsom‚ Trevor Cohn‚ Sharon Goldwater and Mark Johnson

In Proceedings of the ACL−IJCNLP 2009 Conference Short Papers. Pages 337–340. Suntec‚ Singapore. August, 2009. Association for Computational Linguistics.

Details about A Note on the Implementation of Hierarchical Dirichlet Processes | BibTeX data for A Note on the Implementation of Hierarchical Dirichlet Processes | Link to A Note on the Implementation of Hierarchical Dirichlet Processes

A Study of Entanglement in a Categorical Framework of Natural Language

Dimitri Kartsaklis and Mehrnoosh Sadrzadeh

In Proceedings of the 11th Workshop on Quantum Physics and Logic (QPL). Kyoto‚ Japan. June, 2014.

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A Systematic Bayesian Treatment of the IBM Alignment Models

Yarin Gal and Phil Blunsom

In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics. 2013.

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A Type−Driven Tensor−Based Semantics for CCG

Jean Maillard‚ Stephen Clark and Edward Grefenstette

In EACL 2014 Type Theory and Natural Language Semantics Workshop. 2014.

Details about A Type−Driven Tensor−Based Semantics for CCG | BibTeX data for A Type−Driven Tensor−Based Semantics for CCG | Link to A Type−Driven Tensor−Based Semantics for CCG

A Unified Sentence Space for Categorical Distributional−Compositional Semantics: Theory and Experiments

Dimitri Kartsaklis‚ Mehrnoosh Sadrzadeh and Stephen Pulman

In Proceedings of 24th International Conference on Computational Linguistics (COLING): Posters. Pages 549−558. Mumbai‚ India. December, 2012.

Details about A Unified Sentence Space for Categorical Distributional−Compositional Semantics: Theory and Experiments | BibTeX data for A Unified Sentence Space for Categorical Distributional−Compositional Semantics: Theory and Experiments | Download  (pdf) of A Unified Sentence Space for Categorical Distributional−Compositional Semantics: Theory and Experiments

A Bayesian Model of Syntax−Directed Tree to String Grammar Induction

Trevor Cohn and Phil Blunsom

In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing. Pages 352–361. Singapore. August, 2009. Association for Computational Linguistics.

Details about A Bayesian Model of Syntax−Directed Tree to String Grammar Induction | BibTeX data for A Bayesian Model of Syntax−Directed Tree to String Grammar Induction | Link to A Bayesian Model of Syntax−Directed Tree to String Grammar Induction

A Gibbs Sampler for Phrasal Synchronous Grammar Induction

Phil Blunsom‚ Trevor Cohn‚ Chris Dyer and Miles Osborne

In Proc. of the Joint conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL/IJCNLP−09). Pages 782–790. Singapore. August, 2009.

Details about A Gibbs Sampler for Phrasal Synchronous Grammar Induction | BibTeX data for A Gibbs Sampler for Phrasal Synchronous Grammar Induction

Adaptor Grammars for Learning Non−Concatenative Morphology

Jan A. Botha and Phil Blunsom

In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Pages 345−356. Seattle‚ Washington‚ USA. October, 2013. Association for Computational Linguistics.

Details about Adaptor Grammars for Learning Non−Concatenative Morphology | BibTeX data for Adaptor Grammars for Learning Non−Concatenative Morphology | Download (pdf) of Adaptor Grammars for Learning Non−Concatenative Morphology

An Unsupervised Ranking Model for Noun−Noun Compositionality

Karl Moritz Hermann‚ Phil Blunsom and Stephen Pulman

In *SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task‚ and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012). Pages 132–141. Montréal‚ Canada. 2012. Association for Computational Linguistics.

Details about An Unsupervised Ranking Model for Noun−Noun Compositionality | BibTeX data for An Unsupervised Ranking Model for Noun−Noun Compositionality | Download  (pdf) of An Unsupervised Ranking Model for Noun−Noun Compositionality | Link to An Unsupervised Ranking Model for Noun−Noun Compositionality

Analysing Document Similarity Measures

Edward Grefenstette

Master's Thesis University of Oxford. September, 2009.

