Profanity analyzer
WebbWe're creating the world's largest profanity dataset, in 20+ languages. Dataset This repo contains 1600+ popular English profanities and their variations. Columns. text: the … Webb9 aug. 2024 · Profanity: term-based matching with built-in list of profane terms in various languages Classification: machine-assisted classification into three categories Personal data Auto-corrected text Original text Language Profanity If the API detects any profane terms in any of the supported languages, those terms are included in the response.
Profanity analyzer
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Webb30 sep. 2024 · Aedos is a node.js module created primarily to detect profanity in a text, but it also can detect languages as well, the detection is based on Artificial Intelligence and have an 90% approximate... Webbför 15 timmar sedan · In addition to Boolean strings, I use ChatGPT for two other purposes that are huge time savers. First, I ask ChatGPT to send me interview questions that can help me analyze how well the candidates ...
Webb9 mars 2024 · A swear word is a word or phrase that's generally considered blasphemous, obscene, vulgar, or otherwise offensive. These are also called bad words, obscenities, expletives, dirty words, profanities, and four-letter words. The act of using a swear word is known as swearing or cursing. "Swear words serve many different functions in different ...
Webb10 apr. 2024 · Comment Toxicity/Profanity Analyzer, will help help increase empathy, participation and quality in online conversation at scale using Google's perspective api google profanity perspective-api toxicity comment-analyzer conversation-ai Updated Feb 11, 2024 JavaScript crbothe / discourse-wizard Star 2 Code Issues Webb5 nov. 2024 · Studying Trends in World Religion using R - Unboxed Analytics Studying Trends in World Religion using R Using a data set from the Pew Research Center, this post is about unpacking trends in world religion. The data set contains estimated religious compositions by country from 2010 to 2050. Sourcing the Data
Webb22 apr. 2024 · The verbatim analysis tool on Skeepers enables you to automatically, effectively and quickly analyze customer comments and transform these into tools for operational and strategic improvement. One way of displaying information in a Skeepers CX report: the top 10 words present in comments with a positive tone.
Webb11 nov. 2024 · I add the Profanity analyzer file. then, I run “rasa shell” but it can’t load the spacy model for the language and I received this error when I typed any message: … thousand bolts and only one nutWebbThe profanity analyzer looks for the really profane words. We chose not to let you see the list of profanities. If you want to know whether one is in there, you can type it in and hit the Check… button. It will tell you if it is in the list. The data file is encoded, so don't bother looking in there either. understand go happy new year 2022WebbOur profanity detector will highlight possible swear words for you with a bright pink underline. Please note that we err on the side of caution - a lot of the words we highlight … understand gps:principles and applicationWebbGender Analyzer Gender analysis identifies whether your text looks like it was written by a man or a woman. Our gender analysis tool looks at your text and compares it with a corpus of data with a known origin, looking at specific word frequencies to … understand game free downloadWebb6 nov. 2024 · Building a Lyrics Profanity Analyzer with R Shiny. A few weeks ago, a family member asked me to make them a Spotify playlist with recent rap hits. To avoid including anything excessively profane, I’d pull … thousand bolts quilting fabricWebbReadable's text scoring tool is designed tell you how easy a piece of text is to read and provide tips for improving its readability. TAKE A TOUR or LOAD EXAMPLE TEXT What's Readability? Readability scores are a way to measure whether written information is likely to be understood by the intended reader. understand gradient of a line as a ratioWebb27 okt. 2024 · 1. an extractor in the config pipeline in order to catch the names as {PERSON} entity 2. if the {PERSON} entity is empty, spacy matcher comes in play within a custom action 3. if there is no spacy match, the same custom action splits the value and search in already known names. finally, if Extractor couldn’t catch, and there is no match … understand gaussian process