spaCy NER model for Spanish trained with interviews in the domain of tourism related to the Way of Saint Jacques. It recognizes four types of entities: location (LOC), organizations (ORG), person (PER) and miscellaneous (MISC).
1import spacy
2from spacy.pipeline import merge_entities
3
4
5nlp = spacy.load("es_spacy_ner_cds")
6nlp.add_pipe('sentencizer')
7
8example = "Fue antes de llegar a Sigüeiro, en el Camino de Santiago. El proyecto lo financia el Ministerio de Industria y Competitividad."
9ner_pipe = nlp(example)
10
11print(ner_pipe.ents)
12for token in merge_entities(ner_pipe):
13 print(token.text, token.ent_type_)