Details about Analysing Document Similarity Measures | BibTeX data for Analysing Document Similarity Measures | Download (pdf) of Analysing Document Similarity Measures

BLOCKED INFERENCE IN BAYESIAN TREE SUBSTITUTION GRAMMARS

Trevor Cohn and Phil Blunsom

In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. Uppsala‚ Sweden. 2010.

Details about BLOCKED INFERENCE IN BAYESIAN TREE SUBSTITUTION GRAMMARS | BibTeX data for BLOCKED INFERENCE IN BAYESIAN TREE SUBSTITUTION GRAMMARS

Bayesian Synchronous Grammar Induction

Phil Blunsom‚ Trevor Cohn and Miles Osborne

In D. Koller‚ D. Schuurmans‚ Y. Bengio and L. Bottou, editors, Advances in Neural Information Processing Systems 21. Pages 161–168. 2008.

Details about Bayesian Synchronous Grammar Induction | BibTeX data for Bayesian Synchronous Grammar Induction

Category−Theoretic Quantitative Compositional Distributional Models of Natural Language Semantics

Edward Grefenstette

PhD Thesis June, 2013.

Details about Category−Theoretic Quantitative Compositional Distributional Models of Natural Language Semantics | BibTeX data for Category−Theoretic Quantitative Compositional Distributional Models of Natural Language Semantics | Link to Category−Theoretic Quantitative Compositional Distributional Models of Natural Language Semantics

Collapsed Variational Bayesian Inference for Hidden Markov Models

Pengyu Wang and Phil Blunsom

In AISTATS. 2013.

Details about Collapsed Variational Bayesian Inference for Hidden Markov Models | BibTeX data for Collapsed Variational Bayesian Inference for Hidden Markov Models

Collapsed Variational Bayesian Inference for PCFGs

Pengyu Wang and Phil Blunsom

In Proceedings of the Seventeenth Conference on Computational Natural Language Learning. Pages 173–182. Sofia‚ Bulgaria. August, 2013. Association for Computational Linguistics.

Details about Collapsed Variational Bayesian Inference for PCFGs | BibTeX data for Collapsed Variational Bayesian Inference for PCFGs | Link to Collapsed Variational Bayesian Inference for PCFGs

Compositional Operators in Distributional Semantics

Dimitri Kartsaklis

In Springer Science Reviews. April, 2014.

Details about Compositional Operators in Distributional Semantics | BibTeX data for Compositional Operators in Distributional Semantics | Download  (pdf) of Compositional Operators in Distributional Semantics | DOI (10.1007/s40362-014-0017-z)

Conceptual Knowledge Acquisition Using Automatically Generated Large−Scale Semantic Networks

Pia−Ramona Wojtinnek‚ Brian Harrington‚ Sebastian Rudolph and Stephen Pulman

In Proceedings of the 18th International Conference on Conceptual Structures. 2010.

Details about Conceptual Knowledge Acquisition Using Automatically Generated Large−Scale Semantic Networks | BibTeX data for Conceptual Knowledge Acquisition Using Automatically Generated Large−Scale Semantic Networks

Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning

Edward Grefenstette and Mehrnoosh Sadrzadeh

In Computational Linguistics. 2014.

Details about Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning | BibTeX data for Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning

Concrete Sentence Spaces for Compositional Distributional Models of Meaning

Edward Grefenstette‚ Mehrnoosh Sadrzadeh‚ Stephen Clark‚ Bob Coecke and Stephen Pulman

In Proceedings of the 9th International Conference on Computational Semantics (IWCS11). Pages 125–134. 2011.

Details about Concrete Sentence Spaces for Compositional Distributional Models of Meaning | BibTeX data for Concrete Sentence Spaces for Compositional Distributional Models of Meaning | Download (pdf) of Concrete Sentence Spaces for Compositional Distributional Models of Meaning

Discriminative Word Alignment with Conditional Random Fields

Phil Blunsom and Trevor Cohn

In Proc. of the 44th Annual Meeting of the ACL and 21st International Conference on Computational Linguistics (COLING/ACL−2006). Pages 65–72. Sydney‚ Australia. July, 2006.

