CoFiF Plus: A French Financial Narrative Summarisation Corpus.
International Conference on Language Resources and Evaluation (LREC)(2022)
Abstract
Natural Language Processing is increasingly being applied in the finance and business industry to analyse the text of many different types of financial documents. Given the increasing growth of firms around the world, the volume of financial disclosures and financial texts in different languages and forms is increasing sharply and therefore the study of language technology methods that automatically summarise content has grown rapidly into a major research area. Corpora for financial narrative summarisation exist in English, but there is a significant lack of financial text resources in the French language. To remedy this, we present CoFiF Plus, the first financial narrative summarisation dataset providing a comprehensive set of financial text written in the French language. The dataset has been extracted from french financial reports published in PDF file format. It is composed of 1,703 reports from the most capitalised companies in France (Euronext Paris) covering a time frame from 1995 to 2021. This paper describes the collection, annotation and validation of the financial reports and their summaries. It also describes the dataset and gives the results of some baseline summarisers.
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Key words
Summarisation, French financial narratives, French NLP, corpus, dataset construction
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