metadata
task_categories:
- feature-extraction
- sentence-similarity
language:
- en
size_categories:
- 1K<n<10K
license: mit
Dataset Card for FinSTS Golden Dataset
Table of Contents
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Splits
- Dataset Creation
- Citing & Authors
Dataset Summary
The FinSTS Golden Dataset is designed for financial semantic textual similarity tasks. It contains a development set of 2001 sentence pairs and a test set of 1999 sentence pairs, annotated to reflect the degree of semantic similarity between financial texts. The sentence pairs are collected from earnings call transcripts and 10-K filings, making this dataset ideal for evaluating models in financial text analysis.
Supported Tasks and Leaderboards
- Text Similarity: This dataset can be used to evaluate models measuring the semantic similarity between pairs of financial sentences.
Languages
The dataset is in English.
Dataset Structure
Data Fields
split: Indicates whether the data point belongs to the development or test set.sentence1: The first sentence in the pair.sentence2: The second sentence in the pair.gpt_score: An integer score between 0 and 5 indicating the degree of semantic similarity between the two sentences, annotated by GPT-4 Turbo API.score: An integer score between 0 and 5 indicating the degree of semantic similarity between the two sentences, annotated by 4 human experts.
Example
{
"split": "dev",
"sentence1": "Unlike many industrial companies, substantially all of our assets and virtually all of our liabilities are monetary in nature.",
"sentence2": "Unlike most industrial companies, virtually all of our assets and liabilities are monetary in nature.",
"gpt_score": 5,
"score": 4
}