The financial narrative summarisation shared task (FNS 2022 & 2023): Datasets

<p>Financial Narrative Processing (FNP) consists of workshops organized by Lancaster University at international NLP conferences to address various aspects of automatic processing of financial narratives, including automatic summarization. The LLI-UAM participated in 2022 and 2023 by creating Spanish-language datasets for the FNS shared task (evaluating AI systems using the same dataset to compare different approaches).</p>
<p>The dataset consists of complete annual reports from companies, chairmen's letters (which are considered summaries of the reports), and a version created by linguists that consists of a summary of the chairmen's letters in fewer than 1,000 words. Based on the dataset, participants train their models to generate summaries similar to the chairman's letter or the simplified version for new evaluation reports that were not shared during training. The evaluation is conducted using the ROUGE metric.</p>
<p>The dataset is composed of 262 financial reports taken from the FinT-esp corpus. The reports were originally in PDF format and were converted into plain text, removing tables, footnotes, headers, and retaining only the narrative content. The length of the reports ranges from 40 to 400 pages, with an average of 36,285 words. A total of 262 chairman's letters were extracted, and an additional 262 summary documents were created, each containing fewer than 1,000 words. This publication is about the dataset from the 2022 and 2023 competition.</p>
<p>These are txt files containing the full report, their respective chairmen's letters, and the summaries of these letters. They belong to The Financial Narrative Summarisation Shared Task (2022 and 2023).</p>