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NLP
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About |
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The volume of available financial information is increasing sharply and therefore the study of NLP methods that automatically summarise content has grown rapidly into a major research area. The Financial Narrative Summarisation (FNS 2020) aims to demonstrate the value and challenges of applying automatic text summarisation to financial text written in English, usually referred to as financial narrative disclosures. The task dataset has been extracted from UK annual reports published in PDF file format. The participants are asked to provide structured single summaries, based on real-world, publicly available financial annual reports of UK firms by extracting information from different key sections. Participants will be asked to generate summaries that reflects the analysis and assessment of the financial trend of the business over the past year, as provided by annual reports. For the evaluation we aim to use the JRouge package for ROUGE, from Marina Litvak’s team (https://bitbucket.org/nocgod/jrouge/wiki/Home), using multiple variants (ROUGE-2, ROUGE-SU4). |
Call for Papers |
TaskFor FNS 2020 task we focus on annual reports produced by UK firms listed on The London Stock Exchange (LSE). In the UK and elsewhere, annual report structure is much less rigid than those produced in the US. Companies produce glossy brochures with a much looser structure, and this makes automatic summarisation of narratives in UK annual reports a challenging task. This is due to the fact that the structure of those documents needs to be extracted first in order to summarise the narrative sections of the annual reports. This can happen by detecting narrative sections that usually include the management disclosures rather than the financial statements of the annual reports. In this task we will introduce a new summarisation task which we call Financial Narrative Summarisation. In this task the summary requires extraction from different key sections found in the annual reports. Those sections are usually referred to as “narrative sections” or “front-end” sections and they usually contain textual information and reviews by the firm’s management and board of directors. Sections containing financial statements in terms of tables and numbers are usually referred to as “back-end” sections and are not supposed to be part of the narrative summaries. UK annual reports are lengthy documents with around 80 pages on average, some annual reports could span over more than 250 pages, making the summarisation task a challenging but an academically interesting one. For the purpose of this task we will ask the participants to produce one summary for each annual report. The summary length should not exceed 1000 words. We advise that the summary is generated/extracted based on the narrative sections, therefore the participating summarisers need to be trained to detect narrative sections before creating the summaries. The MultiLing team along with help from Barcelona’s UPF summarisation team will help in organising the shared task including the generation of the evaluation results and final proceedings. The MultiLing team have a rich experience in organising summarisation tasks since 2011. |
Summary |
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FNS 2020 : The 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation will take place in Barcelona, Spain. It’s a 1 day event starting on Sep 13, 2020 (Sunday) and will be winded up on Sep 13, 2020 (Sunday). FNS 2020 falls under the following areas: NLP, etc. Submissions for this Workshop can be made by Apr 06, 2020. Authors can expect the result of submission by May 01, 2020. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the FNS 2020
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Credits and Sources |
| [1] FNS 2020 : The 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation |
