Almugbel, Z (2020) ExSim at eHealth-KD Challenge 2020 Combining NLP and Word Embeddings for Entity Recognition. In: Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020). eHealth-KD 2020 Challenge, 23 Sep 2020, Online. IberLEF , pp. 94-101.
Abstract
This paper describes the system submitted to the eHealth-KD Challenge 2020-Task A: entity recognition. The system utilizes a supervised learning methodology to recognize entities within Spanish texts; namely, it applies NLP and word2vec techniques to create a unique labeled dictionary of entities in the training set. These labels are propagated into new entities that are found in the testing set via semantic similarity measurement. The simplicity of our system shows low performance with F1=0.32, precision=
0.29, and recall=0.34. Finally, the system is discussed from different aspects: challenges, earlier attempts, current system’s characteristics, and possible future work.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). IberLEF 2020, September 2020, Málaga, Spain. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: | entity recognition, NLP, word2vec |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Jul 2020 13:42 |
Last Modified: | 08 Dec 2020 14:54 |
Published Version: | http://ceur-ws.org/Vol-2664/ |
Status: | Published |
Publisher: | IberLEF |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:163178 |