mirror of https://github.com/explosion/spaCy.git
Update universe [ci skip]
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@ -26,7 +26,7 @@
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{
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"id": "NLPre",
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"title": "NLPre",
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"slogan": "Natural Language Preprocessing Library in Health data",
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"slogan": "Natural Language Preprocessing Library for health data and more",
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"github": "NIHOPA/NLPre",
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"pip": "nlpre",
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"code_example": [
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@ -39,7 +39,7 @@
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" text = f(text)",
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"print(text)"
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],
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"category": ["standalone"]
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"category": ["scientific"]
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},
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{
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"id": "Chatterbot",
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@ -62,6 +62,10 @@
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"",
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"response = chatbot.get_response('I would like to book a flight.')"
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],
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"author": "Gunther Cox",
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"author_links": {
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"github": "gunthercox"
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},
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"category": ["conversational", "standalone"],
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"tags": ["chatbots"]
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},
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@ -78,7 +82,8 @@
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"saber.load('PRGE')",
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"saber.annotate('The phosphorylation of Hdm2 by MK2 promotes the ubiquitination of p53.')"
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],
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"category": ["research"],
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"author": "Bader Lab, University of Toronto",
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"category": ["scientific"],
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"tags": ["keras", "biomedical"]
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},
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{
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@ -94,6 +99,7 @@
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"explainer.fit(X_train)",
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"explainer.explain(x)"
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],
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"author": "Seldon",
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"category": ["standalone", "research"]
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},
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{
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@ -239,7 +245,7 @@
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"doc = nlp(my_doc_text)"
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],
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"author": "tc64",
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"author_link": {
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"author_links": {
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"github": "tc64"
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},
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"category": ["pipeline"]
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@ -442,7 +448,7 @@
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"author_links": {
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"github": "huggingface"
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},
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"category": ["standalone", "conversational"],
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"category": ["standalone", "conversational", "models"],
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"tags": ["coref"]
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},
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{
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@ -634,7 +640,7 @@
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"twitter": "allenai_org",
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"website": "http://allenai.org"
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},
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"category": ["models", "research"]
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"category": ["scientific", "models", "research"]
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},
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{
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"id": "textacy",
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@ -697,7 +703,7 @@
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"github": "ahalterman",
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"twitter": "ahalterman"
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},
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"category": ["standalone"]
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"category": ["standalone", "scientific"]
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},
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{
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"id": "kindred",
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@ -722,7 +728,7 @@
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"author_links": {
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"github": "jakelever"
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},
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"category": ["standalone"]
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"category": ["standalone", "scientific"]
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},
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{
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"id": "sense2vec",
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@ -990,6 +996,23 @@
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"author": "Aaron Kramer",
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"category": ["courses"]
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},
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{
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"type": "education",
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"id": "spacy-course",
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"title": "Advanced NLP with spaCy",
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"slogan": "spaCy, 2019",
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"description": "In this free interactive course, you'll learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.",
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"url": "https://course.spacy.io",
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"image": "https://i.imgur.com/JC00pHW.jpg",
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"thumb": "https://i.imgur.com/5RXLtrr.jpg",
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"author": "Ines Montani",
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"author_links": {
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"twitter": "_inesmontani",
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"github": "ines",
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"website": "https://ines.io"
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},
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"category": ["courses"]
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},
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{
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"type": "education",
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"id": "video-spacys-ner-model",
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@ -1150,7 +1173,7 @@
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"github": "ecohealthalliance",
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"website": " https://ecohealthalliance.org/"
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},
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"category": ["research", "standalone"]
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"category": ["scientific", "standalone"]
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},
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{
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"id": "self-attentive-parser",
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@ -1472,7 +1495,7 @@
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"url": "https://github.com/msg-systems/holmes-extractor",
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"description": "Holmes is a Python 3 library that supports a number of use cases involving information extraction from English and German texts, including chatbot, structural search, topic matching and supervised document classification.",
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"pip": "holmes-extractor",
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"category": ["conversational", "research", "standalone"],
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"category": ["conversational", "standalone"],
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"tags": ["chatbots", "text-processing"],
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"code_example": [
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"import holmes_extractor as holmes",
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@ -1511,6 +1534,11 @@
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"title": "Research",
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"description": "Frameworks and utilities for developing better NLP models, especially using neural networks"
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},
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{
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"id": "scientific",
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"title": "Scientific",
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"description": "Frameworks and utilities for scientific text processing"
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},
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{
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"id": "visualizers",
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"title": "Visualizers",
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@ -1530,6 +1558,11 @@
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"id": "standalone",
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"title": "Standalone",
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"description": "Self-contained libraries or tools that use spaCy under the hood"
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},
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{
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"id": "models",
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"title": "Models",
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"description": "Third-party pre-trained models for different languages and domains"
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}
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]
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},
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