Showcase/Named Entity Recognition
intermediatetext

Named Entity Recognition

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

📝

text annotation

Configuration Fileconfig.yaml

# Named Entity Recognition Configuration
# Generated by Potato Annotation Showcase

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

# Data configuration
data_files:
  - data.json
id_key: id
text_key: text

# Output
output_file: annotations.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

Complex Named Entity Recognition (MultiCoNER)

Recognize complex and emerging named entities. Based on SemEval 2022/2023 MultiCoNER. Identify creative works, products, groups, and other challenging entity types.

span

Coreference Resolution (OntoNotes)

Link pronouns and noun phrases to the entities they refer to in text. Based on the OntoNotes coreference annotation guidelines and CoNLL shared tasks. Identify mention spans and cluster coreferent mentions together.

spanradio

Dialogue Relation Extraction (DialogRE)

Extract relations between entities in dialogue. Based on Yu et al., ACL 2020. Identify 36 relation types between speakers and entities mentioned in conversations.

spanradio