From 10742d3219385d52f02e887944cc506599d9d6de Mon Sep 17 00:00:00 2001 From: Ines Montani Date: Sat, 28 Sep 2019 15:57:22 +0200 Subject: [PATCH] Update v2 docs [ci skip] --- website/docs/usage/spacy-101.md | 9 -------- website/docs/usage/v2-2.md | 38 ++++----------------------------- 2 files changed, 4 insertions(+), 43 deletions(-) diff --git a/website/docs/usage/spacy-101.md b/website/docs/usage/spacy-101.md index 12d789410..4bfecb3a9 100644 --- a/website/docs/usage/spacy-101.md +++ b/website/docs/usage/spacy-101.md @@ -238,15 +238,6 @@ of a model, see the usage guides on - - -To learn more about entity linking in spaCy, and how to **train and update** the -entity linker predictions, see the usage guides on -[entity linking](/usage/linguistic-features#entity-linking) and -[training the entity linker](/usage/training#entity-linker). - - - ### Word vectors and similarity {#vectors-similarity model="vectors"} import Vectors101 from 'usage/101/\_vectors-similarity.md' diff --git a/website/docs/usage/v2-2.md b/website/docs/usage/v2-2.md index c429559ad..3b53a3945 100644 --- a/website/docs/usage/v2-2.md +++ b/website/docs/usage/v2-2.md @@ -11,10 +11,10 @@ menu: spaCy v2.2 features improved statistical models, new pretrained models for Norwegian and Lithuanian, better Dutch NER, as well as a new mechanism for storing language data that makes the installation about **15× smaller** on -disk. We've also added a new API for **entity linking**, a new class to -efficiently **serialize annotations**, an improved and 10× faster phrase -matching engine, built-in scoring and **CLI training for text classification** -and a new command to analyze and **debug training data**. For the full +disk. We've also added a new class to efficiently **serialize annotations**, an +improved and **10× faster** phrase matching engine, built-in scoring and +**CLI training for text classification**, a new command to analyze and **debug +training data**, data augmentation during training and more. For the full changelog, see the [release notes on GitHub](https://github.com/explosion/spaCy/releases/tag/v2.2.0). @@ -45,36 +45,6 @@ overall. We've also added new core models for [Norwegian](/models/nb) (MIT) and -### Entity linking API {#entity-linking} - -> #### Example -> -> ```python -> nlp = spacy.load("my_custom_wikidata_model") -> doc = nlp("Ada Lovelace was born in London") -> print([(e.text, e.label_, e.kb_id_) for e in doc.ents]) -> # [('Ada Lovelace', 'PERSON', 'Q7259'), ('London', 'GPE', 'Q84')] -> ``` - -Entity linking lets you ground named entities into the "real world". We're -excited to now provide a built-in API for training entity linking models and -resolving textual entities to unique identifiers from a knowledge base. The -annotated KB identifier is accessible as either a hash value or as a string from -a `Span` or `Token` object. For more details on entity linking in spaCy, check -out -[Sofie's talk](https://www.youtube.com/watch?v=PW3RJM8tDGo&list=PLBmcuObd5An4UC6jvK_-eSl6jCvP1gwXc&index=6) -at spaCy IRL 2019. - - - -**API:** [`EntityLinker`](/api/entitylinker), -[`KnowledgeBase`](/api/knowledgebase) **Code: ** -[`bin/wiki_entity_linking`](https://github.com/explosion/spaCy/tree/master/bin/wiki_entity_linking) -**Usage: ** [Entity linking](/usage/linguistic-features#entity-linking), -[Training an entity linking model](/usage/training#entity-linker) - - - ### Serializable lookup table and dictionary API {#lookups} > #### Example