Sierra hopes every company will use its empathetic AI chatbots for customer interactions.

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ChatParse.AI is an app that provides out-of-box NLP AI models.

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In early 2015, we closed a partnership deal to invest in New Regency’s three enthralling titles, namely The Revenant, Assassin’s Creed and Splinter Cell, marking the first investment of a Taiwanese company in major Hollywood productions. CATCHPLAY and partners also control exclusive ...

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Yes/No Intent detection to empower workflow builders

Yes/No Intent detection analysis - ChatParse.AI Documentation

Use trained machine learning NLP models to get intents, sentiments and keywords on text messages. We empower chatbots, data analytics, CRM and other softwares with support on all languages.

ChatParse.AI - Get AI analysed message data through API

Go to https://www.integromat.com/en/apps/invite/dad37a0edc14ecbbed77b6cd3a1395c1 and install our ChatParse plugin at Integromat · For the output of the ChatParse plugin, different analysis models provide different parameters, you can find out by referring to the next node or check out the ...

Integromat Plugin - ChatParse.AI Documentation

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To display data in bubble pages, first create a group with it&#x27;s &quot;type of content&quot; set to the name of the analysis model in ChatParse.AI like below: · Within the group created a text element with it&#x27;s appearence setup to the group result&#x27;s body value like below: · In the workflow of that page, ...

Bubble.io Plugin - ChatParse.AI Documentation

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Parse CHAT syntax from the CHILDES corpus to YAML. Contribute to jayelm/chatparse development by creating an account on GitHub.

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After installing ChatParse.AI plugin into your Zapier, when creating/updating a Zap, you will be able to find ChatParse.AI in your action when you search &quot;ChatParse&quot; in action · After selecting ChatParse.AI as action, you can choose an event from a list of NLP AI analysis: · You will need ...

Zapier Plugin - ChatParse.AI Documentation

Supercharge your Chatbot with pre-trained AI, and yet #NoCode

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<a href="https://mmhaskell.com/blog/2018/2/5/parsing-primer-gherkin-syntax" target="_blank">Last week</a> we prepared ourselves for parsing by going over the basics of the Gherkin Syntax. In this article and the next, we’ll be using the <a href="https://hackage.haskell.org/package/regex-applicative-0.3.3/docs/Text-Regex-Applicative.html#t:RE" target="_blank">applicative parsing</a> library to parse that syntax. This week, we’ll focus on the fundamentals of this library, and build up a vocabulary of combinators to use. We’ll make heavy use of the <code class="markup--code markup--p-code">Applicative</code> typeclass. If you need a refresher on that, check out <a href="https://mmhaskell.com/blog/2017/2/6/applicatives-one-step-further" target="_blank">this article</a>. As we start coding, you can also follow along with the examples on <a href="https://github.com/jhb563/GherkinParsing" target="_blank">Github here</a>! Most of the code here is in <a href="https://github.com/jhb563/GherkinParsing/blob/master/src/Parser.hs" target="_blank">Parser.hs</a>.

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CATCHPLAY Corporate – For movie lovers by movie lovers

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