Pretrained text classifier
Identify if a text contains a gerund with one API call.
A pretrained if a text contains a gerund classifier that sorts text into one of 2 categories. Use the if a text contains a gerund API immediately, no training required, then adapt it to your own data when you need more.
Try the if a text contains a gerund classifier
Drop in some text and get the prediction back. No signup, no setup.
What this if a text contains a gerund classifier recognizes
A sample of the 2 labels this pretrained classifier chooses between.
Need a label that isn't here? Clone the classifier into your Nyckel console and edit the label set to fit your data.
Call the if a text contains a gerund API
Get your own copy of this classifier behind your own endpoint — callable from any HTTP client:
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "The text you want to classify"}'import requests
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer YOUR_ACCESS_TOKEN"},
json={"data": "The text you want to classify"},
)
print(response.json())const response = await fetch("https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_ACCESS_TOKEN",
"Content-Type": "application/json",
},
body: JSON.stringify({ data: "The text you want to classify" }),
});
console.log(await response.json());$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, 'https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke');
curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1);
curl_setopt($ch, CURLOPT_POST, 1);
curl_setopt($ch, CURLOPT_POSTFIELDS, '{"data": "The text you want to classify"}');
$headers = array();
$headers[] = 'Authorization: Bearer YOUR_ACCESS_TOKEN';
$headers[] = 'Content-Type: application/json';
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
$result = curl_exec($ch);
curl_close($ch);
echo $result;Example response
{
"labelName": "Contains Gerund",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 2 if a text contains a gerund categories, served on Nyckel's own infrastructure — your text snippet stays on Nyckel.
Send raw text to the invoke endpoint; the response is a label with a confidence score.
Clone it, then correct predictions and add your own samples in the console — Nyckel retrains automatically, turning this into a custom model tuned to your data.
Where teams use if a text contains a gerund classification
Content Analysis for Marketing
In marketing, understanding the tone and engagement of content is critical. By identifying gerunds, marketers can analyze the action-oriented language in their promotional materials, helping to assess whether the content effectively encourages customer engagement.
Grammar Checking in Writing Tools
Writing software can utilize the gerund identifier to enhance grammar-checking capabilities. By flagging or suggesting changes to gerunds, it aids users in improving the clarity and correctness of their writing, ensuring a more professional output.
Sentiment Analysis in Social Media
Social media platforms can leverage the identification of gerunds to gauge the sentiment of user-generated content. By analyzing how individuals express actions and emotions, companies can extract insights about public opinion and trends.
Resume Screening for Recruitment
Recruiters can implement this function to analyze resumes and cover letters more effectively. By detecting gerunds, which often indicate active participation, candidates can be evaluated on their demonstrated experiences and skills in a clearer manner.
Educational Tools for Language Learning
Language education applications can use the gerund identification function to help learners grasp English grammar nuances. By providing instant feedback on gerund usage, students can receive targeted exercises that reinforce their understanding of action-related vocabulary.
Chatbot Development for Enhanced Interactivity
In chatbot applications, identifying gerunds can improve conversational capabilities by making interactions feel more dynamic and responsive. By recognizing and responding to gerund-based queries, chatbots can deliver a more engaging user experience.
News and Journalism Content Structuring
Journalists and editors can use gerund identification to structure articles around key actions and themes. By highlighting gerunds in their reporting, they can emphasize ongoing events and actions, making their narratives more compelling and action-oriented.
Common questions
What's the difference between a zero-shot and a Nyckel-trained classifier?
A zero-shot classifier uses a large foundation model's general knowledge to pick between your labels — no task-specific training, so new or edited labels work immediately. A Nyckel-trained classifier has been trained on labeled examples and runs on Nyckel's own infrastructure, which typically makes it faster, cheaper per call, and more accurate on data that resembles its training set. The "Under the hood" section on this page shows which kind this classifier is, and any classifier can be adapted into a trained one by adding your own examples.
How do I know whether this will work for my application?
Honestly: we can't know in advance — it depends on your data stream and how closely it resembles what this classifier has seen. The reliable way to find out is to measure it on your own data: start invoking the classifier with real traffic, or upload and annotate a set of text samples in the console — make sure they look like your production data, not idealized examples. Nyckel's evaluation metrics then show you exactly how it performs on that data before you rely on it.
What happens when it makes a mistake?
No classifier is perfect, so Nyckel is built around the correction loop: invokes can be captured for review, you confirm or correct predictions in the console, and corrections become training data. Over time the model adapts to your data distribution — accuracy on your traffic improves with use rather than staying fixed.
Do I need training data to get started?
No. This if a text contains a gerund classifier works out of the box — clone it into your console and you'll have your own API endpoint in under a minute. Training data only enters the picture when you want to adapt it: your corrected predictions and uploaded samples improve the model, and you can also edit the label set to match your needs.
What does it cost to try?
Trying the classifier on this page is free with no signup. Cloning it requires a free account, and the free tier covers your first API calls each month — see nyckel.com/pricing for current limits and paid tiers.
Related classifiers
Ready to classify if a text contains a gerund at scale?
Add this pretrained classifier to your Nyckel console — you'll get a live API endpoint in under a minute, and a path to a custom model when you need one.