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Semantic parsing is the task of conversion of natural language utterance into a logical form: a machine-understandable language. The job of semantic parsing is to extract the precise meaning of an utterance. It is worthwhile to notice that semantic parsing is different from other sequential prediction tasks such as machine translation and natural language generation.

Question Answering is a computer science area that comes in the fields of information retrieval and natural language processing, with a focus on building systems that automatically answer questions posed by humans in natural language.

A computer understands natural language by translating the human written sentences into a representation that the system can understand easily. Only after this, the system can generate valid answers to the questions asked by the user


The main challenges that a Question Answering System faces are described below:

1. Lexical Gap

In a natural language, the same meaning can be expressed in different ways. Because a question can only be answered if every single concept is clearly identified. Bridging this gap can significantly increase the proportion of questions that can be answered by a system

2. Ambiguity

The same phrase can have different meanings. The same string can refer to different concepts (like money bank vs. river bank) and polysemy is also included, where the same string refers to different concepts which are related in some manner (like in bank as a company vs. Bank as a building)

3. Multilingualism

A QA system is expected to understand and recognize every language as users have various native languages. The system needs to answer queries by understanding all the languages. There is not a single language that is always used in Web documents.

RIS will help you overcome all the challenges being faced in semantic parsing or question answering techniques.

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