Skip to content

Probate Parsing Solution#8

Open
shahsaumya wants to merge 2 commits intoFreeUKGen:masterfrom
shahsaumya:master
Open

Probate Parsing Solution#8
shahsaumya wants to merge 2 commits intoFreeUKGen:masterfrom
shahsaumya:master

Conversation

@shahsaumya
Copy link
Copy Markdown
Collaborator

Refer Issue #7

The system that I propose to implement is an end-to-end system that extracts the text from probate books and seeds them into a database with entities such as name, county, date, relationships etc. This system can, therefore, be broken down into three phases -

  1. Text extraction using Optical Character Recognition
  2. Named Entity Recognition using Language Processing
  3. Database Seeding based on the entities generated

Due to lack of samples to train a Named Entity Recognizer, I've made use of the Stanford NER Wrapper and NLTK to produce the results.

1. OCR using pytesseract - ocr.py
2. Named Entity Recognition using NLTK and Stanford NLP Wrapper
	a)NLTK - nltk_ner.py
	b)Stanford NLP - stanford_ner.py
3. To get a good idea of prerequisites and execution details - README.md
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

1 participant