2025年3月26日 · 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.

2023年6月6日 · 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.

In the task of Financial Numeric Extreme Labelling (FNXL), your job is to identify and label the semantic role of each token in a sentence.

2024年10月4日 · The FNXL task focuses on the identification and categorization of numeric values within financial documents. This involves labeling numbers based on their type (e.g., revenue, profit, expense) and their relevance in the context of the text.

fnxl数据集由印度理工学院卡拉格普尔分校和高盛数据科学与机器学习团队创建，专注于金融领域的数字极端标注。 该数据集包含79,088个句子，总计142,922个数字被标注，使用2,794个标签。

meric Extreme Labelling (FNXL), annotated with 2,794 labels. We benchmark the perfor-mance of the FNXL dataset by formulating the task as (a) a sequence labelling problem and (b) a pipeline with span extraction followed by Extreme Classication. Although the two approaches perform comparably, the pipeline solution provides a slight edge for the ...

2023年6月6日 · 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,...

This repository contains supplements for the ACL 2023 Findings paper titled: - GitHub - soummyaah/FNXL: This repository contains supplements for the ACL 2023 Findings paper titled:

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