Details about Discriminative Word Alignment with Conditional Random Fields | BibTeX data for Discriminative Word Alignment with Conditional Random Fields | Link to Discriminative Word Alignment with Conditional Random Fields

Evaluating Neural Word Representations in Tensor−Based Compositional Settings

Dmitrijs Milajevs‚ Dimitri Kartsaklis‚ Mehrnoosh Sadrzadeh and Matthew Purver

In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Doha‚ Qatar. October, 2014. Association for Computational Linguistics.

Details about Evaluating Neural Word Representations in Tensor−Based Compositional Settings | BibTeX data for Evaluating Neural Word Representations in Tensor−Based Compositional Settings | Download  (pdf) of Evaluating Neural Word Representations in Tensor−Based Compositional Settings | Download (pdf) of Evaluating Neural Word Representations in Tensor−Based Compositional Settings

Experimental Support for a Categorical Compositional Distributional Model of Meaning

Edward Grefenstette and Mehrnoosh Sadrzadeh

In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing. 2011.

Details about Experimental Support for a Categorical Compositional Distributional Model of Meaning | BibTeX data for Experimental Support for a Categorical Compositional Distributional Model of Meaning | Download (pdf) of Experimental Support for a Categorical Compositional Distributional Model of Meaning

Experimenting with Transitive Verbs in a DisCoCat

Edward Grefenstette and Mehrnoosh Sadrzadeh

In Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics. 2011.

Details about Experimenting with Transitive Verbs in a DisCoCat | BibTeX data for Experimenting with Transitive Verbs in a DisCoCat | Download (pdf) of Experimenting with Transitive Verbs in a DisCoCat

Formal and Computational Semantics: a Case Study

Stephen Pulman

In Jeroen Geertzen‚ Elias Thijsse‚ Harry Bunt and Amanda Schiffrin, editors, Proceedings of the Seventh International Workshop on Computational Semantics: IWCS−7‚ Tilburg‚ The Netherlands‚ 2007. Pages 181–196. 2007.

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Grammatical Description and Sentence Processing

Stephen Pulman

University of East Anglia. 1979.

Details about Grammatical Description and Sentence Processing | BibTeX data for Grammatical Description and Sentence Processing

Indexed Grammars and Intersecting Dependencies

Stephen Pulman and G. D. Ritchie

No. 23. University of East Anglia. 1985.

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Inducing Synchronous Grammars with Slice Sampling

Phil Blunsom and Trevor Cohn

In NAACL 2010. June, 2010.

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Inducing Tree−Substitution Grammars

Trevor Cohn‚ Phil Blunsom and Sharon Goldwater

In Journal of Machine Learning Research. Pages 3053–3096. 2010.

Details about Inducing Tree−Substitution Grammars | BibTeX data for Inducing Tree−Substitution Grammars

Inducing compact but accurate tree−substitution grammars

Trevor Cohn‚ Sharon Goldwater and Phil Blunsom

In NAACL '09: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics. Pages 548–556. Morristown‚ NJ‚ USA. 2009. Association for Computational Linguistics.

Details about Inducing compact but accurate tree−substitution grammars | BibTeX data for Inducing compact but accurate tree−substitution grammars

Investigating the Role or Prior Disambiguation in Deep−Learning Compositional Models of Meaning

Jianpeng Cheng‚ Dimitri Kartsaklis and Edward Grefenstette

In Learning Semantics workshop‚ NIPS 2014. Montreal‚ Canada. December, 2014.

