Identify name format
using AI
Below is a free classifier to identify name format. Just input your text, and our AI will predict the appropriate name format for the given input. - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("name-format", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/name-format/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/name-format/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict the appropriate name format for the given input..
This pretrained text model uses a Nyckel-created dataset and has 10 labels, including First Last, First Last Suffix, First Middle Last, First Name Last Name, Initials Last Name, Last First Middle, Last Name First Name, Last Name Initials, Last Name Professional Title and Professional Title First Last.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the appropriate name format for the given input.).
Whether you're just curious or building name format detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify name format at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Support Ticket Sorting: Automatically classify incoming customer support tickets based on their urgency, type, or department. This allows support teams to prioritize and route issues more effectively, leading to faster response times and improved customer satisfaction.
- Email Filtering for Marketing Campaigns: Identify and classify email responses from customers into relevant categories such as inquiries, complaints, or feedback. This helps marketing teams analyze customer sentiment and tailor their campaigns accordingly to enhance engagement.
- Social Media Post Monitoring: Analyze and classify social media mentions of a brand to determine their sentiment and relevance. By identifying false or misleading mentions, businesses can swiftly address reputational risks and engage positively with their audience.
- Resume Screening for Job Applications: Automate the initial screening of job applications by classifying resumes based on qualifications, experience, and fit for the role. This significantly reduces the time and effort spent by HR teams in the recruitment process.
- Fraud Detection in Financial Transactions: Classify financial transactions to identify patterns and detect potentially fraudulent activities. By flagging suspicious transactions based on historical data, businesses can mitigate risks and protect customer assets.
- Product Review Analysis: Automatically classify product reviews to identify positive, negative, or neutral sentiments. This enables companies to better understand customer feedback and make improvements to their products or services based on real-time data.
- Content Moderation for Online Platforms: Use classification to identify and filter out false, misleading, or harmful content posted by users. This helps maintain a safe and trustworthy environment on online platforms, ensuring compliance with community guidelines and legal standards.