[英]How do I train say Tamil names (Tamil ethnicity) as part of Person in Google NLP
In your description you show a demo run of the Natural Language API.在您的描述中,您展示了自然语言 API 的演示运行。 This demo has in its backend a Natural Language model trained with a huge amount of labelled data and you are choosing an entity extraction task.
此演示在其后端有一个自然语言 model 训练有大量标记数据,您正在选择一个实体提取任务。
To use the Natural Language API to perform an entity task you have two options, which you can see if you scroll down a little bit in [1]: Entity Analysis and Custom Entity Extraction.要使用自然语言 API 执行实体任务,您有两个选项,如果您在 [1] 中向下滚动一点可以看到:实体分析和自定义实体提取。
The first option is what you see in the demo, it takes an entity analysis model and performs the task with the input text.第一个选项是您在演示中看到的,它进行实体分析 model 并使用输入文本执行任务。 The labels learned by the model cannot be changed so it's not able to recognize the names Pazhanivel and Kuzhanthaivel.
model 学习的标签无法更改,因此无法识别名称 Pazhanivel 和 Kuzhanthaivel。
The second option is what you are looking for, a custom entity extraction.第二个选项是您正在寻找的,自定义实体提取。 To perform a training with this you can check the quickstart [2].
要使用它进行培训,您可以查看快速入门 [2]。 This implies training a custom entity recognition model which is not a simple task, however with Google Cloud Platform you can launch a model training using only the UI and so it becomes manageable.
这意味着训练自定义实体识别 model 这不是一项简单的任务,但是使用 Google Cloud Platform,您可以仅使用 UI 启动 model 训练,因此它变得易于管理。 Also in the Google Cloud documentation you have explanations about all the steps to prepare the data [3], training models [4] and so on.
此外,在 Google Cloud 文档中,您还对准备数据 [3]、训练模型 [4] 等的所有步骤进行了解释。
Do not hesitate to ask if you have any question.如果您有任何问题,请不要犹豫。
[1] https://cloud.google.com/natural-language/#section-5 [1] https://cloud.google.com/natural-language/#section-5
[2] https://cloud.google.com/natural-language/automl/docs/quickstart [2] https://cloud.google.com/natural-language/automl/docs/quickstart
[3] https://cloud.google.com/natural-language/automl/docs/prepare?_ga=2.66840366.-1201206137.1584215642 [3] https://cloud.google.com/natural-language/automl/docs/prepare?_ga=2.66840366.-1201206137.1584215642
[4] https://cloud.google.com/natural-language/automl/docs/models [4] https://cloud.google.com/natural-language/automl/docs/models
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