Details about Investigating the Role or Prior Disambiguation in Deep−Learning Compositional Models of Meaning | BibTeX data for Investigating the Role or Prior Disambiguation in Deep−Learning Compositional Models of Meaning | Download (pdf) of Investigating the Role or Prior Disambiguation in Deep−Learning Compositional Models of Meaning

Lambek vs. Lambek: Functorial Vector Space Semantics and String Diagrams for Lambek Calculus

Bob Coecke‚ Edward Grefenstette and Mehrnoosh Sadrzadeh

In Annals of Pure and Applied Logic. 2013.

Details about Lambek vs. Lambek: Functorial Vector Space Semantics and String Diagrams for Lambek Calculus | BibTeX data for Lambek vs. Lambek: Functorial Vector Space Semantics and String Diagrams for Lambek Calculus | Link to Lambek vs. Lambek: Functorial Vector Space Semantics and String Diagrams for Lambek Calculus

Learning Semantics and Selectional Preference of Adjective−Noun Pairs

Karl Moritz Hermann‚ Chris Dyer‚ Phil Blunsom and Stephen Pulman

In *SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task‚ and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012). Pages 70–74. Montréal‚ Canada. 2012. Association for Computational Linguistics.

Details about Learning Semantics and Selectional Preference of Adjective−Noun Pairs | BibTeX data for Learning Semantics and Selectional Preference of Adjective−Noun Pairs | Download  (pdf) of Learning Semantics and Selectional Preference of Adjective−Noun Pairs | Link to Learning Semantics and Selectional Preference of Adjective−Noun Pairs

Linguistic steganography on Twitter: hierarchical language modeling with manual interaction

Alex Wilson‚ Phil Blunsom and Andrew D Ker

In &T/SPIEIS Electronic Imaging. Pages 902803–902803. International Society for Optics and Photonics. 2014.

Details about Linguistic steganography on Twitter: hierarchical language modeling with manual interaction | BibTeX data for Linguistic steganography on Twitter: hierarchical language modeling with manual interaction

Maximum Entropy Markov models for semantic role labelling

Phil Blunsom

In Proc. of the Australasian Language Technology Workshop 2004. Pages 109–116. Sydney‚ Australia. 2005.

Details about Maximum Entropy Markov models for semantic role labelling | BibTeX data for Maximum Entropy Markov models for semantic role labelling

Metrics for MT Evaluation: Evaluating Reordering

Alexandra Birch‚ Phil Blunsom and Miles Osborne

In Machine Translation. 2010.

Details about Metrics for MT Evaluation: Evaluating Reordering | BibTeX data for Metrics for MT Evaluation: Evaluating Reordering

Modelling the Lexicon in Unsupervised Part of Speech Induction

Gregory Dubbin and Phil Blunsom

In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics. Pages 116–125. Gothenburg‚ Sweden. April, 2014. Association for Computational Linguistics.

Details about Modelling the Lexicon in Unsupervised Part of Speech Induction | BibTeX data for Modelling the Lexicon in Unsupervised Part of Speech Induction | Link to Modelling the Lexicon in Unsupervised Part of Speech Induction

Modelling‚ Visualising and Summarising Documents with a Single Convolutional Neural Network

Misha Denil‚ Alban Demiraj‚ Nal Kalchbrenner‚ Phil Blunsom and Nando de Freitas

No. arXiv:1406.3830. University of Oxford. 2014.

Details about Modelling‚ Visualising and Summarising Documents with a Single Convolutional Neural Network | BibTeX data for Modelling‚ Visualising and Summarising Documents with a Single Convolutional Neural Network | Link to Modelling‚ Visualising and Summarising Documents with a Single Convolutional Neural Network

Monte Carlo inference and maximization for phrase−based translation

Abhishek Arun‚ Chris Dyer‚ Barry Haddow‚ Phil Blunsom‚ Adam Lopez and Philipp Koehn

In CoNLL '09: Proceedings of the Thirteenth Conference on Computational Natural Language Learning. Pages 102–110. Morristown‚ NJ‚ USA. 2009. Association for Computational Linguistics.

