Hypernym Discovery
Discovery of hypernyms (broader terms) for a given target term in context, with classification of the hypernym relationship type. Based on SemEval-2018 Task 9.
Fichier de configurationconfig.yaml
# Hypernym Discovery
# Based on Camacho-Collados et al., SemEval 2018
# Paper: https://aclanthology.org/S18-1115/
# Dataset: https://competitions.codalab.org/competitions/17119
#
# This task asks annotators to identify the hypernym (broader/parent term)
# of a target term given its usage in context. Annotators also classify
# whether the hypernym relation is for an entity, concept, or both.
#
# Hypernym Type Labels:
# - Entity: The target term refers to a named entity (person, place, organization)
# - Concept: The target term refers to a general concept or class
# - Both: The target term can be interpreted as both entity and concept
annotation_task_name: "Hypernym Discovery"
task_dir: "."
data_files:
- sample-data.json
item_properties:
id_key: "id"
text_key: "text"
output_annotation_dir: "annotation_output/"
output_annotation_format: "json"
port: 8000
server_name: localhost
annotation_schemes:
- annotation_type: text
name: hypernym
description: "What is the hypernym (broader/parent term) of the target term?"
- annotation_type: radio
name: hypernym_type
description: "Is the target term an entity, a concept, or both?"
labels:
- "Entity"
- "Concept"
- "Both"
keyboard_shortcuts:
"Entity": "1"
"Concept": "2"
"Both": "3"
tooltips:
"Entity": "The target term is a named entity (person, place, organization)"
"Concept": "The target term is a general concept, class, or category"
"Both": "The target term can be interpreted as both an entity and a concept"
annotation_instructions: |
You will be shown a sentence containing a target term (highlighted) along with its domain.
Your task is to:
1. Identify the hypernym (broader/parent category) of the target term.
2. Classify whether the target is an entity, concept, or both.
For example, the hypernym of "dog" is "animal", and the hypernym of "Paris" is "city".
html_layout: |
<div style="padding: 15px; max-width: 800px; margin: auto;">
<div style="display: flex; gap: 12px; margin-bottom: 12px;">
<div style="background: #fefce8; border: 1px solid #fde68a; border-radius: 8px; padding: 12px; flex: 1;">
<strong style="color: #a16207;">Target Term:</strong>
<span style="font-size: 15px; font-weight: bold;">{{target_term}}</span>
</div>
<div style="background: #f0fdf4; border: 1px solid #bbf7d0; border-radius: 8px; padding: 12px; flex: 1;">
<strong style="color: #15803d;">Domain:</strong>
<span style="font-size: 15px;">{{domain}}</span>
</div>
</div>
<div style="background: #f0f9ff; border: 1px solid #bae6fd; border-radius: 8px; padding: 16px; margin-bottom: 16px;">
<strong style="color: #0369a1;">Context:</strong>
<p style="font-size: 16px; line-height: 1.7; margin: 8px 0 0 0;">{{text}}</p>
</div>
</div>
allow_all_users: true
instances_per_annotator: 50
annotation_per_instance: 2
allow_skip: true
skip_reason_required: false
Données d'exemplesample-data.json
[
{
"id": "hypernym_001",
"text": "The python is one of the largest snakes found in tropical regions of Asia and Africa.",
"target_term": "python",
"domain": "Biology"
},
{
"id": "hypernym_002",
"text": "Researchers used a convolutional neural network to classify satellite images for land use detection.",
"target_term": "convolutional neural network",
"domain": "Computer Science"
}
]
// ... and 8 more itemsObtenir ce design
Clone or download from the repository
Démarrage rapide :
git clone https://github.com/davidjurgens/potato-showcase.git cd potato-showcase/semeval/2018/task09-hypernym-discovery potato start config.yaml
Détails
Types d'annotation
Domaine
Cas d'utilisation
Étiquettes
Vous avez trouvé un problème ou souhaitez améliorer ce design ?
Ouvrir un ticketDesigns associés
CODWOE - Comparing Dictionaries and Word Embeddings
Definition generation and concreteness classification for words in context, comparing dictionary definitions with distributional word representations. Based on SemEval-2022 Task 1 (Mickus et al.).
Argument Reasoning in Civil Procedure
Legal argument reasoning task requiring annotators to answer multiple-choice questions about civil procedure by selecting the best answer and providing legal reasoning. Based on SemEval-2024 Task 5.
BRAINTEASER - Commonsense-Defying QA
Lateral thinking and commonsense-defying question answering task requiring annotators to select answers to brain teasers that defy default commonsense assumptions and provide explanations. Based on SemEval-2024 Task 9 (BRAINTEASER).