The U.S. Securities and Exchange Commission (SEC) mandates all public companies to file periodic financial statements that should contain numerals annotated with a particular label from a taxonomy. In this paper, we formulate the task of automating the assignment of a label to a particular numeral span in a sentence from an extremely large label set. Towards this task, we release a dataset, Financial Numeric Extreme Labelling (FNXL), annotated with 2,794 labels. We benchmark the performance of the FNXL dataset by formulating the task as (a) a sequence labelling problem and (b) a pipeline with span extraction followed by Extreme Classification. Although the two approaches perform comparably, the pipeline solution provides a slight edge for the least frequent labels.
Cite
@article{arxiv.2306.03723,
title = {Financial Numeric Extreme Labelling: A Dataset and Benchmarking for XBRL Tagging},
author = {Soumya Sharma and Subhendu Khatuya and Manjunath Hegde and Afreen Shaikh. Koustuv Dasgupta and Pawan Goyal and Niloy Ganguly},
journal= {arXiv preprint arXiv:2306.03723},
year = {2023}
}