from spacy import displacy
%run ./Practica1ObligatoriaRIMT_1819.py
Prepared 22 documents. They can be accessed using or_texts[n], being n an integer from 0 to 21. Distribution of documents by language after translation: {'en': 22} Unique terms found: 3538 Named entities found: 176 Vectors created. Test: [4 5 0 0 0 2 0 0 0 1 4 4 2 2 1 0 2 4 1 1 1 3] Reference: [0, 5, 2, 2, 2, 3, 2, 2, 2, 4, 0, 0, 3, 3, 4, 2, 3, 0, 4, 4, 4, 1] Adjusted Rand Index: 1.0
displacy.render(nlp(or_texts[3])[0:50], style = 'ent', jupyter = True)
displacy.render(nlp(or_texts[4])[0:50], style = 'ent', jupyter = True)
displacy.render(nlp(or_texts[0])[0:50], style = 'ent', jupyter = True)