Text Classification Models for Form Entity Linking

12/14/2021
by   María Villota, et al.
5

Forms are a widespread type of template-based document used in a great variety of fields including, among others, administration, medicine, finance, or insurance. The automatic extraction of the information included in these documents is greatly demanded due to the increasing volume of forms that are generated in a daily basis. However, this is not a straightforward task when working with scanned forms because of the great diversity of templates with different location of form entities, and the quality of the scanned documents. In this context, there is a feature that is shared by all forms: they contain a collection of interlinked entities built as key-value (or label-value) pairs, together with other entities such as headers or images. In this work, we have tacked the problem of entity linking in forms by combining image processing techniques and a text classification model based on the BERT architecture. This approach achieves state-of-the-art results with a F1-score of 0.80 on the FUNSD dataset, a 5 project is available at https://github.com/mavillot/FUNSD-Entity-Linking.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/01/2023

End-to-End Document Classification and Key Information Extraction using Assignment Optimization

We propose end-to-end document classification and key information extrac...
research
03/08/2021

Fast and Effective Biomedical Entity Linking Using a Dual Encoder

Biomedical entity linking is the task of identifying mentions of biomedi...
research
09/03/2019

Neural Attentive Bag-of-Entities Model for Text Classification

This study proposes a Neural Attentive Bag-of-Entities model, which is a...
research
12/15/2021

Evaluating Pretrained Transformer Models for Entity Linking in Task-Oriented Dialog

The wide applicability of pretrained transformer models (PTMs) for natur...
research
06/04/2019

Boosting Entity Linking Performance by Leveraging Unlabeled Documents

Modern entity linking systems rely on large collections of documents spe...
research
05/27/2019

FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

In this paper, we present a new dataset for Form Understanding in Noisy ...
research
06/02/2021

End-to-End Hierarchical Relation Extraction for Generic Form Understanding

Form understanding is a challenging problem which aims to recognize sema...

Please sign up or login with your details

Forgot password? Click here to reset