lexnlp.extract.en.dates: Extracting date references

The lexnlp.extract.en.dates module contains methods that allow for the extraction of dates from text. Sample formats that are handled by this module include:

  • February 1, 1998

  • 2017-06-01

  • 1st day of June, 2017

  • 31 October 2016

  • 15th of March 2000

The full list of current unit test cases can be found here: https://github.com/LexPredict/lexpredict-lexnlp/tree/master/test_data/lexnlp/extract/en/tests/test_dates

Extracting dates

Example

>>> import lexnlp.extract.en.dates
>>> text = "This agreement shall terminate on the 15th day of March, 2020."
>>> print(list(lexnlp.extract.en.dates.get_dates(text)))
[datetime.date(2020, 3, 15)]
>>> text = "This agreement shall terminate on the 2nd of Apr 2030."
>>> print(list(lexnlp.extract.en.dates.get_dates(text)))
[datetime.date(2030, 4, 1)]

Note

This method combines both pattern-matching approaches as well as machine learning and NLP to remove false positive matches. If speed is more important than precision, then users should examine the get_raw_dates method below or train their own model using a smaller feature space or faster machine learning model type. For more details, see the Advanced Usage section below.

Advanced usage and customization

Out of the box, LexNLP uses a cross-validated logistic classifier whose inputs are the one-character and two-character sequence distributions within a 5-character window of the potential date match. The training and assessment data used can be found in train_default_model and unit tests.