You can use this model in the Extract Entities Using Deep Learning tool available in the GeoAI toolbox in ArcGIS Pro. Follow the steps below to use the model.
Extract Entities
Complete the following steps to extract entities from the text files:
- Download the Named Entity Recognition model from ArcGIS Living Atlas of the World.
- Browse to Tools on the Analysis tab.
- Click the Toolboxes tab in the Geoprocessing pane, select GeoAI Tools, and browse to the Extract Entities Using Deep Learning tool under Text Analysis.
- Set the variables on the Parameters tab as follows:
- Input Folder—The folder containing the text files on which named entity extraction will be performed.
- Output Table—The output feature class or table that will contain the extracted entities. If a locator is provided and the model extracts addresses, the feature class will be produced by geocoding the extracted addresses.
- Model Definition—Select the pretrained or fine-tuned model .dlpk file.
- Model Arguments (optional)—Change the values of the arguments if
required.
- Sequence_length—Maximum sequence length (at subword level after tokenization) of the training data to be considered for training the model. This is applicable only for models with HuggingFace transformer backbones. The default value is 512.
- To geocode the extracted location entity, use the Advanced options:
- Batch Size—Increasing the batch size can improve tool performance; however, as the batch size increases, more memory is used.
- Location Zone—The geographic region or zone in which the addresses are expected to be located.
- Input Locator—The locator that will be used to geocode addresses found in the input text documents.
- Set the variables on the Environments tab by selecting Processor Type as CPU or GPU.
It is recommended that you select GPU, if available, and set GPU ID to the GPU to be used.
- Click Run.
When processing finishes, the output layer or table is added to the map. Click Attribute Table to see the output.
