Fetching the paper…
Reading the bibliography…
Shallow syntax provides an approximation of phrase-syntactic structure of sentences; it can be produced with high accuracy, and is computationally cheap to obtain.
Parsing by chunks
Steven P Abney. 1991 · 1991
Earlier work this paper cites.
Building a large annotated corpus of English: The Penn treebank
Mitchell P Marcus, Mary Ann Marcinkiewicz, and Beatrice Santorini. 1993 · 1993
Earlier work this paper cites.
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition , 1st edition
Daniel Jurafsky and James H. Martin. 2000 · 2000
Earlier work this paper cites.
Introduction to the CoNLL-2000 shared task: Chunking
Erik F. Tjong Kim Sang and Sabine Buchholz. 2000 · 2000
Earlier work this paper cites.
A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Janvin. 2003 · 2003
Earlier work this paper cites.
Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition
Erik F Tjong Kim Sang and Fien De Meulder. 2003 · 2003
Earlier work this paper cites.
Feature-rich part-of-speech tagging with a cyclic dependency network
Kristina Toutanova, Dan Klein, Christopher D. Manning, and Yoram Singer. 2003 · 2003
Earlier work this paper cites.
CCGbank: A corpus of ccg derivations and dependency structures extracted from the Penn Treebank
Julia Hockenmaier and Mark Steedman. 2007 · 2007
Earlier work this paper cites.
OntoNotes Release 4.0
Ralph Weischedel, Sameer Pradhan, Lance Ramshaw, Martha Palmer, Nianwen Xue, Mitchell Marcus, Ann Taylor, Craig Greenberg, Eduard Hovy, Robert Belvin, et al. 2011 · 2011
Earlier work this paper cites.
A new dataset and method for automatically grading esol texts
Helen Yannakoudakis, Ted Briscoe, and Ben Medlock. 2011 · 2011
Earlier work this paper cites.
One billion word benchmark for measuring progress in statistical language modeling
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson. 2013 · 2013
Earlier work this paper cites.
Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Ng, and Christopher Potts. 2013 · 2013
Cited alongside, same era.
OntoNotes release 5.0 ldc2013t19
Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, et al. 2013 · 2013
Cited alongside, same era.
A gold standard dependency corpus for English
Natalia Silveira, Timothy Dozat, Marie-Catherine De Marneffe, Samuel R Bowman, Miriam Connor, John Bauer, and Christopher D Manning. 2014 · 2014
Cited alongside, same era.
Semantic tagging with deep residual networks
Johannes Bjerva, Barbara Plank, and Johan Bos. 2016 · 2016
Cited alongside, same era.
Recurrent neural network grammars
Chris Dyer, Adhiguna Kuncoro, Miguel Ballesteros, and Noah A Smith. 2016 · 2016
Cited alongside, same era.
Character-aware neural language models
Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush. 2016 · 2016
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Later among the works it cites.
Deep rnns encode soft hierarchical syntax
Terra Blevins, Omer Levy, and Luke Zettlemoyer. 2018 · 2018
Later among the works it cites.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Later among the works it cites.
Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
Later among the works it cites.
Lstms can learn syntax-sensitive dependencies well, but modeling structure makes them better
Adhiguna Kuncoro, Chris Dyer, John Hale, Dani Yogatama, Stephen Clark, and Phil Blunsom. 2018 · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Neural architectures for named entity recognition
Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer. 2016 · 2016
Cited alongside, same era.
AllenNLP: A deep semantic natural language processing platform
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson F. Liu, Matthew Peters, Michael Schmitz, and Luke S. Zettlemoyer. 2017 · 2017
Cited alongside, same era.
Learned in translation: Contextualized word vectors
Bryan McCann, James Bradbury, Caiming Xiong, and Richard Socher. 2017 · 2017
Cited alongside, same era.
Semi-supervised sequence tagging with bidirectional language models
Matthew Peters, Waleed Ammar, Chandra Bhagavatula, and Russell Power. 2017 · 2017
Cited alongside, same era.
A minimal span-based neural constituency parser
Mitchell Stern, Jacob Andreas, and Dan Klein. 2017 · 2017
Cited alongside, same era.
Deep contextualized word representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018a
Cited in the paper.
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
Later among the works it cites.
Neural models of factuality
Rachel Rudinger, Aaron Steven White, and Benjamin Van Durme. 2018 · 2018
Later among the works it cites.
Comprehensive supersense disambiguation of English prepositions and possessives
Nathan Schneider, Jena D Hwang, Vivek Srikumar, Jakob Prange, Austin Blodgett, Sarah R Moeller, Aviram Stern, Adi Bitan, and Omri Abend. 2018 · 2018
Later among the works it cites.
Linguistically-informed self-attention for semantic role labeling
Emma Strubell, Patrick Verga, Daniel Andor, David Weiss, and Andrew McCallum. 2018 · 2018
Later among the works it cites.
Linguistic knowledge and transferability of contextual representations
Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew Peters, and Noah A. Smith. 2019 · 2019
Closest in time.
What do you learn from context? Probing for sentence structure in contextualized word representations
Ian Tenney, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R Thomas McCoy, Najoung Kim, Benjamin Van Durme, Sam Bowman, Dipanjan Das, and Ellie Pavlick. 2019 · 2019
Closest in time.