How to Use Prefix for Generating Questions in AI

Jan 30, 2021 | Educational

Are you curious about enhancing your AI model’s ability to generate questions from given contexts? In this blog, we will delve into how to utilize prefix context for generating questions, specifically using datasets like Squad, XQuad, and Tydiqa. Let’s break it down step-by-step for better understanding!

Understanding the Concept

The core idea is to use specific prefixes that guide the AI in constructing relevant questions based on the input context. Here’s how it works:

  • Prefix usage: To generate a question, a prefix is used along with the context.
  • Example: You might have a context stating “nama saya andi. saya tinggal di jakarta. istri saya bernama raisa” and you want to generate a question like “siapa nama saya?”.

Example Breakdown

To illustrate this further, let’s imagine your program is a detective trying to piece together information from various clues.

  • The context is like a series of clues scattered around the crime scene.
  • The prefix acts as the detective’s guiding questions that help highlight what is being sought.
  • When the clues (context) are presented, the detective (AI) uses his leading questions (prefix) to derive the needed answers.
question: siapa nama saya ? 
context: nama saya andi. saya tinggal di jakarta. istri saya bernama raisa.

Training Data

When working with question generation, it is essential to train the model using robust datasets such as:

  • Squad
  • XQuad
  • Tydiqa

These datasets provide comprehensive examples that help the AI learn context and question relationship effectively.

Troubleshooting Common Issues

If you encounter issues while implementing prefix-based question generation, here are some troubleshooting tips:

  • Ensure that the context provided is clear and concise to avoid ambiguous questions.
  • Check if the prefix used aligns with the context; mismatched prefixes can lead to irrelevant questions.
  • Review and adjust your training data to enhance the accuracy of question generation.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

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