Named Entity Recognition with Bidirectional LSTM-CNNs

@article{Chiu2016NamedER,
  title={Named Entity Recognition with Bidirectional LSTM-CNNs},
  author={Jason P. C. Chiu and Eric Nichols},
  journal={Transactions of the Association for Computational Linguistics},
  year={2016},
  volume={4},
  pages={357-370}
}
  • Jason P. C. Chiu, Eric Nichols
  • Published in
    Transactions of the…
    2016
  • Computer Science
  • Named entity recognition is a challenging task that has traditionally required large amounts of knowledge in the form of feature engineering and lexicons to achieve high performance. [...] Key Method We also propose a novel method of encoding partial lexicon matches in neural networks and compare it to existing approaches. Extensive evaluation shows that, given only tokenized text and publicly available word embeddings, our system is competitive on the CoNLL-2003 dataset and surpasses the previously reported…Expand Abstract

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 660 CITATIONS

    Automated analysis of Norwegian text

    VIEW 7 EXCERPTS
    CITES METHODS & RESULTS
    HIGHLY INFLUENCED

    Building Knowledge Graphs : Processing Infrastructure and Named Entity Linking

    VIEW 6 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Bidirectional LSTM-CNNs-CRF Models for POS Tagging

    • Hao Tang
    • 2018
    VIEW 18 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Chinese Clinical Entity Recognition via Attention-Based CNN-LSTM-CRF

    VIEW 11 EXCERPTS
    HIGHLY INFLUENCED

    Few-shot Learning for Named Entity Recognition in Medical Text

    VIEW 4 EXCERPTS
    CITES METHODS
    HIGHLY INFLUENCED

    Modeling with Recurrent Neural Networks for Open Vocabulary Slots

    VIEW 12 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    OpenTag: Open Attribute Value Extraction from Product Profiles

    VIEW 17 EXCERPTS
    CITES BACKGROUND & METHODS
    HIGHLY INFLUENCED

    FILTER CITATIONS BY YEAR

    2016
    2020

    CITATION STATISTICS

    • 93 Highly Influenced Citations

    • Averaged 183 Citations per year from 2017 through 2019

    • 27% Increase in citations per year in 2019 over 2018

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 45 REFERENCES

    Towards Robust Linguistic Analysis using OntoNotes

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL

    Natural Language Processing (Almost) from Scratch

    VIEW 21 EXCERPTS
    HIGHLY INFLUENTIAL

    DBpedia: A Nucleus for a Web of Open Data

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    A Joint Model for Entity Analysis: Coreference, Typing, and Linking

    VIEW 2 EXCERPTS
    HIGHLY INFLUENTIAL

    Dropout Improves Recurrent Neural Networks for Handwriting Recognition

    VIEW 1 EXCERPT
    HIGHLY INFLUENTIAL

    Distributed Representations of Words and Phrases and their Compositionality

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL