Table Identification

Table Identification

Overview

A Table is a data structure used to organize and present information in rows and columns. It is used to present values in a readable format.

A table consists of the following elements:

Hyperscience provides a solution for extracting the data from tables by using Table Identification models in Semi-Structured layouts.

Table Extraction is available only for Semi-Structured Layouts. Learn more in Creating Semi-Structured Layouts.

We support extraction for the following tables:

In this article, you will learn how to annotate and train a Table ID model.

Table Identification Task

Table ID tasks are specific to Semi-structured documents with table columns. To see these tasks, you must define table columns on a Semi-structured layout.

Prerequisites

Follow the steps below to define a table and start the annotation process:

Extract your tables by using the Table Identification task. It is available for Supervision, QA, and Training Data Management.

Annotating Tables

The Table Identification task is available in Training Data Management and it’s similar to annotating in Supervision.

Follow the steps described in the Table ID Supervision tab to annotate your documents.

Navigating the Table ID task in TDM

Be sure to click the Continue to Review (CMD+ENTER) button for each available table.

Follow the steps below to annotate your table in Supervision:

1. Select a row from the table to be a Template row

A Template Row is the lead row in your table. It is not necessary to be the first one. Hyperscience uses the copycat tool to populate the annotation to the rest of the rows in Step 2. The copycat is not always accurate, so make sure to double-check the annotations.

In this step, you will define the template row of your table.

  1. Select a row from the table to be a template row.

2. Make sure to capture the cell and follow the tips below if necessary

If... Then...
The bounding box includes all of the cell's content. Move on to the next step.
The box is in the right place but doesn't include all of the cell's content (e.g., parts of letters fall outside of the box). Click and drag the box's corners until it contains all of the content that should be transcribed.
Neighboring text segments should also be included in the cell's transcription. With a click-and-drag motion, draw a bounding box that includes all of the cell's content.
The box doesn’t include any of the cell’s content OR no bounding box appears around the cell’s content when hovering over it. Press the spacebar, and with a click-and-drag motion, draw a bounding box that includes all of the cell's content.

3. Review your annotations

  1. De-select all columns by pressing the ESC button to have a better preview of the annotations. The labels will indicate all cells annotated in the respective column with different colors. Hide all labels by pressing CMD+I.

If you have more rows in the table, use the Split button to identify them faster:

  1. Use the action buttons on the labels to adjust the annotations of your cells:

a. Find Missing Cells: This button allows you to auto-annotate missing cells. The target button ( on the column label can help auto-annotate any cells that may have been left unidentified in a particular column. Use this button in the following cases:

  1. When a user manually created rows that the machine had failed to identify.
  2. When a user manually deleted all rows, created new rows from scratch, and annotated a single row.

b. Select all column cells on page: This button ( will select all cells from the column you’re currently working with.

c. Delete all column cells on page: This button ( allows you to delete all column cells on the page.

Other actions

You can use the Scroll freeze button ( located at the top of the page if you have more pages in your document. Clicking it improves the performance of the system by rendering the images on each page faster. You can also extend a row to the next page by using the button, located between the pages - Extend row [row’s number] to next page.

Insert a row by clicking the button on the left side of the page or the button in the middle of the page if you don’t have any rows.

Right-click on the row for the following options:

Click Manually Re-identify Table if you need to start over.

If you have a nested table, follow Steps 1. and 2. described above. Learn more about Nested tables in What is a Nested table?

The Table Identification QA task:

The Table ID QA task is similar to the Supervision task. Note that once all tables reach consensus, the document will also reach consensus. Learn more about consensus in Transcription Supervision Consensus.

Limitations

Table ID Models

After completing your annotations, you will be able to train a Table Identification model.

It enables cell-level predictions and automatic table processing. A Table ID model can be trained to automatically identify regular and nested tables.

Table ID models look at the transcribed text to improve table identification. This feature is called Table Detector and supports the following scenarios:

To train and deploy a model, go to the Model Details page. Once you determine a Semi-structured layout where you would like to train a model, there are two ways to get to the Model Details page:

  1. Go to Library > Models, select Identification Models from the drop-down list at the top of the page, and then click on the name of the model.
  2. Go to Layouts, click on the name of the layout, and then click on the name of the Identification Model on the Layout Details page.

You can process multiple tables within a document. Note that they will be trained one after another when initiating the model training.

The model for each table is available in the Table Identification Models card. To initiate a model training follow the steps described in Training a New Table Identification Model.

Learn more about navigating Training Data Management and using its features in Training Data Management Features and Training Data Management.