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43 lines
1.6 KiB
Plaintext
43 lines
1.6 KiB
Plaintext
//- 💫 DOCS > USAGE > LINGUISTIC FEATURES
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include ../_includes/_mixins
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p
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| Processing raw text intelligently is difficult: most words are rare, and
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| it's common for words that look completely different to mean almost the
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| same thing. The same words in a different order can mean something
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| completely different. Even splitting text into useful word-like units can
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| be difficult in many languages. While it's possible to solve some
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| problems starting from only the raw characters, it's usually better to
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| use linguistic knowledge to add useful information. That's exactly what
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| spaCy is designed to do: you put in raw text, and get back a
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| #[+api("doc") #[code Doc]] object, that comes with a variety of
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| annotations.
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+section("pos-tagging")
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+h(2, "pos-tagging") Part-of-speech tagging
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+tag-model("tagger", "dependency parse")
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include _linguistic-features/_pos-tagging
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+section("dependency-parse")
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+h(2, "dependency-parse") Dependency parsing
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+tag-model("dependency parse")
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include _linguistic-features/_dependency-parse
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+section("named-entities")
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+h(2, "named-entities") Named Entities
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+tag-model("named entities")
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include _linguistic-features/_named-entities
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+section("tokenization")
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+h(2, "tokenization") Tokenization
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include _linguistic-features/_tokenization
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+section("sbd")
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+h(2, "sbd") Sentence Segmentation
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include _linguistic-features/_sentence-segmentation
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+section("rule-based-matching")
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+h(2, "rule-based-matching") Rule-based matching
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include _linguistic-features/_rule-based-matching
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