Right now, the integration test use the movie dataset. This is an issue because this dataset is unnessecarily big for testing purpose and thus drastically slows down running the test suite. I suggest we use a smaller dataset (< 100 entries) to improve our CI time.

While this isn't really a huge problem, you may wish to reformat your docstrings according to the established formats.

PEP 287 recommends that reST (reStructuredText) format be used, but Epytext is popular as well - They're used because Python IDEs are often able to parse them to get more information about

Dear OpenSearchServer!

I have found an issue, server cannot deserialize json.

Can not deserialize instance of java.lang.String out of START_OBJECT token
at [Source: org.apache.cxf.transport.http.AbstractHTTPDestination$1@147bba9; line: 2, column: 5](through reference chain: com.jaeksoft.searchlib.webservice.query.search.SearchPatternQuery["query"])

I used the provided sample, found in the

spacy

• A tour of awesome features of spaCy (part 1/2) - https://medium.com/eliiza-ai/a-tour-of-awesome-features-of-spacy-part-1-2-58b32425954f
• A tour of awesome features of spaCy (part 2/2) - https://medium.com/eliiza-ai/a-tour-of-awesome-features-of-spacy-part-2-2-d7bd628a81ce
• How to Train NER with Custom training data using spaCy. https://medium.com/@manivannan_data/how-to-train-

When configuring Anonimatron, it is not always obvious what options there are for generating synonyms. It would help if Anonimatron could print out all available anonymizers with example input/output values.

Interesting consideration: Show the reduction in address space (replacing a 100 character free text field with a roman name would reduce the possibilities of unique target values by orders

I imagine that there would be some application of deriving synonyms of words to assist in parts of text analysis, but I do not work in this area. Perhaps @juliasilge @dgrtwo or @kbenoit might have an idea?