| [`Doc`](/api/doc) | A container for accessing linguistic annotations. |
| [`Span`](/api/span) | A slice from a `Doc` object. |
| [`Token`](/api/token) | An individual token — i.e. a word, punctuation symbol, whitespace, etc. |
| [`Lexeme`](/api/lexeme) | An entry in the vocabulary. It's a word type with no context, as opposed to a word token. It therefore has no part-of-speech tag, dependency parse etc. |
| [`Language`](/api/language) | A text-processing pipeline. Usually you'll load this once per process as `nlp` and pass the instance around your application. |
| [`Tokenizer`](/api/tokenizer) | Segment text, and create `Doc` objects with the discovered segment boundaries. |
| [`Lemmatizer`](/api/lemmatizer) | Determine the base forms of words. |
| `Morphology` | Assign linguistic features like lemmas, noun case, verb tense etc. based on the word and its part-of-speech tag. |
| [`Tagger`](/api/tagger) | Annotate part-of-speech tags on `Doc` objects. |
| [`DependencyParser`](/api/dependencyparser) | Annotate syntactic dependencies on `Doc` objects. |
| [`EntityRecognizer`](/api/entityrecognizer) | Annotate named entities, e.g. persons or products, on `Doc` objects. |
| [`TextCategorizer`](/api/textcategorizer) | Assign categories or labels to `Doc` objects. |
| [`Matcher`](/api/matcher) | Match sequences of tokens, based on pattern rules, similar to regular expressions. |
| [`PhraseMatcher`](/api/phrasematcher) | Match sequences of tokens based on phrases. |
| [`EntityRuler`](/api/entityruler) | Add entity spans to the `Doc` using token-based rules or exact phrase matches. |
| [`Sentencizer`](/api/sentencizer) | Implement custom sentence boundary detection logic that doesn't require the dependency parse. |
| [Other functions](/api/pipeline-functions) | Automatically apply something to the `Doc`, e.g. to merge spans of tokens. |
