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doc: Fix minor mistakes

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mpuels 2017-12-13 11:37:24 +01:00 committed by GitHub
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website/usage/_training/_tagger-parser.jade
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@ -95,11 +95,11 @@ p
+h(3, "intent-parser") Training a parser for custom semantics
p
| spaCy's parser component can be used to trained to predict any type
| spaCy's parser component can be used to be trained to predict any type
| of tree structure over your input text – including
| #[strong semantic relations] that are not syntactic dependencies. This
| can be useful to for #[strong conversational applications], which need to
| predict trees over whole documents or chat logs, with connections between
| predict trees over whole documents or chat logs, with connections between
| the sentence roots used to annotate discourse structure. For example, you
| can train spaCy's parser to label intents and their targets, like
| attributes, quality, time and locations. The result could look like this:
@ -132,7 +132,7 @@ p
| to do this automatically – just make sure to add it #[code before='parser'].
p
| The following example example shows a full implementation of a training
| The following example shows a full implementation of a training
| loop for a custom message parser for a common "chat intent": finding
| local businesses. Our message semantics will have the following types
| of relations: #[code ROOT], #[code PLACE], #[code QUALITY],