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DeLFT and entity-fishing : Tools for CLEF HIPE 2020 Shared Task

Authors: Kristanti, Tanti; Romary, Laurent;

DeLFT and entity-fishing : Tools for CLEF HIPE 2020 Shared Task

Abstract

International audience; This article presents an overview of approaches and results during our participation in the CLEF HIPE 2020 NERC-COARSE-LIT and EL-ONLY tasks for English and French. For these two tasks, we use two systems: 1) DeLFT, a Deep Learning framework for text processing; 2) entity-fishing, generic named entity recognition and disambiguation service deployed in the technical framework of INRIA.

Country
France
Keywords

Entity recognition, Entity linking, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], Machine learning, [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL], Deep learning, [INFO.INFO-DL] Computer Science [cs]/Digital Libraries [cs.DL], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]

15 references, page 1 of 2

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2. Chiu, J.P., Nichols, E.: Named entity recognition with bidirectional lstm-cnns. Transactions of the Association for Computational Linguistics 4, 357-370 (2016)

3. Delft. https://github.com/kermitt2/delft (2018-2020)

4. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

5. Ehrmann, M., Romanello, M., Flückiger, A., Clematide, S.: Overview of CLEF HIPE 2020: Named Entity Recognition and Linking on Historical Newspapers. In: Arampatzis, A., Kanoulas, E., Tsikrika, T., Vrochidis, S., Joho, H., Lioma, C., Eickhoff, C., Névéol, A., Cappellato, L., Ferro, N. (eds.) Experimental IR Meets Multilinguality, Multimodality, and Interaction. Proceedings of the 11th International Conference of the CLEF Association (CLEF 2020). Lecture Notes in Computer Science (LNCS), vol. 12260. Springer (2020)

6. Foppiano, L., Romary, L.: entity-fishing: a DARIAH entity recognition and disambiguation service. In: Digital Scholarship in the Humanities . Tokyo, Japan (Sep 2018), https://hal.inria.fr/hal-01812100 [OpenAIRE]

7. Habibi, M., Weber, L., Neves, M., Wiegandt, D.L., Leser, U.: Deep learning with word embeddings improves biomedical named entity recognition. Bioinformatics 33(14), i37-i48 (2017) [OpenAIRE]

8. Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., Dyer, C.: Neural architectures for named entity recognition. arXiv preprint arXiv:1603.01360 (2016)

9. Luo, G., Huang, X., Lin, C.Y., Nie, Z.: Joint entity recognition and disambiguation. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. pp. 879-888 (2015)

10. Ma, X., Hovy, E.: End-to-end sequence labeling via bi-directional lstm-cnns-crf. arXiv preprint arXiv:1603.01354 (2016)

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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