mirror of https://github.com/explosion/spaCy.git
Fix formatting and details
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@ -78,7 +78,7 @@
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{ "id": "en", "title": "English", "meta": "50MB" },
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{ "id": "en", "title": "English", "meta": "50MB" },
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{ "id": "de", "title": "German", "meta": "645MB" },
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{ "id": "de", "title": "German", "meta": "645MB" },
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{ "id": "fr", "title": "French", "meta": "1.33GB" },
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{ "id": "fr", "title": "French", "meta": "1.33GB" },
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{ "id": "es", "title": "Spanish", "meta": "378MB"}]
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{ "id": "es", "title": "Spanish", "meta": "377MB"}]
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}
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}
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],
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],
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@ -112,7 +112,7 @@
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{ "id": "fr_depvec_web_lg", "lang": "French", "feats": [1, 1, 0, 1], "size": "1.33 GB", "license": "CC BY-NC" }
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{ "id": "fr_depvec_web_lg", "lang": "French", "feats": [1, 1, 0, 1], "size": "1.33 GB", "license": "CC BY-NC" }
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],
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],
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"es": [
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"es": [
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{ "id": "es_core_web_md", "lang": "Spanish", "feats": [1, 1, 1, 1], "size": "378 MB", "license": "CC BY-SA"}
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{ "id": "es_core_web_md", "lang": "Spanish", "feats": [1, 1, 1, 1], "size": "377 MB", "license": "CC BY-SA"}
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]
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]
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},
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},
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@ -53,7 +53,7 @@ p
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assert ent_francisco == [u'Francisco', u'I', u'GPE']
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assert ent_francisco == [u'Francisco', u'I', u'GPE']
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+table(["Text", "ent_iob", "ent_iob_", "ent_type_", "Description"])
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+table(["Text", "ent_iob", "ent_iob_", "ent_type_", "Description"])
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- var style = [0, 1, 1, 1, 1, 0]
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- var style = [0, 1, 1, 1, 0]
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+annotation-row(["San", 3, "B", "GPE", "beginning of an entity"], style)
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+annotation-row(["San", 3, "B", "GPE", "beginning of an entity"], style)
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+annotation-row(["Francisco", 1, "I", "GPE", "inside an entity"], style)
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+annotation-row(["Francisco", 1, "I", "GPE", "inside an entity"], style)
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+annotation-row(["considers", 2, "O", '""', "outside an entity"], style)
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+annotation-row(["considers", 2, "O", '""', "outside an entity"], style)
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@ -81,7 +81,7 @@ p
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+h(2, "features") Features
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+h(2, "features") Features
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p
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p
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| Across the documentation, you'll come across mentions of spaCy's
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| In the documentation, you'll come across mentions of spaCy's
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| features and capabilities. Some of them refer to linguistic concepts,
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| features and capabilities. Some of them refer to linguistic concepts,
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| while others are related to more general machine learning functionality.
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| while others are related to more general machine learning functionality.
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