Entity Linking
Span annotation with knowledge base linking to Wikidata. Annotators highlight entities and link them to their corresponding Wikidata entries via an inline search widget.

Configuration Fileconfig.yaml
# Entity Linking Configuration
# Demonstrates linking span annotations to Wikidata knowledge base
annotation_task_name: Entity Linking Example
task_dir: .
output_annotation_dir: annotation_output
output_annotation_format: json
data_files:
- data.json
item_properties:
id_key: id
text_key: text
user_config:
allow_all_users: true
users: []
annotation_schemes:
- annotation_type: span
name: ner
description: Highlight and link named entities to Wikidata
labels:
- name: PERSON
tooltip: "A person's name (e.g., Albert Einstein, Marie Curie)"
- name: ORGANIZATION
tooltip: "An organization name (e.g., NASA, United Nations)"
- name: LOCATION
tooltip: "A location or place name (e.g., Paris, Mount Everest)"
- name: EVENT
tooltip: "A named event (e.g., World War II, Olympics)"
sequential_key_binding: true
# Entity linking configuration
entity_linking:
enabled: true
knowledge_bases:
- name: wikidata
type: wikidata
language: en
auto_search: true
required: false
multi_select: false
# UI configuration
ui:
display_instance_id: true
Sample Datasample-data.json
[
{
"id": "el_1",
"text": "Albert Einstein developed the theory of relativity while working at the Swiss Patent Office in Bern.",
"context": "Physics history"
},
{
"id": "el_2",
"text": "The United Nations headquarters in New York hosted the General Assembly meeting on climate change.",
"context": "International affairs"
}
]
// ... and 1 more itemsGet This Design
This design is available in our showcase. Copy the configuration below to get started.
Quick start:
# Create your project folder mkdir entity-linking cd entity-linking # Copy config.yaml from above potato start config.yaml
Details
Annotation Types
Domain
Use Cases
Tags
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).
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.
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.).