Details about Monte Carlo inference and maximization for phrase−based translation | BibTeX data for Monte Carlo inference and maximization for phrase−based translation

Multi−Step Regression Learning for Compositional Distributional Semantics

Edward Grefenstette‚ Georgiana Dinu‚ Yao−Zhong Zhang‚ Mehrnoosh Sadrzadeh and Marco Baroni

In Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013). 2013.

Details about Multi−Step Regression Learning for Compositional Distributional Semantics | BibTeX data for Multi−Step Regression Learning for Compositional Distributional Semantics | Download (pdf) of Multi−Step Regression Learning for Compositional Distributional Semantics

Multilingual Deep Lexical Acquisition for HPSGs via Supertagging

Phil Blunsom and Timothy Baldwin

In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing. Pages 164–171. Sydney‚ Australia. July, 2006.

Details about Multilingual Deep Lexical Acquisition for HPSGs via Supertagging | BibTeX data for Multilingual Deep Lexical Acquisition for HPSGs via Supertagging

New Directions in Vector Space Models of Meaning

Edward Grefenstette‚ Karl Moritz Hermann‚ Georgiana Dinu and Phil Blunsom

In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. June, 2014.

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OxLM: A Neural Language Modelling Framework for Machine Translation

Paul Baltescu‚ Phil Blunsom and Hieu Hoang

In The Prague Bulletin of Mathematical Linguistics. Vol. 102. No. 1. Pages 81–92. October, 2014.

Details about OxLM: A Neural Language Modelling Framework for Machine Translation | BibTeX data for OxLM: A Neural Language Modelling Framework for Machine Translation | Download (pdf) of OxLM: A Neural Language Modelling Framework for Machine Translation

Prior Disambiguation of Word Tensors for Constructing Sentence Vectors

Dimitri Kartsaklis and Mehrnoosh Sadrzadeh

In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP). Seattle‚ USA. October, 2013.

Details about Prior Disambiguation of Word Tensors for Constructing Sentence Vectors | BibTeX data for Prior Disambiguation of Word Tensors for Constructing Sentence Vectors | Download  (pdf) of Prior Disambiguation of Word Tensors for Constructing Sentence Vectors

Probabilistic Inference for Machine Translation

Phil Blunsom and Miles Osborne

In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing. Pages 215–223. Honolulu‚ Hawaii. October, 2008.

Details about Probabilistic Inference for Machine Translation | BibTeX data for Probabilistic Inference for Machine Translation

Quantum Physics and Linguistics: A Compositional‚ Diagrammatic Discourse

Chris Heunen‚ Mehrnoosh Sadrzadeh and Edward Grefenstette, editors

Oxford University Press. February, 2013.

Details about Quantum Physics and Linguistics: A Compositional‚ Diagrammatic Discourse | BibTeX data for Quantum Physics and Linguistics: A Compositional‚ Diagrammatic Discourse | Link to Quantum Physics and Linguistics: A Compositional‚ Diagrammatic Discourse

Question classification with log−linear models

Phil Blunsom‚ Krystle Kocik and James R. Curran

In SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval. Pages 615–616. New York‚ NY‚ USA. 2006. ACM.

Details about Question classification with log−linear models | BibTeX data for Question classification with log−linear models | DOI (http://doi.acm.org/10.1145/1148170.1148282)

Reasoning about Meaning in Natural Language with Compact Closed Categories and Frobenius Algebras

Dimitri Kartsaklis‚ Mehrnoosh Sadrzadeh‚ Stephen Pulman and Bob Coecke

In A. Chubb J. Eskandarian and V. Harizanov, editors, Logic and Algebraic Structures in Quantum Computing and Information. Cambridge University Press. 2013.

To appear

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Recurrent Continuous Translation Models

Nal Kalchbrenner and Phil Blunsom

Seattle. October, 2013. Association for Computational Linguistics.

Details about Recurrent Continuous Translation Models | BibTeX data for Recurrent Continuous Translation Models

Recurrent Convolutional Neural Networks for Discourse Compositionality

Nal Kalchbrenner and Phil Blunsom

In Proceedings of the 2013 Workshop on Continuous Vector Space Models and their Compositionality. 2013.

