README.md

🪐 spaCy Project: Demo NER in a new pipeline (Named Entity Recognition)

A minimal demo NER project for spaCy v3 adapted from the spaCy v2 train_ner.py example script for creating an NER component in a new pipeline.

📋 project.yml

The project.yml defines the data assets required by the project, as well as the available commands and workflows. For details, see the spaCy projects documentation.

⏯ Commands

The following commands are defined by the project. They can be executed using spacy project run [name]. Commands are only re-run if their inputs have changed.

Command	Description
download	Download a spaCy model with pretrained vectors
convert	Convert the data to spaCy's binary format
create-config	Create a new config with an NER pipeline component
train	Train the NER model
train-with-vectors	Train the NER model with vectors
evaluate	Evaluate the model and export metrics
package	Package the trained model as a pip package
visualize-model	Visualize the model's output interactively using Streamlit

⏭ Workflows

The following workflows are defined by the project. They can be executed using spacy project run [name] and will run the specified commands in order. Commands are only re-run if their inputs have changed.

Workflow	Steps
all	convert → create-config → train → evaluate

🗂 Assets

The following assets are defined by the project. They can be fetched by running spacy project assets in the project directory.

File	Source	Description
assets/train.json	Local	Demo training data converted from the v2 train_ner.py example with srsly.write_json("train.json", TRAIN_DATA)
assets/dev.json	Local	Demo development data