es-core-news-sm 3.1.0

Spanish pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.

### Details: https://spacy.io/models/es#es_core_news_sm

Spanish pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.

Feature | Description |

— | — |

Name | es_core_news_sm |

Version | 3.1.0 |

spaCy | >=3.1.0,<3.2.0 |

Default Pipeline | tok2vec, morphologizer, parser, attribute_ruler, lemmatizer, ner |

Components | tok2vec, morphologizer, parser, senter, attribute_ruler, lemmatizer, ner |

Vectors | 0 keys, 0 unique vectors (0 dimensions) |

Sources | [UD Spanish AnCora v2.5](https://github.com/UniversalDependencies/UD_Spanish-AnCora) (Martínez Alonso, Héctor; Zeman, Daniel)<br />[WikiNER](https://figshare.com/articles/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500) (Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, James R Curran)<br />[spaCy lookups data](https://github.com/explosion/spacy-lookups-data) (Explosion) |

License | GNU GPL 3.0 |

Author | [Explosion](https://explosion.ai) |

### Label Scheme

<details>

<summary>View label scheme (414 labels for 4 components)</summary>

</details>

### Accuracy

Type | Score |

— | — |

TOKEN_ACC | 100.00 |

TAG_ACC | 97.29 |

POS_ACC | 98.20 |

MORPH_ACC | 97.74 |

LEMMA_ACC | 98.32 |

DEP_UAS | 90.42 |

DEP_LAS | 86.94 |

SENTS_P | 97.87 |

SENTS_R | 98.97 |

SENTS_F | 98.42 |

ENTS_P | 88.90 |

ENTS_R | 88.98 |

ENTS_F | 88.94 |