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At present, bots are still in their preliminary stages of development. Manyare relatively simple, or developed ad-hoc for a very specific use-case. Forthis reason, they are typically programmed manually, or utilizemachine-learning classifiers to interpret a fixed set of user utterances. Inreality, real world conversations with humans require support for dynamicallycapturing users expressions. Moreover, bots will derive immeasurable value byprogramming them to invoke APIs for their results. Today, within the Web andMobile development community, complex applications are being stringed togetherwith a few lines of code -- all made possible by APIs. Yet, developers todayare not as empowered to program bots in much the same way. To overcome this, weintroduce BotBase, a bot programming platform that dynamically synthesizesnatural language user expressions into API invocations. Our solution is twofaceted: Firstly, we construct an API knowledge graph to encode and evolveAPIs; secondly, leveraging the above we apply techniques in NLP, ML and EntityRecognition to perform the required synthesis from natural language userexpressions into API calls.

Programming Bots by Synthesizing Natural Language Expressions into API Invocations