mirror of https://github.com/explosion/spaCy.git
Added asent to spacy universe (#11078)
* Added asent to spacy universe * Update addition of asent following correction
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@ -1120,6 +1120,46 @@
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"category": ["pipeline", "models", "training"],
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"tags": ["pipeline", "models", "transformers"]
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},
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{
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"id": "asent",
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"title": "Asent",
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"slogan": "Fast, flexible and transparent sentiment analysis",
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"description": "Asent is a rule-based sentiment analysis library for Python made using spaCy. It is inspired by VADER, but uses a more modular ruleset, that allows the user to change e.g. the method for finding negations. Furthermore it includes visualisers to visualize the model predictions, making the model easily interpretable.",
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"github": "kennethenevoldsen/asent",
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"pip": "aseny",
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"code_example": [
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"import spacy",
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"import asent",
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"",
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"# load spacy pipeline",
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"nlp = spacy.blank('en')",
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"nlp.add_pipe('sentencizer')",
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"",
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"# add the rule-based sentiment model",
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"nlp.add_pipe('asent_en_v1')",
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"",
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"# try an example",
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"text = 'I am not very happy, but I am also not especially sad'",
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"doc = nlp(text)",
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"",
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"# print polarity of document, scaled to be between -1, and 1",
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"print(doc._.polarity)",
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"# neg=0.0 neu=0.631 pos=0.369 compound=0.7526",
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"",
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"# Naturally, a simple score can be quite unsatisfying, thus Asent implements a series of visualizer to interpret the results:",
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"asent.visualize(doc, style='prediction')",
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" # or",
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"asent.visualize(doc[:5], style='analysis')"
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],
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"thumb": "https://github.com/KennethEnevoldsen/asent/raw/main/docs/img/logo_black_font.png?raw=true",
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"author": "Kenneth Enevoldsen",
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"author_links": {
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"github": "KennethEnevoldsen",
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"website": "https://www.kennethenevoldsen.com"
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},
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"category": ["pipeline", "models"],
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"tags": ["pipeline", "models", "sentiment"]
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},
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{
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"id": "textdescriptives",
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"title": "TextDescriptives",
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