UFO
Understanding of non-Financial Objects
in Financial Reports

Yasutomo Kimura

Takahito Kondo

Kazuma Kadowaki

Hokuto Ototake

Makoto P. Kato

Otaru University of Commerce

Kyoto Sangyo University

The Japan Research Institute,LimitedFukuoka University

University of Tsukuba

NTCIR-17 Kick-Off Event
September 28th (Wed) 2022

Table of contents●

What is annual securities reports?
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EDINET
XBRL
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Taxonomy
Instance

What kinds of tables are included in annual securities reports?
What is the relationship between the text and tables in annual securities
reports?
Whati is UFO task?
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Understanding of non-Financial Objects in Financial Reports■■

What is TDE (Table Data Extraction)?
What is TTRE(Text-to-Table Relationship Extraction)?

What is annual securities reports?
Annual securities reports are●●●reports that listed and other companies arerequired to prepare.
disclosed to the outside every fiscal year
electronically submitted to EDINET

Annual securities reports

EDINET(Electronic Disclosure for Investors' NETwork)●

An electronic disclosure system for disclosure documents

XBRL
eXtensible Business Reporting Language●●A standardized XML-based language for making information available forfinancial reporting
Link related elements using taxonomy and instance○○

Taxonomy: Attributes of elements to be linked (name, etc.)
Instance: Set period, currency unit, etc. for attribute value

https://www.fsa.go.jp/search/20211109/1b-1_GaiyoSetsumei.pdf

Issues related to annual securities reports
Annual securities reports●●●●

Different types of tables
Different notation
Non-financial table cells that is NOT assigned a taxonomy
Text without taxonomies
Text

Table
Name of table

MetadataHeader

Ordinary profit for the current consolidated fiscal year was 300.5 billion yen,

an increase of 66.9 billion yen from 233.5 billion yen for the previous consolidated fiscal

AttributeData

due to the increase in operating profit.
ReasonUFO Task
Understanding of non-Financial Objects in Financial Reports
Purpose●We aim to develop a technology for extracting structured information from tabular data and documents.

Table Data Extraction (TDE)●TDE is a subtask that extracts data from tables contained in reports for comparison between companies.

Text-to-Table Relationship Extraction (TTRE)●

TTRE is a relationship extraction task that connects the values contained in the table of reports and therelated texts.

Why is the task named UFO?
●●●“有報” stands for “有価証券報告書”
The pronunciation of 有報 is “júfoʊ”The pronunciation of UFO is “júfoʊ”, NOT “júːèfóʊ” in Japan

Annual securities reports

Table Data Extraction (TDE)
Input●

TOPIX100 tables (TABLE in HTML)

Output●Classification of table cells (Metadata, Header, Attribute, Data)○○For Header, add ontologyID
For Data, normalize the value.

Evaluation●Evaluation by Accuracy

Table Data Extraction (TDE)
Metadata, Header, Attribute and Data

Metadata<table tableClass=”equipment.per_segment” targetCompany=”xxxx”>
Header<tr><td cellClass=”header” ontologyID=”segment_name”>セグメントの名称</td><td cellClass=”header” ontologyID=”amount”>金額（百万円）</td><td cellClass=”header” ontologyID=””>前連結会計年度比（％）</td></tr>
Attribute<tr>
Data<td cellClass=”attribue”>資源</td><td cellClass=”data” valueClass=”currency.JPY” normalizedValue=”92012000000”>92,012</td><td cellClass=”data” valueClass=”amount.relative” normalizedValue=”689.9%”>689.9</td></tr></table>Text-to-Table Relationship Extraction (TTRE)
Input●

Text and Tables in the annual securities reports

Output●Text range corresponding to the table○○

Labels for amounts, increases/decreases, references, and reasons
Assign IDs for the corresponding tables

Evaluation●

Evaluation by Accuracy

Text-to-Table Relationship Extraction (TTRE)
Text
Ordinary profit for the current consolidated fiscal year was 300.5 billion yen,
an increase of 66.9 billion yen from 233.5 billion yen for the previous consolidated fiscal year,
due to the increase in operating profit.
ReasonTable

Calculation of difference

66.9 billion yenIncrese

Schedule●●

September 28, 2022
October 8, 2022
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NTCIR-17 Kickoff Event
JSAI SIG-FIN (Special Interest Group on Financial Informatics) in Tokyo

Title “UFO: Proposal for an Information Extraction Task for Tables in Annual Securities Reports”

November 8, 2022
First table meeting
January 2023:
Dataset Release*
March 2023:
Second round table meetingJanuary-June 2023: Dry Run*
June 2023:
Release of Formal Run dataset
June-July 2023:
Formal Run*
August 1, 2023:
Evaluation Result Release
August 1, 2023:
Draft Task Overview Paper Release
September 1, 2023:
Draft Participant Paper Submission Due
November 1, 2023:
All Camera-ready Paper Submission Due
December 2023:
NTCIR-17 Conference in NII, Tokyo, Japan(* indicates that the schedule can be different for different tasks)