Results of the WNUT2017 Shared Task on Novel and Emerging Entity Recognition
Leon Derczynski,Eric Nichols,Marieke van Erp,Nut Limsopatham +3 more
- pp 140-147
TLDR
The goal of this task is to provide a definition of emerging and of rare entities, and based on that, also datasets for detecting these entities and to evaluate the ability of participating entries to detect and classify novel and emerging named entities in noisy text.Citations
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Proceedings ArticleDOI
IIT (BHU) Submission for the ACL Shared Task on Named Entity Recognition on Code-switched Data.
TL;DR: This paper describes the best performing system for the shared task on Named Entity Recognition on code-switched data for the language pair Spanish-English (ENG-SPA) and introduces a gated neural architecture for the NER task.
Posted Content
Robust Named Entity Recognition with Truecasing Pretraining
TL;DR: This work addresses the problem of robustness of NER systems in data with noisy or uncertain casing, using a pretraining objective that predicts casing in text, or a truecaser, leveraging unlabeled data.
Proceedings ArticleDOI
SpanNER: Named Entity Re-/Recognition as Span Prediction
Abstract: Recent years have seen the paradigm shift of Named Entity Recognition (NER) systems from sequence labeling to span prediction. Despite its preliminary effectiveness, the span prediction model’s architectural bias has not been fully understood. In this paper, we first investigate the strengths and weaknesses when the span prediction model is used for named entity recognition compared with the sequence labeling framework and how to further improve it, which motivates us to make complementary advantages of systems based on different paradigms. We then reveal that span prediction, simultaneously, can serve as a system combiner to re-recognize named entities from different systems’ outputs. We experimentally implement 154 systems on 11 datasets, covering three languages, comprehensive results show the effectiveness of span prediction models that both serve as base NER systems and system combiners. We make all codes and datasets available: https://github.com/neulab/spanner, as well as an online system demo: http://spanner.sh. Our model also has been deployed into the ExplainaBoard platform, which allows users to flexibly perform a system combination of top-scoring systems in an interactive way: http://explainaboard.nlpedia.ai/leaderboard/task-ner/.
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Neural Modeling for Named Entities and Morphology (NEMO^2)
TL;DR: The results show that explicitly modeling morphological boundaries consistently leads to improved NER performance, and that a novel hybrid architecture that is proposed, in which NER precedes and prunes the morphological decomposition (MD) space, greatly outperforms the standard pipeline approach, on both Hebrew NER and Hebrew MD in realistic scenarios.
Journal ArticleDOI
Reddit: a novel data source for cultural ecosystem service studies
TL;DR: It is demonstrated how researchers can search Reddit for CES datasets related to recreation and how specific pages on Reddit may provide data for other CES such as aesthetics and recommended that data from Reddit is best suited to assessing general trends in CES, either for a given service or place.
References
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Proceedings ArticleDOI
The Stanford CoreNLP Natural Language Processing Toolkit
Christopher D. Manning,Mihai Surdeanu,John Bauer,Jenny Rose Finkel,Steven Bethard,David McClosky +5 more
TL;DR: The design and use of the Stanford CoreNLP toolkit is described, an extensible pipeline that provides core natural language analysis, and it is suggested that this follows from a simple, approachable design, straightforward interfaces, the inclusion of robust and good quality analysis components, and not requiring use of a large amount of associated baggage.
Book
Naming and Necessity
TL;DR: In this paper, the authors make a connection between the mind-body problem and the so-called "identity thesis" in analytic philosophy, which has wide-ranging implications for other problems in philosophy that traditionally might be thought far-removed.
Proceedings ArticleDOI
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
TL;DR: The CoNLL-2003 shared task on NER as mentioned in this paper was the first NER task with language-independent named entity recognition (NER) data sets and evaluation method, and a general overview of the systems that participated in the task and their performance.
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NLTK: The Natural Language Toolkit
Edward Loper,Steven Bird +1 more
TL;DR: NLTK, the Natural Language Toolkit, is a suite of open source program modules, tutorials and problem sets, providing ready-to-use computational linguistics courseware that covers symbolic and statistical natural language processing.