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Showcase/Multilingual Semantic Word Similarity
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Multilingual Semantic Word Similarity

Graded word similarity judgment across multiple languages, based on SemEval-2017 Task 2. Annotators rate how semantically similar two words are on a continuous scale, supporting cross-lingual evaluation of distributional semantic models.

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Configuration Fileconfig.yaml

# Multilingual Semantic Word Similarity
# Based on Camacho-Collados et al., SemEval 2017
# Paper: https://aclanthology.org/S17-2002/
# Dataset: http://alt.qcri.org/semeval2017/task2/
#
# Annotators judge the degree of semantic similarity between two words
# on a graded scale. This task supports multilingual and cross-lingual
# word pair evaluation for distributional semantic models.
#
# Similarity Scale (Likert):
# 1 = Completely Different (no semantic overlap)
# 2 = Slightly Similar (vague topical connection)
# 3 = Moderately Similar (share some meaning)
# 4 = Very Similar (closely related meaning)
# 5 = Identical Meaning (perfect synonyms in context)
#
# Annotation Guidelines:
# 1. Read both words carefully
# 2. Consider the most common sense of each word
# 3. Rate how semantically similar the two words are
# 4. Use the full range of the scale
# 5. Note the language of the word pair

annotation_task_name: "Multilingual Semantic Word Similarity"
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: likert
    name: similarity_rating
    description: "How semantically similar are these two words?"
    min_label: "Completely Different"
    max_label: "Identical Meaning"
    size: 5

  - annotation_type: slider
    name: similarity_slider
    description: "Rate the semantic similarity using the slider (0 = unrelated, 4 = identical)"
    min_value: 0
    max_value: 4
    starting_value: 2

annotation_instructions: |
  You will be shown two words, possibly from different languages. Your task is to judge
  how semantically similar these two words are.

  Use the Likert scale for a quick categorical judgment (1-5) and the slider for a
  fine-grained continuous rating (0-4).

  Consider the most common meaning of each word. Two words are semantically similar
  if they refer to the same or closely related concepts.

html_layout: |
  <div style="padding: 15px; max-width: 800px; margin: auto;">
    <div style="background: #f0f9ff; border: 1px solid #bae6fd; border-radius: 8px; padding: 16px; margin-bottom: 16px;">
      <div style="display: flex; justify-content: center; align-items: center; gap: 40px;">
        <div style="text-align: center;">
          <span style="color: #64748b; font-size: 13px;">Word 1</span>
          <p style="font-size: 22px; font-weight: bold; margin: 4px 0;">{{text}}</p>
        </div>
        <span style="font-size: 24px; color: #94a3b8;">~</span>
        <div style="text-align: center;">
          <span style="color: #64748b; font-size: 13px;">Word 2</span>
          <p style="font-size: 22px; font-weight: bold; margin: 4px 0;">{{word_2}}</p>
        </div>
      </div>
      <p style="text-align: center; color: #64748b; margin-top: 8px;">Language: <strong>{{language}}</strong></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": "wordsim_001",
    "text": "car",
    "word_2": "automobile",
    "language": "English"
  },
  {
    "id": "wordsim_002",
    "text": "bank",
    "word_2": "river",
    "language": "English"
  }
]

// ... and 8 more items

Get This Design

View on GitHub

Clone or download from the repository

Quick start:

git clone https://github.com/davidjurgens/potato-showcase.git
cd potato-showcase/semeval/2017/task02-word-similarity
potato start config.yaml

Details

Annotation Types

likertslider

Domain

NLPSemEvalSemantics

Use Cases

Word SimilarityLexical SemanticsCross-Lingual NLP

Tags

semevalsemeval-2017shared-taskword-similaritymultilinguallexical-semantics

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