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.

Country		Names	Country		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	Added the name extraction endpoint to the API to extract names from text. Created database with common keywords in every supported language to reduce false possive names for extraction endpoint. Examined and improved complete API to meet strict GDPR regulations.
1.3	30-09-2020	All endpoints don't try to parse (obvious) rubbish names anymore. Added additional status codes for when names could not be found (404). Improved the rate limiting functionality excluding error responses. Added additional hourly and daily usage fields to account information endpoint. Parse and Validation endpoints accept different orders for first and last name like: last name, first name first name or last name first name.
1.2	01-06-2020	Added rate limiting based upon subscription plan. Improved the name parser so it can detect multiple middle names. Increased accuracy of nationality prediction using new algorithm Updated the structure of the result object to a more logical model. Added support for IP addresses to Country Code using MaxMind GeoLite2. Added Pantheon and IMDB data files for loose and strict validation.
1.1	24-09-2019	Fixed salutation breaking after a title. Added the detection of nicknames that are written like: (nickname), [nickname] or "nickname". Added the following endpoints to the API: account information, validation and name generation.
1.0	17-08-2019	Released first version of the API.

Database

Version	Date	Changes
7	07-10-2020	Updated countries RU in the gender database. Created a lastname table to import all official lastnames. Added all supported countries to lastname database. In the countries RU, PL, CZ the lastname also indicates the gender. Updated firstname database for countries CA, RU, PL, IT, CH with additional names.
6	31-08-2020	Exported 10.187.493 public profiles to rebuilt the first name database resulting in 122 countries. Improved performance of cron jobs that collect public profiles. Fixed the Russian first names entries.
5	05-05-2020	Names from unsupported countries are now added and based upon first names from supported countries resulting in 110 countries. Started measuring and tracking nationality prediction performance by using open database with names and countries from 29,216 olympic athletes . Updated country tables with additional country information. Added countries HU, SI, SK, IN, RU and UA.
4	26-12-2019	Added column country_rank to name tables to support nationality prediction. Added countries AR, BR, AU, NZ, CZ, ES, FR, GR, PL, TR to the gender database.
3	22-10-2019	Updated tables, now including frequency of names. Added additional table for ASCII version of each name. Added countries AT, CA, DK, IT, NO, IE, CH, PT to the gender database.
2	02-09-2019	Released first version of the database. Converted whole database to UTF-8 when importing name databases. Added countries NL, SE, DE, FI, BE, US, GB to the gender database.
1	17-08-2019	Released first version of the database.