mirror of https://github.com/explosion/spaCy.git
Add multiple packages to universe.json (#3809) [ci skip]
* Add multiple packages to universe.json Added following packages: NLPArchitect, NLPRe, Chatterbot, alibi, NeuroNER * Auto-format * Update slogan (probably just copy-paste mistake) * Adjust formatting * Update tags / categories
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Nirant
Ines Montani
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86eb817b74
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@ -1,22 +1,106 @@
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{
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{
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"resources": [
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"resources": [
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{
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"id": "nlp-architect",
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"title": "NLP Architect",
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"slogan": "Python lib for exploring Deep NLP & NLU by Intel AI",
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"github": "NervanaSystems/nlp-architect",
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"pip": "nlp-architect",
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"thumb": "https://raw.githubusercontent.com/NervanaSystems/nlp-architect/master/assets/nlp_architect_logo.png",
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"code_example": [],
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"category": ["standalone", "research"],
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"tags": ["pytorch"]
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},
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{
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"id": "NeuroNER",
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"title": "NeuroNER",
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"slogan": "Named-entity recognition using neural networks",
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"github": "Franck-Dernoncourt/NeuroNER",
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"pip": "pyneuroner[cpu]",
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"thumb": "",
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"code_example": [
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"from neuroner import neuromodel",
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"nn = neuromodel.NeuroNER(train_model=False, use_pretrained_model=True)"
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],
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"category": ["ner"],
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"tags": ["standalone"]
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},
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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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"github": "NIHOPA/NLPre",
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"pip": "nlpre",
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"thumb": "",
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"code_example": [
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"from nlpre import titlecaps, dedash, identify_parenthetical_phrases",
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"from nlpre import replace_acronyms, replace_from_dictionary",
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"ABBR = identify_parenthetical_phrases()(text)",
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"parsers = [dedash(), titlecaps(), replace_acronyms(ABBR),",
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" replace_from_dictionary(prefix='MeSH_')]",
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"for f in parsers:",
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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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"tags": []
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},
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{
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"id": "Chatterbot",
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"title": "Chatterbot",
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"slogan": "A machine-learning based conversational dialog engine for creating chat bots",
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"github": "gunthercox/ChatterBot",
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"pip": "chatterbot",
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"thumb": "https://chatterbot.readthedocs.io/en/stable/_images/banner.png",
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"code_example": [
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"from chatterbot import ChatBot",
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"from chatterbot.trainers import ListTrainer",
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"# Create a new chat bot named Charlie",
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"chatbot = ChatBot('Charlie')",
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"trainer = ListTrainer(chatbot)",
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"trainer.train([",
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"'Hi, can I help you?',",
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"'Sure, I would like to book a flight to Iceland.",
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"'Your flight has been booked.'",
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"])",
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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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"category": ["conversational", "standalone"],
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"tags": ["chatbots"]
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},
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{
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{
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"id": "saber",
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"id": "saber",
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"title": "saber",
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"title": "saber",
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"slogan": "deep-learning based tool for information extraction in the biomedical domain",
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"slogan": "Deep-learning based tool for information extraction in the biomedical domain",
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"github": "BaderLab/saber",
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"github": "BaderLab/saber",
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"pip": "saber",
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"pip": "saber",
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"thumb": "https://raw.githubusercontent.com/BaderLab/saber/master/docs/img/saber_logo.png",
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"thumb": "https://raw.githubusercontent.com/BaderLab/saber/master/docs/img/saber_logo.png",
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"code_example": [
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"code_example": [
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">>> from saber.saber import Saber",
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"from saber.saber import Saber",
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">>> saber = Saber()",
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"saber = Saber()",
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">>> saber.load('PRGE')",
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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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"saber.annotate('The phosphorylation of Hdm2 by MK2 promotes the ubiquitination of p53.')"
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],
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],
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"category": ["research", "biomedical"],
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"category": ["research"],
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"tags": ["keras"]
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"tags": ["keras", "biomedical"]
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},
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{
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"id": "alibi",
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"title": "alibi",
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"slogan": "Algorithms for monitoring and explaining machine learning models ",
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"github": "SeldonIO/alibi",
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"pip": "alibi",
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"thumb": "https://docs.seldon.io/projects/alibi/en/v0.2.0/_static/Alibi_Logo.png",
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"code_example": [
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">>> from alibi.explainers import AnchorTabular",
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">>> explainer = AnchorTabular(predict_fn, feature_names)",
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">>> explainer.fit(X_train)",
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">>> explainer.explain(x)"
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],
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"category": ["standalone", "research"],
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"tags": []
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},
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},
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{
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{
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"id": "spacymoji",
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"id": "spacymoji",
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"slogan": "Emoji handling and meta data as a spaCy pipeline component",
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"slogan": "Emoji handling and meta data as a spaCy pipeline component",
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