Skip to content
Showcase/Named Entity Recognition
intermediatetext

Named Entity Recognition

Span-based annotation for identifying entities like persons, organizations, locations, and dates in text.

PERORGLOCPERORGLOCDATESelect text to annotate

Configuration Fileconfig.yaml

# Named Entity Recognition Configuration
# Generated by Potato Annotation Showcase

port: 8000
server_name: localhost
annotation_task_name: "Named Entity Recognition"

# Data configuration
data_files:
  - "data.json"

item_properties:
  id_key: id
  text_key: text

# Output
output_annotation_dir: "annotation_output/"
output_annotation_format: "json"

# Annotation scheme
annotation_schemes:
  - annotation_type: span
    name: entities
    description: "Highlight named entities in the text and select their type"
    labels:
      - PERSON
      - ORGANIZATION
      - LOCATION
      - DATE
      - MISC
    label_colors:
      PERSON: "#3b82f6"
      ORGANIZATION: "#10b981"
      LOCATION: "#f59e0b"
      DATE: "#8b5cf6"
      MISC: "#6b7280"
    tooltips:
      PERSON: "Names of people (e.g., 'John Smith', 'Dr. Johnson')"
      ORGANIZATION: "Companies, institutions, agencies (e.g., 'Google', 'United Nations')"
      LOCATION: "Places, cities, countries (e.g., 'New York', 'France')"
      DATE: "Dates and time expressions (e.g., 'January 2024', 'next Monday')"
      MISC: "Other named entities that don't fit the above categories"
    allow_overlapping: false

# User configuration
allow_all_users: true

# Task assignment
instances_per_annotator: 50
annotation_per_instance: 2

Get This Design

This design is available in our showcase. Copy the configuration below to get started.

Quick start:

# Create your project folder
mkdir named-entity-recognition
cd named-entity-recognition
# Copy config.yaml from above
potato start config.yaml

Details

Annotation Types

span

Domain

NLP

Use Cases

Named Entity RecognitionInformation Extraction

Tags

NERentitiesspan annotationinformation extraction

Related Designs

Aspect-Based Sentiment Analysis

Identification of aspect terms in review text with sentiment polarity classification for each aspect. Based on SemEval-2016 Task 5 (ABSA).

spanradio

BioNLP 2011 - Gene Regulation Event Extraction

Biomedical event extraction for gene regulation, based on the BioNLP 2011 Shared Task (Kim et al., ACL Workshop 2011). Annotators identify biological entities and mark regulatory events such as gene expression, transcription, and protein catabolism in scientific abstracts.

event_annotationspan

Causal Medical Claim Detection and PICO Extraction

Detection of causal claims in medical texts and extraction of PICO (Population, Intervention, Comparator, Outcome) elements. Based on SemEval-2023 Task 8 (Khetan et al.).

spanradio