Identify if a text contains a question mark
using AI
Below is a free classifier to identify if a text contains a question mark. Just input your text, and our AI will predict if the text contains a question mark - in just seconds.
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Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-a-text-contains-a-question-mark", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/if-a-text-contains-a-question-mark/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_text_here"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_text_here"}' \
https://www.nyckel.com/v1/functions/if-a-text-contains-a-question-mark/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict if the text contains a question mark.
This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Contains Question and Does Not Contain Question.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if the text contains a question mark).
Whether you're just curious or building if a text contains a question mark detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify if a text contains a question mark at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Support Query Detection: This use case involves identifying incoming customer support tickets that contain questions, allowing support teams to prioritize and categorize inquiries more effectively. By filtering for question marks, support can streamline their responses to common queries and enhance customer satisfaction.
- Market Research Analysis: In market research, companies can utilize text classification to identify consumer sentiment and feedback that pose questions. Analyzing these inquiries can reveal customer concerns, needs, and areas for improvement in products or services.
- Social Media Engagement Monitoring: Businesses can monitor social media interactions by detecting questions in user comments or posts. This allows them to proactively engage with customers, providing answers and building community while enhancing brand loyalty.
- Educational Content Assessment: Educational platforms can assess student submissions or forum posts to identify questions. This analysis helps instructors understand student engagement and areas where learners struggle, allowing for targeted support and resources.
- FAQ Generation: Automated systems can identify and compile frequently asked questions from various text sources. This helps organizations create comprehensive FAQ sections that address common inquiries, improving user experience on their websites.
- Chatbot Interaction Improvement: By flagging user messages with question marks, chatbots can prioritize human-like responses to inquiries. This enhancement allows for more effective real-time interaction, leading to better user experiences and satisfaction.
- Content Quality Analysis for Writing Tools: Writing applications can assess input text for questions to gauge content interactivity and reader engagement. This can assist users in refining their writing to be more dynamic and engaging by encouraging them to include questions that provoke thought.