Multilingual Word-in-Context
Cross-lingual word sense disambiguation task where annotators determine whether a target word is used in the same sense across two different contexts, based on SemEval-2021 Task 2 (Martelli et al.).
Configuration Fileconfig.yaml
This Potato config reproduces the annotation task. Save it as config.yaml and run potato start config.yaml to try it.
# Multilingual Word-in-Context
# Based on Martelli et al., SemEval 2021
# Paper: https://aclanthology.org/2021.semeval-1.3/
# Dataset: https://github.com/SapienzaNLP/mcl-wic
#
# Annotators decide whether a target word carries the same meaning
# in two different sentence contexts. The task supports multilingual
# and cross-lingual settings.
annotation_task_name: "Multilingual Word-in-Context"
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: radio
name: sense_match
description: "Does the target word have the same sense in both contexts?"
labels:
- "Same Sense"
- "Different Sense"
keyboard_shortcuts:
"Same Sense": "1"
"Different Sense": "2"
tooltips:
"Same Sense": "The target word is used with the same meaning in both contexts"
"Different Sense": "The target word is used with different meanings in the two contexts"
annotation_instructions: |
You will see a target word used in two different sentence contexts. Your task
is to determine whether the target word carries the same meaning (sense) in both
sentences.
1. Read both contexts carefully.
2. Focus on the meaning of the target word in each sentence.
3. Select "Same Sense" if the word has the same meaning in both contexts.
4. Select "Different Sense" if the word has different meanings.
Example:
- "bank" in "I went to the bank to deposit money" vs "The river bank was muddy"
-> Different Sense
html_layout: |
<div style="padding: 15px; max-width: 800px; margin: auto;">
<div style="background: #fefce8; border: 1px solid #fde68a; border-radius: 8px; padding: 16px; margin-bottom: 16px; text-align: center;">
<strong style="color: #a16207;">Target Word:</strong>
<span style="font-size: 20px; font-weight: bold; color: #b45309;">{{target_word}}</span>
<span style="margin-left: 12px; color: #78716c;">({{language}})</span>
</div>
<div style="background: #f0f9ff; border: 1px solid #bae6fd; border-radius: 8px; padding: 16px; margin-bottom: 12px;">
<strong style="color: #0369a1;">Context 1:</strong>
<p style="font-size: 16px; line-height: 1.7; margin: 8px 0 0 0;">{{text}}</p>
</div>
<div style="background: #f0fdf4; border: 1px solid #bbf7d0; border-radius: 8px; padding: 16px; margin-bottom: 16px;">
<strong style="color: #15803d;">Context 2:</strong>
<p style="font-size: 16px; line-height: 1.7; margin: 8px 0 0 0;">{{context_2}}</p>
</div>
</div>
allow_all_users: true
instances_per_annotator: 50
annotation_per_instance: 2
allow_skip: true
skip_reason_required: false
Sample Datasample-data.json
[
{
"id": "wic_001",
"text": "The bank approved my loan application after reviewing my credit history.",
"context_2": "We sat on the bank of the river and watched the sunset.",
"target_word": "bank",
"language": "English"
},
{
"id": "wic_002",
"text": "She decided to run for president of the student council.",
"context_2": "He went for a run in the park every morning before work.",
"target_word": "run",
"language": "English"
}
]
// ... and 8 more itemsGet This Design
Clone or download from the repository
Quick start:
git clone https://github.com/davidjurgens/potato-showcase.git cd potato-showcase/semeval/2021/task02-crosslingual-wic potato start config.yaml
Dataset & paper
Martelli et al., SemEval 2021
Citation (BibTeX)
@inproceedings{martelli-etal-2021-semeval,
title = "{S}em{E}val-2021 {T}ask 2: {M}ultilingual and {C}ross-lingual {W}ord-in-{C}ontext {D}isambiguation ({MCL}-{W}i{C})",
author = "Martelli, Federico and Kalach, Najla and Tola, Gabriele and Navigli, Roberto",
booktitle = "Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.semeval-1.3/",
doi = "10.18653/v1/2021.semeval-1.3",
pages = "24--36"
}Details
Annotation Types
Domain
Use Cases
Tags
Found an issue or want to improve this design?
Open an IssueRelated Designs
AdMIRe - Advancing Multimodal Idiomaticity Representation
Multimodal idiomaticity task (SemEval-2025 Task 1, Subtask A): given a potentially idiomatic nominal compound in a context sentence, annotators rank five candidate images by how well each represents the sense in which the compound is used.
AfriSenti - African Language Sentiment
Sentiment analysis for tweets in African languages, classifying text as positive, negative, or neutral. Covers 14 African languages including Amharic, Hausa, Igbo, Yoruba, and Swahili. Based on SemEval-2023 Task 12 (Muhammad et al.).
Argument Reasoning in Civil Procedure
Legal argument reasoning task from SemEval-2024 Task 5. Given a short introduction to a U.S. civil procedure topic, a question, and a candidate answer (a possible solution argument), annotators perform binary classification: judge whether the answer candidate is correct (True) or incorrect (False). Questions and answers are drawn from a civil procedure textbook widely used in U.S. law schools.