Extract names from unstructured text
By using millions of first and last names our name extraction solution can extract names with an extremely high precision and accuracy. Extract complete names from unstructured text with our Web App or API.
Extract names from news articles for automated tagging. Build an index with names extracted from news articles to improve search and discover relations between articles.
Corporate team web pages
Extract employee names from corporate web pages like the 'About us' or 'Meet the Team' web page. Calculate the ratio between men and women and discover the nationalities.
Automatically redact incoming messages posted via your website. Search and replace extracted names from messages to mask names for GDPR compliance.
Integrate our RESTful name extraction API into your platform
We offer a blazing fast RESTful API that returns JSON objects that easily integrate into any project. The JSON object below is an example response of what you receive when using the name extraction API.
Each extracted name is provided with a frequency number which is an indication of the accuracy of the name. The frequency is based upon how many times the first and last name occur in a country.
By using extremely fast servers and a database with 2.208.942 official first names received from governments and statistical agencies we can identify potential first names fast.
In the past extracting names from text was done using named-entity recognition (NER). Unfortunately that is not accurate enough (~90%). We extract names by examining every word in a text to check if the word could be a first name. This results in an extremely high precision and accuracy.
After we identified a possible first name we check the following words in a database with 6.119.869 last names. This way we can identify and extract complete names with an extremely high precision and a high accuracy.
If we extracted the first and last name we combine both country frequencies to an ultimate frequency that indicates the accuracy of the complete name. If the frequency is above a certain threshold we return the extracted name.
Based upon the first name and last name our service can predict the country of origin of any given name. As you can see in the response object each name has a country code.
For each country we deliver comprehensive country information like language code, currency and demonym. This makes your development database rich and accurate.
Use our Web App to extract names from unstructured text
Do you want extract names from news articles, social media messages or corporate team web pages? Use our name extraction endpoint to extract complete names from any given unstructured text.
Copy and paste a piece of text
Copy and paste a piece of unstructured text into our Web App to extract the names from.
Export to table or excel
Let the Web App extract the names and show results on your screen or export to CSV.
Highlight extracted names
After extracting the names from the text the names will be highlighted in the original text.