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Add parser example to docs
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//- 💫 DOCS > USAGE > TRAINING > TAGGER & PARSER
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+under-construction
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+h(3, "example-train-parser") Updating the parser
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p
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| This example shows how to train spaCy's dependency parser, starting off
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| with an existing model or a blank model. You'll need a set of
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| #[strong training examples] and the respective #[strong heads] and
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| #[strong dependency label] for each token of the example texts.
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+github("spacy", "examples/training/train_parser.py")
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+h(4) Step by step guide
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+list("numbers")
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+item
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| #[strong Load the model] you want to start with, or create an
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| #[strong empty model] using
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| #[+api("spacy#blank") #[code spacy.blank]] with the ID of your
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| language. If you're using a blank model, don't forget to add the
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| parser to the pipeline. If you're using an existing model,
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| make sure to disable all other pipeline components during training
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| using #[+api("language#disable_pipes") #[code nlp.disable_pipes]].
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| This way, you'll only be training the parser.
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+item
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| #[strong Add the dependency labels] to the parser using the
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| #[+api("dependencyparser#add_label") #[code add_label]] method. If
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| you're starting off with a pre-trained spaCy model, this is usually
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| not necessary – but it doesn't hurt either, just to be safe.
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+item
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| #[strong Shuffle and loop over] the examples and create a
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| #[code Doc] and #[code GoldParse] object for each example. Make sure
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| to pass in the #[code heads] and #[code deps] when you create the
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| #[code GoldParse].
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+item
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| For each example, #[strong update the model]
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| by calling #[+api("language#update") #[code nlp.update]], which steps
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| through the words of the input. At each word, it makes a
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| #[strong prediction]. It then consults the annotations provided on the
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| #[code GoldParse] instance, to see whether it was
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| right. If it was wrong, it adjusts its weights so that the correct
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| action will score higher next time.
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+item
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| #[strong Save] the trained model using
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| #[+api("language#to_disk") #[code nlp.to_disk]].
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+item
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| #[strong Test] the model to make sure the parser works as expected.
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+h(3, "training-json") JSON format for training
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@ -80,6 +80,15 @@ include ../_includes/_mixins
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+github("spacy", "examples/training/train_new_entity_type.py")
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+h(3, "parser") Training spaCy's parser
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p
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| This example shows how to update spaCy's dependency parser,
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| starting off with an existing, pre-trained model, or from scratch
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| using a blank #[code Language] class.
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+github("spacy", "examples/training/train_parser.py")
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+h(3, "textcat") Training spaCy's text classifier
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+tag-new(2)
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