Data loaders and abstractions for text and NLP


>>> pos = data.TabularDataset( ... path='data/pos/pos_wsj_train.tsv', format='tsv', ... fields=[('text', data.Field()), ... ('labels', data.Field())]) ... >>> sentiment = data.TabularDataset( ... path='data/sentiment/train.json', format='json', ... fields={'sentence_tokenized': ('text', data.Field(sequential=True)), ... 'sentiment_gold': ('labels', data.Field(sequential=False))})
Author info


Categories standalone research

Submit your project

If you have a project that you want the spaCy community to make use of, you can suggest it by submitting a pull request to the spaCy website repository. The Universe database is open-source and collected in a simple JSON file. For more details on the formats and available fields, see the documentation. Looking for inspiration your own spaCy plugin or extension? Check out the project idea label on the issue tracker.

Read the docsJSON source