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Display single text outputs

If you are

  • Developping a new component
  • Testing various inputs on an existing component
  • ...

you might want to quickly apply a pipeline and display the output doc in a comprehensible way.

from edsnlp.viz import QuickExample

E = QuickExample(nlp)  # (1)
  1. This is the Language instance that should be defined beforehands

Next, simply call E with any string:

txt = "Le patient présente une anomalie."
E(txt)
                              Le patient présente une anomalie                               
                                                                                             
┏━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ Entity    Source    eds.hypoth…  eds.negation  eds.family  eds.history  eds.report… ┃
┡━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│ patient  │ patient  │ FalseFalseFalseFalseFalse       │
│ anomalie │ anomalie │ FalseFalseFalseFalseFalse       │
└──────────┴──────────┴─────────────┴──────────────┴────────────┴─────────────┴─────────────┘

By default, each Qualifiers in nlp adds a corresponding column to the output. Additionnal informations can be displayed by using the extensions parameter. For instance, if entities have a custom ent._.custom_ext extensions, it can be displayed by providing the extension when instantiating QuickExample:

E = QuickExample(nlp, extensions=["_.custom_ext"])

Finally, if you prefer to output a DataFrame instead of displaying a table, set the as_dataframe parameter to True:

E = QuickExample(nlp)
E(txt, as_dataframe=True)