Introduction
We all take our names for granted and yet there is so much information in it. Your name reveals a lot of information about who you are. It tells if you're a man or a women, what language you speak and it can even reveal your nationality.
Validating a phone number, zip code or email address is simple. You don’t need a parsing service for that. But parsing a name and getting information out of it is much harder. That is where we come in: Name Parser is an API service that splits a complete name into useful information such as first name, last name, gender and nationality. It makes your live as a developer or data scientist much easier. Just give us a name and we'll give you the useful components.
Order of names
Names can be written in different name orders . This makes it complicated for developers to check if a name is valid or not. The order [first name] [last name] is known as the Western order and is usually used in most Western countries (Europe, North and South America, India and Oceania). The order [last name] [first name] is known as the Eastern order and is primarily used in East Asia. Our software can parse all common name orders, salutations and titles.
Types | Format | Example |
---|---|---|
Regular names. | [first name] [last name] | Jennifer Anderson |
Names with middle name. | [first name] [middle name] [last name] | Stephanie Karen Hills |
Last name first. | [last name], [first name] [middle name] | Procházka, Lukáš Michal |
Names with salutation and initials. | [salutation] [first name] [initial] [last name] | Mr Bob S. Samuels |
Title with last name first. | [title] [last name], [first name] | Dr. Jenkins, Philip |
Nickname between [], (), {} or "". | [first name] [nickname] [last name] | Stephanie "DJ" Williams |
Cyrillic, Greek and Latin characters. | [first name] [last name] | Екатерина Иванов |
Supporting 104 countries
In order to properly parse names, our service uses an huge database with 1.597.154 first names and 5.012.607 last names from 104 different countries. A significant part of this name data is available for purchase as a CSV file with names and gender at Name Census .
There are many names such as Robin, Pascal or Mickey, which are mainly used for girls in one country and for boys in other countries. By specifying the country code in the query, we can determine the gender of a name with greater certainty.
Names | Names | ||
---|---|---|---|
United Arab Emirates | 8.131 | Afghanistan | 4.143 |
Albania | 3.077 | Argentina | 14.963 |
Austria | 15.215 | Australia | 19.283 |
Azerbaijan | 1.809 | Bosnia and Herzegovina | 3.657 |
Bangladesh | 6.024 | Belgium | 26.068 |
Bulgaria | 5.763 | Bermuda | 2.777 |
Brazil | 107.674 | Belarus | 1.951 |
Canada | 26.142 | Switzerland | 58.506 |
Chile | 4.751 | Cameroon | 4.004 |
China | 8.379 | Colombia | 10.011 |
Costa Rica | 4.293 | Czech Republic | 8.081 |
Germany | 34.731 | Denmark | 130.994 |
Dominican Republic | 4.517 | Algeria | 3.283 |
Ecuador | 3.832 | Egypt | 4.676 |
Spain | 56.913 | Finland | 4.831 |
France | 42.245 | United Kingdom | 54.136 |
Georgia | 4.189 | Ghana | 3.775 |
Greece | 5.176 | Guatemala | 4.156 |
Hong Kong | 4.312 | Honduras | 2.763 |
Croatia | 2.702 | Hungary | 8.362 |
Indonesia | 16.187 | Ireland | 8.890 |
Israel | 3.494 | India | 23.161 |
Iraq | 2.665 | Iran | 3.683 |
Italy | 25.788 | Jersey | 4.101 |
Jamaica | 10.104 | Jordan | 1.915 |
Japan | 7.154 | Kenya | 5.041 |
South Korea | 5.274 | Kazakhstan | 2.262 |
Lebanon | 2.732 | Liberia | 5.473 |
Lithuania | 1.676 | Luxembourg | 3.472 |
Latvia | 1.832 | Morocco | 3.651 |
Macedonia | 2.518 | Mexico | 14.176 |
Malaysia | 9.007 | Nigeria | 8.875 |
Nicaragua | 1.880 | Netherlands | 21.799 |
Norway | 31.178 | Nepal | 3.593 |
New Zealand | 6.733 | Panama | 2.564 |
Peru | 5.731 | Philippines | 11.770 |
Pakistan | 7.213 | Poland | 53.376 |
Palestine | 1.851 | Portugal | 16.901 |
Paraguay | 2.234 | Romania | 6.554 |
Serbia | 3.204 | Russia | 34.491 |
Saudi Arabia | 3.730 | Sweden | 35.910 |
Singapore | 8.572 | Slovenia | 9.472 |
Slovakia | 4.340 | Somalia | 1.630 |
El Salvador | 2.032 | Syria | 2.640 |
Thailand | 6.065 | Tunisia | 2.044 |
Turkey | 166.098 | Taiwan | 3.712 |
Tanzania | 2.196 | Ukraine | 6.645 |
