mirror of https://github.com/explosion/spaCy.git
306 lines
12 KiB
JSON
306 lines
12 KiB
JSON
{
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"sidebar": {
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"Get started": {
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"Installation": "./",
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"Lightning tour": "lightning-tour"
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},
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"Workflows": {
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"Loading the pipeline": "language-processing-pipeline",
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"Processing text": "processing-text",
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"spaCy's data model": "data-model",
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"Using the parse": "dependency-parse",
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"Custom pipelines": "customizing-pipeline",
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"Rule-based matching": "rule-based-matching",
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"Word vectors": "word-vectors-similarities",
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"Deep learning": "deep-learning",
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"Custom tokenization": "customizing-tokenizer",
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"Training": "training"
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},
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"Examples": {
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"Tutorials": "tutorials",
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"Showcase": "showcase"
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}
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},
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"index": {
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"title": "Install spaCy",
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"next": "lightning-tour"
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},
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"lightning-tour": {
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"title": "Lightning tour"
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},
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"language-processing-pipeline": {
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"title": "Loading a language processing pipeline",
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"next": "processing-text"
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},
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"customizing-pipeline": {
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"title": "Customizing the pipeline",
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"next": "customizing-tokenizer"
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},
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"processing-text": {
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"title": "Processing text",
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"next": "data-model"
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},
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"data-model": {
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"title": "Understanding spaCy's data model"
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},
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"dependency-parse": {
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"title": "Using the dependency parse"
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},
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"rule-based-matching": {
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"title": "Rule-based matching"
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},
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"word-vectors-similarities": {
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"title": "Using word vectors and semantic similarities"
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},
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"deep-learning": {
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"title": "Hooking a deep learning model into spaCy"
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},
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"customizing-tokenizer": {
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"title": "Customizing the tokenizer",
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"next": "training"
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},
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"training": {
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"title": "Training the tagger, parser and entity recognizer"
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},
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"showcase": {
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"title": "Showcase",
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"libraries": {
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"spacy-nlp": {
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"url": "https://github.com/kengz/spacy-nlp",
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"author": "Wah Loon Keng",
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"description": "Expose spaCy NLP text parsing to Node.js (and other languages) via Socket.IO."
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},
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"spacy-api-docker": {
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"url": "https://github.com/jgontrum/spacy-api-docker",
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"author": "Johannes Gontrum",
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"description": "spaCy accessed by a REST API, wrapped in a Docker container."
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},
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"textacy": {
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"url": "https://github.com/chartbeat-labs/textacy",
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"author": " Burton DeWilde (Chartbeat)",
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"description": "Higher-level NLP built on spaCy."
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},
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"visual-qa": {
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"url": "https://github.com/avisingh599/visual-qa",
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"author": "Avi Singh",
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"description": "Keras-based LSTM/CNN models for Visual Question Answering."
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}
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},
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"visualizations": {
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"displaCy": {
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"url": "https://demos.explosion.ai/displacy",
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"author": "Ines Montani",
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"description": "An open-source NLP visualiser for the modern web.",
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"image": "displacy.jpg"
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},
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"displaCy ENT": {
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"url": "https://demos.explosion.ai/displacy-ent",
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"author": "Ines Montani",
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"description": "An open-source named entity visualiser for the modern web.",
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"image": "displacy-ent.jpg"
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}
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},
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"products": {
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"sense2vec": {
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"url": "https://demos.explosion.ai/sense2vec",
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"author": "Matthew Honnibal and Ines Montani",
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"description": "Semantic analysis of the Reddit hivemind.",
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"image": "sense2vec.jpg"
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},
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"TruthBot": {
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"url": "http://summerscope.github.io/govhack/2016/truthbot/",
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"author": "Team Truthbot",
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"description": "The world's first artificially intelligent fact checking robot.",
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"image": "truthbot.jpg"
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},
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"Laice": {
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"url": "https://github.com/kendricktan/laice",
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"author": "Kendrick Tan",
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"description": "Train your own Natural Language Processor from a browser.",
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"image": "laice.jpg"
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},
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"FoxType": {
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"url": "https://foxtype.com",
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"description": "Smart tools for writers.",
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"image": "foxtype.jpg"
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},
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"Kip": {
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"url": "https://kipthis.com",
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"description": "An AI chat assistant for group shopping.",
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"image": "kip.jpg"
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},
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"Indico": {
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"url": "https://indico.io",
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"description": "Text and image analysis powered by Machine Learning.",
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"image": "indico.jpg"
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},
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"TextAnalysisOnline": {
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"url": "http://textanalysisonline.com",
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"description": "Online tool for spaCy's tokenizer, parser, NER and more.",
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"image": "textanalysis.jpg"
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}
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},
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"books": {
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"Introduction to Machine Learning with Python: A Guide for Data Scientists": {
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"url": "https://books.google.de/books?id=vbQlDQAAQBAJ",
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"author": "Andreas C. Müller and Sarah Guido (O'Reilly, 2016)",
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"description": "Andreas is a lead developer of Scikit-Learn, and Sarah is a lead data scientist at Mashable. We're proud to get a mention."