Details about Recurrent Convolutional Neural Networks for Discourse Compositionality | BibTeX data for Recurrent Convolutional Neural Networks for Discourse Compositionality

Resolving Lexical Ambiguity in Tensor Regression Models of Meaning

Dimitri Kartsaklis‚ Nal Kalchbrenner and Mehrnoosh Sadrzadeh

In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Vol. 2: Short Papers). Pages 212–217. Baltimore‚ USA. June, 2014. Association for Computational Linguistics.

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Semantic Relatedness from Automatically Generated Semantic Networks

Pia−Ramona Wojtinnek and Stephen Pulman

In Johan Bos and Stephen Pulman, editors, Proceedings of the 9th International Conference on Computational Semantics (IWCS11). Pages 390−394. Oxford‚ UK. 2011. ACL SIGSEM. ACL.

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Semantic Role Labelling with Tree Conditional Random Fields

Trevor Cohn and Philip Blunsom

In Proc. of the 9th Conference on Natural Language Learning (CoNLL−2005). Pages 169–172. Ann Arbor‚ Michigan. June, 2005.

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Separating Disambiguation from Composition in Distributional Semantics

Dimitri Kartsaklis‚ Mehrnoosh Sadrzadeh and Stephen Pulman

In Proceedings of 17th Conference on Natural Language Learning (CoNLL). Pages 114−123. Sofia‚ Bulgaria. August, 2013.

Details about Separating Disambiguation from Composition in Distributional Semantics | BibTeX data for Separating Disambiguation from Composition in Distributional Semantics | Download  (pdf) of Separating Disambiguation from Composition in Distributional Semantics

Shallow Processing and Automatic Summarising: a First Study

Stephen Pulman‚ Philip Gladwin and Karen Spärck Jones

Computer Laboratory‚ University of Cambridge. 1991.

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Shape Classifiers and Natural Categories

Stephen Pulman

Essex University. 1978.

Details about Shape Classifiers and Natural Categories | BibTeX data for Shape Classifiers and Natural Categories

The pascal challenge on grammar induction

Douwe Gelling‚ Trevor Cohn‚ Phil Blunsom and Joao Graça

In Proceedings of the NAACL−HLT Workshop on the Induction of Linguistic Structure. Pages 64–80. Association for Computational Linguistics. June, 2012.

Details about The pascal challenge on grammar induction | BibTeX data for The pascal challenge on grammar induction

Towards a Formal Distributional Semantics: Simulating Logical Calculi with Tensors

Edward Grefenstette

In Proceedings of the Second Joint Conference on Lexical and Computational Semantics. 2013.

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Tree Transduction Tools for cdec

Austin Matthews‚ Paul Baltescu‚ Phil Blunsom‚ Alon Lavie and Chris Dyer

In The Prague Bulletin of Mathematical Linguistics. Vol. 102. No. 1. Pages 27–36. October, 2014.

Details about Tree Transduction Tools for cdec | BibTeX data for Tree Transduction Tools for cdec | Download (pdf) of Tree Transduction Tools for cdec

Unsupervised Bayesian Part of Speech Inference with Particle Gibbs

Gregory Dubbin and Phil Blunsom

In N. Cristianini P. Flach T. De Bie, editor, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). Bristol‚ UK. September, 2012. Springer.

Details about Unsupervised Bayesian Part of Speech Inference with Particle Gibbs | BibTeX data for Unsupervised Bayesian Part of Speech Inference with Particle Gibbs

Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing

Phil Blunsom and Trevor Cohn

In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing. Pages 1204–1213. Cambridge‚ MA. October, 2010. Association for Computational Linguistics.

Details about Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing | BibTeX data for Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing | Link to Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing

Unsupervised part of speech inference with particle filters

Gregory Dubbin and Phil Blunsom

In Proceedings of the NAACL−HLT Workshop on the Induction of Linguistic Structure. Pages 47–54. Association for Computational Linguistics. 2012.

