Trained models for multi-task multi-dataset learning for sequence prediction in tweets - Old Experiments
收藏doi.org2025-01-15 收录
下载链接:
https://doi.org/10.13012/B2IDB-4520270_V1
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资源简介:
Trained models for multi-task multi-dataset learning for sequence prediction in tweets Tasks include POS, NER, Chunking, and SuperSenseTagging Models were trained using: https://github.com/napsternxg/SocialMediaIE/blob/master/experiments/multitask_multidataset_experiment.py See https://github.com/napsternxg/SocialMediaIE for details.
针对推特序列预测的多任务多数据集学习训练模型,涵盖词性标注(POS)、命名实体识别(NER)、分块处理(Chunking)和超级语义标注(SuperSenseTagging)。模型训练采用以下链接中的方法:https://github.com/napsternxg/SocialMediaIE/blob/master/experiments/multitask_multidataset_experiment.py。更多详细信息,请参阅:https://github.com/napsternxg/SocialMediaIE。
提供机构:
Illinois Data Bank