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}
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},
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"research": {
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"Refactoring the Genia Event Extraction Shared Task Toward a General Framework for IE-Driven KB Development": {
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"url": "https://www.semanticscholar.org/paper/Refactoring-the-Genia-Event-Extraction-Shared-Task-Kim-Wang/06d94b64a7bd2d3433f57caddad5084435d6a91f",
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"author": "Jin-Dong Kim et al. (2016)"
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},
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"Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec": {
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"url": "https://www.semanticscholar.org/paper/Mixing-Dirichlet-Topic-Models-and-Word-Embeddings-Moody/bf8116e06f7b498c6abfbf97aeb67d0838c08609",
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"author": "Christopher E. Moody (2016)"
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},
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"Predicting Pre-click Quality for Native Advertisements": {
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"url": "https://www.semanticscholar.org/paper/Predicting-Pre-click-Quality-for-Native-Zhou-Redi/564985430ff2fbc3a9daa9c2af8997b7f5046da8",
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"author": "Ke Zhou et al. (2016)"
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},
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"Threat detection in online discussions": {
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"url": "https://www.semanticscholar.org/paper/Threat-detection-in-online-discussions-Wester-%C3%98vrelid/f4150e2fb4d8646ebc2ea84f1a86afa1b593239b",
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"author": "Aksel Wester et al. (2016)"
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},
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"The language of mental health problems in social media": {
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"url": "https://www.semanticscholar.org/paper/The-language-of-mental-health-problems-in-social-Gkotsis-Oellrich/537db6c2984514d92a754a591841e2e20845985a",
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"author": "George Gkotsis et al. (2016)"
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}
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}
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},
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"tutorials": {
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"title": "Tutorials",
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"next": "showcase",
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"first_steps": {
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"Setting up an NLP environment with Python": {
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"url": "https://shirishkadam.com/2016/10/06/setting-up-natural-language-processing-environment-with-python/",
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"author": "Shirish Kadam"
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},
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"NLP with spaCy in 10 lines of code": {
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"url": "https://github.com/cytora/pycon-nlp-in-10-lines",
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"author": "Andraz Hribernik et al. (Cytora)",
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"tags": [ "jupyter" ]
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},
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"Intro to NLP with spaCy": {
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"url": "https://nicschrading.com/project/Intro-to-NLP-with-spaCy/",
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"author": "J Nicolas Schrading"
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},
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"NLP with spaCy and IPython Notebook": {
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"url": "http://blog.sharepointexperience.com/2016/01/nlp-and-sharepoint-part-1/",
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"author": "Dustin Miller (SharePoint)",
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"tags": [ "jupyter" ]
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},
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"Getting Started with spaCy": {
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"url": "http://textminingonline.com/getting-started-with-spacy",
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"author": "TextMiner"
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},
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"spaCy – A fast natural language processing library": {
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"url": "https://bjoernkw.com/2015/11/22/spacy-a-fast-natural-language-processing-library/",
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"author": "Björn Wilmsmann"
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},
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"NLP (almost) From Scratch - POS Network with spaCy": {
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"url": "http://sujitpal.blogspot.de/2016/07/nlp-almost-from-scratch-implementing.html",
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"author": "Sujit Pal",
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"tags": [ "gensim", "keras" ]
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},
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"NLP tasks with various libraries": {
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"url": "http://clarkgrubb.com/nlp",
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"author": "Clark Grubb"
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},
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"A very (very) short primer on spacy.io": {
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"url": "http://blog.milonimrod.com/2015/10/a-very-very-short-primer-on-spacyio.html",
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"author": "Nimrod Milo "
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}
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},
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"deep_dives": {
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"Deep Learning with custom pipelines and Keras": {
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"url": "https://explosion.ai/blog/spacy-deep-learning-keras",
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"author": "Matthew Honnibal",
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"tags": [ "keras", "sentiment" ]
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},
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"A decomposable attention model for Natural Language Inference": {
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"url": "https://github.com/explosion/spaCy/tree/master/examples/keras_parikh_entailment",
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"author": "Matthew Honnibal",
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"tags": [ "keras", "similarity" ]
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},
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"Using the German model": {
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"url": "https://explosion.ai/blog/german-model",
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"author": "Wolfgang Seeker",
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"tags": [ "multi-lingual" ]
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},
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"Sense2vec with spaCy and Gensim": {
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"url": "https://explosion.ai/blog/sense2vec-with-spacy",
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"author": "Matthew Honnibal",
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"tags": [ "big data", "gensim" ]
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},
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"Building your bot's brain with Node.js and spaCy": {
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"url": "https://explosion.ai/blog/chatbot-node-js-spacy",
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"author": "Wah Loon Keng",
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"tags": [ "bots", "node.js" ]
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},
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"An intent classifier with spaCy": {
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"url": "http://blog.themusio.com/2016/07/18/musios-intent-classifier-2/",
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"author": "Musio",
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"tags": [ "bots", "keras" ]
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},
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"Visual Question Answering with spaCy": {
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"url": "http://iamaaditya.github.io/2016/04/visual_question_answering_demo_notebook",
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"author": "Aaditya Prakash",
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"tags": [ "vqa", "keras" ]
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}
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},
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"code": {
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"Information extraction": {
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"url": "https://github.com/explosion/spaCy/blob/master/examples/information_extraction.py",
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"author": "Matthew Honnibal",
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"tags": [ "snippet" ]
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},
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"Neural bag of words": {
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"url": "https://github.com/explosion/spaCy/blob/master/examples/nn_text_class.py",
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"author": "Matthew Honnibal",
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"tags": [ "sentiment" ]
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},
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"Part-of-speech tagging": {
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"url": "https://github.com/explosion/spaCy/blob/master/examples/pos_tag.py",
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"author": "Matthew Honnibal",
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"tags": [ "pos" ]
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},
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"Parallel parse": {
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"url": "https://github.com/explosion/spaCy/blob/master/examples/parallel_parse.py",
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"author": "Matthew Honnibal",
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"tags": [ "big data" ]
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},
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"Inventory count": {
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"url": "https://github.com/explosion/spaCy/tree/master/examples/inventory_count",
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"author": "Oleg Zd"
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},
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"Multi-word matches": {
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"url": "https://github.com/explosion/spaCy/blob/master/examples/multi_word_matches.py",
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"author": "Matthew Honnibal",
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"tags": [ "matcher", "out of date" ]
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}
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}
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}
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}
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