Universal Data Tool
  • Universal Data Tool Docs
  • Installation
  • Running On-Premise
  • Collaborative Labeling
  • Building and Labeling Datasets
    • Image Segmentation
    • Image Classification
    • Text Classification
    • Named Entity Recognition
    • Entity Relations / Part of Speech Tagging
    • Audio Transcription
    • Data Entry
    • Video Segmentation
    • Composite Interfaces
    • Landmark / Pose Annotation
  • Importing Data
    • Upload or Open Directories
    • Import File URLs
    • Import COCO Images
    • Import from Google Drive
    • Import from AWS S3 Bucket
    • Import from CSV or JSON
    • Import using AWS Cognito
    • Import Text Snippets
  • The Format .udt.json
    • What is the .udt.json format?
    • What is the .udt.csv format?
  • Machine Learning
    • Jupyter Notebook Integration
    • Import Datasets into Pandas
    • Fast.ai
      • Fast.ai Image Classification
      • Fast.ai Image Segmentation
  • Integrate with Any Web Page
    • Integrate with the Javascript Library
    • Getting Started with React
  • Train your Workforce
    • Getting Started with UDT Courses
  • Frequently Asked Questions
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On this page
  • Setup the Dataset
  • Import Data
  • Label your Data (with friends!)
  • Export and Use

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  1. Building and Labeling Datasets

Entity Relations / Part of Speech Tagging

Named Entity Linking (PoS tagging) with the Universal Data Tool. Draw relationships between words or phrases within text.

PreviousNamed Entity RecognitionNextAudio Transcription

Last updated 4 years ago

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Setup the Dataset

Navigate to udt.dev and click "New File"

Then select the Text Entity Relations button from the Setup > Data Type page.

You can now configure the interface you'd like for you Text Entity Relations dataset by adding any labels you'd like to display per sample.

Import Data

You can use any of the following methods to import text data.

  • Import Text Snippets

  • Import from CSV or JSON

Label your Data (with friends!)

Go to the Label tab to begin labeling data. See the Collaborative Labeling Guide to label with friends or a team of your labelers.

Export and Use

The easiest way to use a Entity Relations dataset is using the JSON format. Use the "Download JSON" button at the top when you're done labeling and check out the Text Entity Relations JSON Specification.

Here's what a JSON sample looks like in the resultant dataset:

{
  "document": "This strainer makes a great hat, I'll wear it while I serve spaghetti!",
  "annotation": {
    "entities": [
      {
        "text": "strainer",
        "label": "hat",
        "start": 5,
        "end": 13,
        "textId": "id1"
      },
      {
        "text": "spaghetti",
        "label": "food",
        "start": 60,
        "end": 69,
        "textId": "id2"
      },
      {
        "text": "I'll",
        "start": 33,
        "end": 37,
        "textId": "id3"
      },
      {
        "text": "wear",
        "start": 38,
        "end": 42,
        "textId": "id4"
      }
    ],
    "relations": [
      {
        "from": "id3",
        "to": "id4",
        "label": "subject-doing"
      }
    ]
  }
}
Click "New File" on udt.dev
Select Text Relations when choosing an interface
Text Entity Relation Configuration
Example of Text Entity Relations labeling