| Paper Abstract and Keywords |
| Presentation |
2023-03-18 11:05
Estimating Named Entity Label Representation for Generative Low-Resource NER Yuya Sawada (NAIST), Hiroki Teranishi (RIKEN AIP), Hiroki Ouchi (NAIST), Yuji Matsumoto (RIKEN AIP), Taro Watanabe (NAIST) NLC2022-22 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Named entity recognition (NER) system needs to identify the entities of novel entity types with fewer examples. Few-shot NER systems can capture useful knowledge from external resources, but identifying the nested and discontinuous span is still challenging because their methods are based on sequence labeling and span-based method. We aim for a low-resource generative NER model corresponding to the complex span and propose utilizing methods that use label representation by the novel type's descriptions. Experiments show that the proposed methods achieve competitive performances in few-shot scenarios, and can extract complex spans with limited samples. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Named Entity Recognition / Fine-tuning / Few-shot learning / Description / Nested / Discontinuous / / |
| Reference Info. |
IEICE Tech. Rep., vol. 122, no. 449, NLC2022-22, pp. 16-21, March 2023. |
| Paper # |
NLC2022-22 |
| Date of Issue |
2023-03-11 (NLC) |
| ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
| Download PDF |
NLC2022-22 |
| Conference Information |
| Committee |
NLC IPSJ-NL |
| Conference Date |
2023-03-18 - 2023-03-18 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
OIST |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Applications of natural language processing, and etc. |
| Paper Information |
| Registration To |
NLC |
| Conference Code |
2023-03-NLC-NL |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Estimating Named Entity Label Representation for Generative Low-Resource NER |
| Sub Title (in English) |
|
| Keyword(1) |
Named Entity Recognition |
| Keyword(2) |
Fine-tuning |
| Keyword(3) |
Few-shot learning |
| Keyword(4) |
Description |
| Keyword(5) |
Nested |
| Keyword(6) |
Discontinuous |
| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Yuya Sawada |
| 1st Author's Affiliation |
Nara Institute of Science and Technology (NAIST) |
| 2nd Author's Name |
Hiroki Teranishi |
| 2nd Author's Affiliation |
RIKEN Center for Advanced Intelligence Project (RIKEN AIP) |
| 3rd Author's Name |
Hiroki Ouchi |
| 3rd Author's Affiliation |
Nara Institute of Science and Technology (NAIST) |
| 4th Author's Name |
Yuji Matsumoto |
| 4th Author's Affiliation |
RIKEN Center for Advanced Intelligence Project (RIKEN AIP) |
| 5th Author's Name |
Taro Watanabe |
| 5th Author's Affiliation |
Nara Institute of Science and Technology (NAIST) |
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| Speaker |
Author-1 |
| Date Time |
2023-03-18 11:05:00 |
| Presentation Time |
20 minutes |
| Registration for |
NLC |
| Paper # |
NLC2022-22 |
| Volume (vol) |
vol.122 |
| Number (no) |
no.449 |
| Page |
pp.16-21 |
| #Pages |
6 |
| Date of Issue |
2023-03-11 (NLC) |