RANER介绍

模型描述

本方法采用Transformer-CRF模型，使用XLM-Roberta作为预训练模型底座，结合使用外部工具召回的相关句子作为额外上下文，使用Multi-view Training方式进行训练。
模型结构如下图所示：

可参考论文：Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning

期望模型使用方式以及适用范围

本模型主要用于给输入英语句子产出命名实体识别结果。用户可以自行尝试输入英语句子。具体调用方式请参考代码示例。

如何使用

在安装ModelScope完成之后即可使用chunking(组块分析)的能力, 默认单句长度不超过512。

代码范例

from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks

ner_pipeline = pipeline(Tasks.named_entity_recognition, 'damo/nlp_raner_chunking_english-large')
result = ner_pipeline('Confidence in the pound is widely expected to take another sharp dive if trade figures for September.')

print(result)
# {'output': [{'type': 'NP', 'start': 0, 'end': 10, 'span': 'Confidence'}, {'type': 'PP', 'start': 11, 'end': 13, 'span': 'in'}, {'type': 'NP', 'start': 14, 'end': 23, 'span': 'the pound'}, {'type': 'VP', 'start': 24, 'end': 50, 'span': 'is widely expected to take'}, {'type': 'NP', 'start': 51, 'end': 69, 'span': 'another sharp dive'}, {'type': 'SBAR', 'start': 70, 'end': 72, 'span': 'if'}, {'type': 'NP', 'start': 73, 'end': 78, 'span': 'trade'}, {'type': 'NP', 'start': 79, 'end': 86, 'span': 'figures'}, {'type': 'PP', 'start': 87, 'end': 90, 'span': 'for'}, {'type': 'NP', 'start': 91, 'end': 101, 'span': 'September.'}]}

模型局限性以及可能的偏差

本模型基于conll2000数据集上训练，在垂类领域英语文本上的chunking效果会有降低，请用户自行评测后决定如何使用。

训练数据介绍

• conll2000 Chunking英文公开数据集

数据评估及结果

模型在conll2000测试数据评估结果:

相关论文以及引用信息

如果你觉得这个该模型对有所帮助，请考虑引用下面的相关的论文：

@inproceedings{wang-etal-2021-improving,
    title = "Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning",
    author = "Wang, Xinyu  and
      Jiang, Yong  and
      Bach, Nguyen  and
      Wang, Tao  and
      Huang, Zhongqiang  and
      Huang, Fei  and
      Tu, Kewei",
    booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.acl-long.142",
    pages = "1800--1812",
}

@inproceedings{wang-etal-2022-damo,
    title = "{DAMO}-{NLP} at {S}em{E}val-2022 Task 11: A Knowledge-based System for Multilingual Named Entity Recognition",
    author = "Wang, Xinyu  and
      Shen, Yongliang  and
      Cai, Jiong  and
      Wang, Tao  and
      Wang, Xiaobin  and
      Xie, Pengjun  and
      Huang, Fei  and
      Lu, Weiming  and
      Zhuang, Yueting  and
      Tu, Kewei  and
      Lu, Wei  and
      Jiang, Yong",
    booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.semeval-1.200",
    pages = "1457--1468",
}