[LFG] Call for participation - FinTOC shared task

[FinTOC SharedTask]

Call for participation - FinTOC shared task

⇒ The Second Financial Narrative Processing Workshop (FNP 2019)

⇒ *The 22nd Nordic Conference on Computational Linguistics (NoDaLiDa’19)*


Task: Predict a Table of Content (ToC) from financial documents.

Two sub-tasks are proposed :

   -

   Detection of titles
   -

   Prediction of a ToC


Shared task webpage: http://wp.lancs.ac.uk/cfie/shared-task/

Shared task contact: fin.toc.task at gmail.com


Important dates

Registration deadline: June 29, 2019

Submission deadline: July 13, 2019

Workshop day: September 30, 3019



*More reading* 👇

*“Financial Document Structure Extraction”*

*Introduction:*

A vast amount of financial documents are created and published constantly
in machine-readable formats (generally PDF file format), with only minimal
structure information. Firms use such documents to report their activities,
financial situation or potential investment plans to shareholders,
investors and the financial markets, basically corporate annual reports
containing detailed financial and operational information.

In some countries as in the US or in France, regulators as EDGAR SEC or AMF
require firms to follow a certain template when reporting their financial
results to insure standardisation and consistency across firms’
disclosures. In other European countries, on the other hand, the management
usually have more discretion on what where and how to report resulting in
lack of standardisation between financial documents published within the
same market.

In this shared task, we focus on analysing Financial Prospectuses; official
PDF documents in which investment funds precisely describe their
characteristics and investment modalities. Although the content they must
include is often regulated, their format is not standardized and displays a
great deal of variability ranging from plain text format, towards more
graphical and tabular presentation of data and information. The majority of
prospectuses are published without a table of content (TOC), which is
usually needed to help readers to navigate within the document by following
a simple outline of headers and page numbers, and assist professional teams
in checking if all the contents required are fully included. Thus,
automatic analyses of prospectuses to extract their structure is becoming
more and more vital to many firms across the world.


*Task:*

As part of the Financial Narrative Processing Workshop, we present a shared
task on Financial Document Structure Extraction.

Systems participating in this shared task will be given a sample collection
of financial prospectuses with different level of structure and different
lengths (document sizes), which are to be automatically analyzed to extract
structural information and build a table of content.

The task will contain two sub tasks are:

a) Title detection

This is a binary classification task aiming at detecting titles in
financial prospectuses. Given a set of text blocks, the goal is to classify
each given text block as a ‘title’ or ‘non-title’. Titles can have
different layouts and they have to be distinguished from the regular text.

b) TOC structure extraction

The TOC is a hierarchical organisation of the headers of a document. In
this subtask, we provide only the headers of a prospectus, and the goal is
to (i) identify the hierarchical level of the header (ii) organize the
headers of the document according to this hierarchical structure. Note that
two headers, with the same layout and the same text can have different
hierarchical levels depending on their location in the document.

Participants need to register. Once registered, all participating teams
will be provided with a common training dataset, which includes common
pre-processed input and corrected output. A common development set will
also be provided. A blind test data set will be used to evaluate the output
of the participating teams. An evaluation script will be provided to all
the teams. In addition to the PDF version of the documents, we will provide
their XML representation.
------------------------------

*Background:*

Existing work on book and document table of contents (TOC) recognition has
been almost all on small size, application-dependent, and domain-specific
datasets. However, TOC of documents from different domains differ
significantly in their visual layout and style, making TOC recognition a
challenging problem for a large scale collection of heterogeneous documents
and books. Compared to regular books (mostly provided in a full text format
with limited structural information such as pages and paragraphs),
Financial documents, containing textual and non textual content, have a
more sophisticated structure including, parts, sections, sub-sections,
sub-sub-sections.

Furthermore, TOCs provide at a glance, the entire structure and layout of a
document, making its recognition an important feature for document
structure extraction and understanding. Extracting a TOC is just a primary
step to a pipeline of information extraction and document extensive
analyses, to monitor investment rules and examine change over time relative
to financial results.


*Important Dates:*

(suggested plan FNP FinTOC task at NoDaLiDa 2019)


   - March 25, 2019: First announcement of shared task
   - April 10, 2019: set up of shared task website
   - April 15, 2019: registration begins and release of initial training
   sets and scoring script
   - May 18, 2019: Final training data release
   - Jun 29, 2019: registration deadline
   - July 6, 2019: test set available
   - July 13, 2019: systems’ outputs collected
   - July 20, 2019: system results due to participants
   - July 27, 2019: shared task system papers due
   - Aug 10, 2019: reviews due
   - Aug 17, 2019: notification of acceptance
   - Aug 24, 2019: camera ready version of shared task system papers due
   - Sep 30, 2019: Workshop day

*Shared Task Contact:*

Questions about FinTOC-2019 shared task can be sent to:

fin.toc.task at gmail.com
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