Uganda | 2.433 | United States | 105.958 |
Uruguay | 1.864 | Saint Vincent | 3.078 |
Venezuela | 8.818 | Vietnam | 3.403 |
Kosovo | 2.849 | Mayotte | 14.873 |
Zambia | 2.570 | Zimbabwe | 2.601 |
Use cases
Name Parser is a blazing fast RESTful API that returns JSON objects. It is easy to integrate into any existing or new project. Names are a very common field in most online forms, databases and processes. To get an idea of the possibilities of our API we listed a few typical use cases.
1) Simplify contact forms
Almost all business websites contain a form where a visitor can enter his name. On average forms have five different text inputs like: first name, last name, salutation, email and country. Using our name parsing endpoint you can bring that back by 60% and even get more information. Instead of a user having to fill five fields, a visitor only has to enter his complete name and email address.
- Shorten contact, registration and order forms by 60%
- Get more conversions (people don't like to fill in long forms)
- Get more information out of your form like gender and nationality
2) Validate names
Do you have a website where people can sign up, order or submit a question via a contact form? You can use our name validation endpoint to check if a name exists, is not made up or misspelled. In addition the validation endpoint also detects if a name is possibly fake by comparing it with 13.738 famous, fictional and humorous names.
- Make sure you get high quality sign-ups
- Validate if a name is not fake
- Check if a name is is not misspelled
3) Clean up your existing customer database
Do you already have an existing database with customer names? Use our name parsing endpoint to flag misspelled or fake names an enrich your database with additional customer information. Our paid plans offer the possibility to process a high volume of names in a short time.
- Validate your customer names
- Detect misspelled and fake names
- Get the right salutation for your emails and other communication
- Enrich your database with your customers gender, possible nationality
4) Generate fictional names for your development databases
In most cases when you develop software, apps or web projects you work with names of customers. For new projects you can generate fictional accounts including the salutation, gender and country details. The endpoint is not only useful for new projects but also for existing projects. Instead of having a development database with real names it's more secure to work with fictional names instead. Use our name generator endpoint to generate a database with fictional names for any country code.
- Generate fictional user accounts (name, gender, country) for new projects
- Improve the security of your applications by developing with fictional names
5) Extract names from text
Do you want extract names from news articles, form messages or web pages? Use our name extraction endpoint to extract complete names from any given text.
- Extract names from news articles or social media posts for automated tagging
- Extract names from web pages like "About us" or "Meet the Team".
- Search and replace extracted names from emails to mask names for GDPR compliance.
Changelog
We always keep on improving our service. We divided the changelog in a section for the API and for the database. Our API returns the version of the API and database via the response headers. You can use the versions from the response header to programmatically detect if we release a new version.
API
Version | Date | Changes |
---|---|---|
1.4 | 13-11-2020 |
|
1.3 | 30-09-2020 |
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1.2 | 01-06-2020 |
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1.1 | 24-09-2019 |
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1.0 | 17-08-2019 |
|
Database
Version | Date | Changes |
---|---|---|
7 | 07-10-2020 |
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6 | 31-08-2020 |
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5 | 05-05-2020 |
|
4 | 26-12-2019 |
|
3 | 22-10-2019 |
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2 | 02-09-2019 |
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1 | 17-08-2019 |
|