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Preprocessed Datasets for our Multimodal NER paper

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Unified Multimodal Transformer (UMT) for Multimodal Named Entity Recognition (MNER)

Two MNER Datasets and Codes for our ACL'2020 paper: Improving Multimodal Named Entity Recognition via Entity Span Detection with Unified Multimodal Transformer.

Author

Jianfei Yu

jfyu@njust.edu.cn

July 1, 2020

Data

Requirement

  • PyTorch 1.0.0
  • Python 3.7

Code Usage

Training for UMT

  • This is the training code of tuning parameters on the dev set, and testing on the test set. Note that you can change "CUDA_VISIBLE_DEVICES=2" based on your available GPUs.
sh run_mtmner_crf.sh
  • We show our running logs on twitter-2015 and twitter-2017 in the folder "log files". Note that the results are a little bit lower than the results reported in our paper, since the experiments were run on different servers.

Acknowledgements

  • Using these two datasets means you have read and accepted the copyrights set by Twitter and dataset providers.

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Preprocessed Datasets for our Multimodal NER paper

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