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RChilli Introduces JD Parser 3.1

RChilli JD Parser 3.1 can parse a job description in real-time through an agile API interface. It extracts data from the job description and saves it in the pre-defined attributes.

RChilli is committed to adding new advancements to its products. This is the reason RChilli is introducing a newer version of its job parser i.e. Job Parser 3.1.

This latest version aims at bringing exciting features for its users. As the first step of the recruitment process is a job description, it is very important for HR managers to create a clear and compelling job description to quickly close jobs.

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What is RChilli JD Parser 3.1?

RChilli JD Parser 3.1 can parse a job description in real-time through an agile API interface. It extracts data from the job description and saves it in the pre-defined attributes.

In short, it gives a structured format to the unstructured data of the job description.

What’s New in RChilli JD Parser 3.1?

The latest version comes with many incredible features that make RChilli JD parser a must-have for HR professionals.

  • It offers multi-lingual support and can now parse job descriptions in multiple languages.
  • There is a new addition of fields related to related skills, ontology, and language.
  • With the introduction of deep learning technology, the users will witness an improved accuracy of the fields.
  • Another exciting development is the implementation of Taxonomy 3.0 in JD parser to enhance search results of Solr/ Elasticsearch.

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Talking about the latest version of JD Parser, Vikesh Kumar, Team Lead-RChilli, said, “We have started supporting multi-lingual parsing for JD Parser 3.1. This version is implemented with Deep learning, which helps to extract data more accurately. The implementation of taxonomy 3.0 in JD Parser will help users who use solr/elastic search.”

  • The Unique Use Cases of RChilli JD Parser 3.1
  • Parse multiple job descriptions at once
  • Parse job descriptions in multiple languages
  • Extract all the job details from the job feeds
  • Upload a job description and get the output in JSON format
  • Parse job descriptions from a single/multiple email inboxes
  • Enhance search results by indexing its taxonomy ontologies to Solr/Elasticsearch
  • Create a structured job post for the internal job posting

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