Making use of Key-Value Extraction NLP at the workplace

Making use of Key-Value Extraction NLP at the workplace

The ‘key’ refers to an attribute of a ‘value’ to which it corresponds. When you’re filling in a form that requires details like your name, email address, phone number, etc. your browser often fills it in for you. Have you ever noticed that? Here, the keys refer to the name or the address or phone number, while the value refers to what you input in the boxes provided for them. The same process can be restructured to match key values with one another from structured or even unstructured documents.

Key-value pairs are pairings of data that are inherently linked with one another. They are required when trying to find and match particular details with one another. Key-value pairs, of course, consist of two items of data, namely a key and a value.

Key: A unique identifier that tells the computer what kind of data you are looking for. It can be a name, it could be a number, it could be a zip code, or any other such thing. These are the parameters into which you need to put in data when filling in any type of form.

Value: The value gives us a bit of information that corresponds with the unique identifier. Values are the data to be put corresponding to the parameters in a form.

Take a look at the following table to understand better what keys and values are. Let’s suppose that the following are the key-value pairs for a textile vendor that has sent in an invoice to you.

Keys Values
Vendor Name ABC Textiles Pvt Ltd
Vendor Code ABCT
Email Address
Invoice Number 11897

The vendor’s name, code, email address and invoice number are the keys, i.e. the unique identifiers or parameters. The values are the actual data put forth corresponding to each key.

The basics of Natural Language Processing (NLP)

Natural language Processing (NLP) is one of the various branches of artificial intelligence that is responsible for converting ‘natural’ language into computerized language. It is the technology that allows computers to understand what a human is saying by listening to one or reading what they have written. It’s where a computer is taught to process text and spoken word and respond to it the same way a human would. With machine learning (ML), it also learns to understand regular conversation and respond more accurately over time.

Natural language processing can be customized for different processes with the appropriate coding. You can carry out sentiment analyses wherein NLP can define whether a statement is negative or positive. This is especially helpful when sorting through customer reviews – it’s automatic and much less tedious. Key-value extraction NLP is another form that breaks up data into more readable formats. Let’s understand a bit more of it in the next section.

Key-Value Extraction NLP: How it works?

Key-value extraction NLP is technically called ‘named entity recognition’ and is fairly simple to understand. What it does is that it extracts data from the source provided and divides it up into keys and values. It identifies each variable and sorts it into the relevant boxes, so to speak. It is incredibly helpful in the workplace because it can sort out unstructured data and put it into relevant consolidated formats that are simple to process. Let’s take an example to understand better how NER works for key-value extraction.

Let’s consider the following sentences for key-value extraction NLP:

  • Michael is 22 years old and studies at Princeton University.
  • Alana is 19 years old and studies at Erasmus University.
  • Arhaan is 25 years old.
  • Morrison studies at Yale University.

This data will be categorized by key-value extraction NLP in the following way, where the name, age and university name are the keys and the data is prescribed as such.

Keys Values
Name Michael Alana Arhaan Morrison
Age (years) 22 19 25 nil
University Princeton Erasmus nil Yale

The key value pairs from the four sentences have formed as above. Natural language processing quite accurately differentiates particular values from the other to give us a clearer picture of what piece of data corresponds to which parameter or unique identifier.

Key-value extraction NLP in Business

There are several places where key-value pairings can be put to use, especially to bring in a whole lot more efficiency to several general tasks. Here are three of the many other business processes where NLP-based key-value extraction can be rather helpful:

1. Invoicing

Using NLP, you can easily extract invoice numbers, dates, taxes, invoice amount, etc. into consolidated and easier-to-read formats without having to do much yourself. Processing invoices can be monotonous and tiring, but having all the info put in place to recheck and send across payments can make the job less so. This can be done with automated invoice capture and processing, then moving forward with key-value extraction with NLP.

2. Processing Resumes

Hiring drives can be difficult to keep up with because of the large volume of applicants, especially with lengthy CVs/resumes. Key-value extraction NLP can help you come up with a list of the most fruitful candidates by sorting out educational and professional qualifications, a list of the relevant skills, previous work experience, and so on. This would give you a better idea of your candidates and can even be put in a comparative format, providing obvious benefits.

3. Government Documents

Again an HR process, you need to process your (new) employees’ government documents as part of their onboarding process. To have to extricate details and fill them in is tedious compared to if your machine could just do it for you – which it can, with key-value pair extractions with NLP. Using OCR and NLP, relevant details like the name, date of birth, document number, issuing authority, and so on, can be very easily extracted and restructured.


Once you download the correct software (and get the hang of it), key-value extraction NLP makes your work life a lot easier. Simple but lengthy processes can be cut much shorter in time using the correct software. Rest be assured, combined with the right OCR enabled with NLP, you can make much more efficient use of your time at work with automated key-value pairings.

Ashutosh Saitwal
Ashutosh Saitwal

Ashutosh is the founder and director of the award winning KlearStack AI platform. You can catch him speaking at NASSCOM events around the world where he speaks and is an evangelist for RPA, AI, Machine Learning and Intelligent Document Processing.