SciPy 1.0: fundamental algorithms for scientific computing in Python
- Pauli Virtanen, R. Gommers, Y. Vázquez-Baeza
- Computer ScienceNature Methods
- 23 July 2019
An overview of the capabilities and development practices of SciPy 1.0 is provided and some recent technical developments are highlighted.
Cross-lingual Name Tagging and Linking for 282 Languages
- Xiaoman Pan, Boliang Zhang, Jonathan May, J. Nothman, Kevin Knight, Heng Ji
- Computer Science, LinguisticsAnnual Meeting of the Association for…
- 2017
This work develops a cross-lingual name tagging and linking framework for 282 languages that exist in Wikipedia that is able to identify name mentions, assign a coarse-grained or fine- grained type to each mention, and link it to an English Knowledge Base (KB) if it is linkable.
Learning multilingual named entity recognition from Wikipedia
- J. Nothman, Nicky Ringland, Will Radford, T. Murphy, J. Curran
- Computer ScienceArtificial Intelligence
- 2013
Evaluating Entity Linking with Wikipedia
- Ben Hachey, Will Radford, J. Nothman, Matthew Honnibal, J. Curran
- Computer ScienceArtificial Intelligence
- 2013
Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python
- Pauli Virtanen, R. Gommers, Y. Vázquez-Baeza
- Computer ScienceNature Methods
- 24 February 2020
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Named Entity Recognition in Wikipedia
- Dominic Balasuriya, Nicky Ringland, J. Nothman, T. Murphy, J. Curran
- Computer SciencePWNLP@IJCNLP
- 7 August 2009
This first NER evaluation on a Wikipedia gold standard (WG) corpus finds that an automatic annotation of Wikipedia has high agreement with WG and, when used as training data, outperforms newswire models by up to 7.7%.
Overview of TAC-KBP2015 Tri-lingual Entity Discovery and Linking
- Heng Ji, J. Nothman, Ben Hachey, Radu Florian
- Computer Science, LinguisticsText Analysis Conference
- 2015
An overview of the task definition, annotation issues, successful methods and research challenges associated with this new end-to-end Tri-lingual entity discovery and linking task at the Knowledge Base Population (KBP) track at TAC2015 is given.
Transforming Wikipedia into Named Entity Training Data
- J. Nothman, J. Curran, T. Murphy
- Computer ScienceAustralasian Language Technology Association…
- 1 December 2008
Wikipedia is exploited to create a massive corpus of named entity annotated text by transforming Wikipedia’s links into named entity annotations by classifying the target articles into common entity types (e.g. person, organisation and location).
Overview of TAC-KBP 2014 Entity Discovery and Linking Tasks
- Heng Ji, J. Nothman, Ben Hachey
- Computer Science
- 2015
An overview of the new end-to-end English entity discovery and linking task which requires a system to take raw texts as input, automatically extract entity mentions, link them to a knowledge base, and cluster NIL mentions is provided.
Overview of TAC-KBP2017 13 Languages Entity Discovery and Linking
- Heng Ji, Xiaoman Pan, Cash Costello
- Computer ScienceText Analysis Conference
- 2017
An overview of the Tri-lingual Entity Discovery and Linking task at the Knowledge Base Population (KBP) track at TAC2017, and of the Ten Low Resource Language EDL Pilot is given.
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