Details about Unsupervised part of speech inference with particle filters | BibTeX data for Unsupervised part of speech inference with particle filters

cdec: A Decoder‚ Alignment‚ and Learning framework for finite−state and context−free translation models

Chris Dyer‚ Adam Lopez‚ Juri Ganitkevitch‚ Johnathan Weese‚ Ferhan Ture‚ Phil Blunsom‚ Hendra Setiawan‚ Vladimir Eidelman and Philip Resnik

In Proceedings of the ACL 2010 System Demonstrations. Pages 7–12. 2010.

Details about cdec: A Decoder‚ Alignment‚ and Learning framework for finite−state and context−free translation models | BibTeX data for cdec: A Decoder‚ Alignment‚ and Learning framework for finite−state and context−free translation models

A Primer on Graph Processing with Bolinas

Jacob Andreas‚ Daniel Bauer‚ David Chiang‚ Karl Moritz Hermann‚ Bevan Jones and Kevin Knight

August, 2013.

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Bayesian Language Modelling of German Compounds

Jan A. Botha‚ Chris Dyer and Phil Blunsom

In Proceedings of the 24th International Conference on Computational Linguistics (COLING). Pages 341–356. Mumbai‚ India. December, 2012. The COLING 2012 Organizing Committee.

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Can‚ Could‚ and Possible For

Stephen Pulman

Essex University. 1976.

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Compositional Morphology for Word Representations and Language Modelling

Jan A. Botha and Phil Blunsom

In Proceedings of the 31st International Conference on Machine Learning (ICML). Beijing‚ China. June, 2014.

*Award for best application paper*

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Hierarchical Bayesian Language Modelling for the Linguistically Informed

Jan A. Botha

In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop (EACL−SRW). Pages 64–73. 2012.

Best student paper prize

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Learning Bilingual Word Representations by Marginalizing Alignments

Tomáš Kočiský‚ Karl Moritz Hermann and Phil Blunsom

In Proceedings of ACL. June, 2014.

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Multilingual Distributed Representations without Word Alignment

Karl Moritz Hermann and Phil Blunsom

In Proceedings of ICLR. April, 2014.

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Multilingual Models for Compositional Distributional Semantics

Karl Moritz Hermann and Phil Blunsom

In Proceedings of ACL. June, 2014.

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Monte Carlo techniques for phrase−based translation

Abhishek Arun‚ Chris Dyer‚ Barry Haddow‚ Phil Blunsom‚ Adam Lopez and Philipp Koehn

In Special Issue of Machine Translation Journal. 2010.

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Parsing Graphs with Hyperedge Replacement Grammars

David Chiang‚ Jacob Andreas‚ Daniel Bauer‚ Karl Moritz Hermann‚ Bevan Jones and Kevin Knight

In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Pages 924–932. Sofia‚ Bulgaria. August, 2013. Association for Computational Linguistics.

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Semantic Frame Identification with Distributed Word Representations

Karl Moritz Hermann‚ Dipanjan Das‚ Jason Weston and Kuzman Ganchev

In Proceedings of ACL. June, 2014.

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Semantics−Based Machine Translation with Hyperedge Replacement Grammars

Bevan Jones‚ Jacob Andreas‚ Daniel Bauer‚ Karl Moritz Hermann and Kevin Knight

In Proceedings of COLING 2012. Pages 1359–1376. December, 2012.

First four are joint first author in randomized order

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The Role of Syntax in Vector Space Models of Compositional Semantics

Karl Moritz Hermann and Phil Blunsom

In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Pages 894–904. Sofia‚ Bulgaria. August, 2013. Association for Computational Linguistics.

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The SRI Core Language Engine project: the grammar

Stephen Pulman and G. D. Ritchie

Centre for Cognitive Science‚ Edinburgh‚ and Institute for Language‚ Logic and Information‚ Amsterdam. 1987.

in E. Klein and J. van Benthem (eds.) Categories‚ Polymorphism and Unification

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