The customer
needed a powerful tool capable of parsing various structured entities from
unstructured text recognized through OCR (Optical Character Recognition). The
challenge was to extract critical information efficiently and accurately from
text, enhancing data usability and facilitating decision-making.
SOLUTION
DataObrii
developed a comprehensive Named Entity Recognition (NER) that included
various analyzers designed to parse different types of entities from
unstructured text.
Key components of the solution included:
- entity names parser; - address parser; - date parser; - quantities and measures parser; - money parser; - the efficient mechanism to minimize false
detections; - the mechanism for automated labelling of the
training dataset.
RESULTS & ADVANTAGES
The
implementation of the NLP-based Named Entity Recognition had a
substantial impact on our client's data processing capabilities. By automating
the extraction of various structured entities, it optimized the analysis of
unstructured text data. This resulted in improved data accuracy, reduced manual
effort, and faster decision-making processes. DataObrii's
commitment to delivering advanced solutions that address complex data
challenges is evident in this project. We combine cutting-edge technology and
expertise to create solutions that empower our customers to unlock the true
potential of their data, enhance operational efficiency, and make informed
decisions with confidence.
