Edits to spacy-101 page

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Matthew Honnibal 2017-06-04 13:10:27 +02:00
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commit f2c4a9f690

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@ -65,13 +65,15 @@ p
| not designed specifically for chat bots, and only provides the | not designed specifically for chat bots, and only provides the
| underlying text processing capabilities. | underlying text processing capabilities.
+item #[strong spaCy is not research software]. +item #[strong spaCy is not research software].
| It's is built on the latest research, but unlike | It's is built on the latest research, but it's designed to get
| #[+a("https://github./nltk/nltk") NLTK], which is intended for | things done. This leads to fairly different design decisions than
| teaching and research, spaCy follows a more opinionated approach and | #[+a("https://github./nltk/nltk") NLTK]
| focuses on production usage. Its aim is to provide you with the best | or #[+a("https://stanfordnlp.github.io/CorenlP") CoreNLP], which were
| possible general-purpose solution for text processing and machine learning | created as platforms for teaching and research. The main difference
| with text input but this also means that there's only one implementation | is that spaCy is integrated and opinionated. We try to avoid asking
| of each component. | the user to choose between multiple algorithms that deliver equivalent
| functionality. Keeping our menu small lets us deliver generally better
| performance and developer experience.
+item #[strong spaCy is not a company]. +item #[strong spaCy is not a company].
| It's an open-source library. Our company publishing spaCy and other | It's an open-source library. Our company publishing spaCy and other
| software is called #[+a(COMPANY_URL, true) Explosion AI]. | software is called #[+a(COMPANY_URL, true) Explosion AI].
@ -79,7 +81,7 @@ p
+h(2, "features") Features +h(2, "features") Features
p p
| Across the documentations, you'll come across mentions of spaCy's | Across the documentation, you'll come across mentions of spaCy's
| features and capabilities. Some of them refer to linguistic concepts, | features and capabilities. Some of them refer to linguistic concepts,
| while others are related to more general machine learning functionality. | while others are related to more general machine learning functionality.
@ -171,7 +173,9 @@ p
p p
| Even though a #[code Doc] is processed e.g. split into individual words | Even though a #[code Doc] is processed e.g. split into individual words
| and annotated it still holds #[strong all information of the original text], | and annotated it still holds #[strong all information of the original text],
| like whitespace characters. This way, you'll never lose any information | like whitespace characters. You can always get the offset of a token into the
| original string, or reconstruct the original by joining the tokens and their
| trailing whitespace. This way, you'll never lose any information
| when processing text with spaCy. | when processing text with spaCy.
+h(3, "annotations-token") Tokenization +h(3, "annotations-token") Tokenization