2023:Program/Submissions/Building ChatBOT using Wikidata - EW8AQS

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Title: Building ChatBOT using Wikidata

Speakers:

Neechalkaran

Developer, Wikipedian & Computational Linguist from Tamilnadu. I edit articles in Indian wikipedias, edit words in wiktionaries, proof read pages in Wikisource and develop various Wiki tools(https://en.wikipedia.org/wiki/User:Neechalkaran/Tools) like Wiki Converter, AppsWiki, Chatwiki, User scripts, BOTs like Wiki Bot(Tamil, Hindi, Bhojpuri). Developer of VaaniNLP-Tamil NLP library, language tools like Tamil Spell checker, Indic Transliteration. . Recipient of IT in Tamil Award from Tamil Literary Garden, Canda(2015) & Tamil Computing Award from Tamilnadu Government (2019)

Pretalx link

Etherpad link

Room:

Start time:

End time:

Type: Lecture

Track: Technology

Submission state: submitted

Duration: 30 minutes

Do not record: false

Presentation language: en

Abstract & description

Abstract

Wikidata is the largest Knowledge Base in the world. ChatBOT can be created using NLP libraries along with Wikidata. This session talks about wikidata structure, Lexeme structure and how this can used to build a chatBOT or question Answering system.

Description

I have developed First wikidata Tamil ChatBOT(https://chatwiki.toolforge.org/) with VaaniNLP. On this experience I have relalized that with full potential of lexeme anyone can build their own chatbot in any language. This session will describe about how to build morphological lexeme, how to query and retrive data effectively from wikidata, how to create simple chatBOT or Q&A system on top of Wikidata. This will help to understand the pratical use case for lexeme for common person

Further details

Qn. How does your session relate to the event themes: Diversity, Collaboration Future?

As the world move towards the Generative AI, This session will give the basic idea about knowledge Base. This will bring conversation about implementing this Wikidata in any chatbot system. Though it is not about AI, however this knowledge base will help them in building any Generative AI product

Qn. What is the experience level needed for the audience for your session?

Everyone can participate in this session

Qn. What is the most appropriate format for this session?

• Onsite in Singapore
• Remote online participation, livestreamed
• Remote from a satellite event
• Hybrid with some participants in Singapore and others dialing in remotely
• Pre-recorded and available on demand