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Towards a Multilingual Financial Narrative Processing System

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Towards a Multilingual Financial Narrative Processing System. / El Haj, Mahmoud; Rayson, Paul Edward; Alves, Paulo; Young, Steven Eric.

The First Financial Narrative Processing Workshop: Proceedings of the 11th Edition of the Language Resources and Evaluation Conference - Miyazaki, Japan. ed. / Mahmoud El-Haj; Paul Rayson; Andrew Moore. 2018. p. 52-58.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

El Haj, M, Rayson, PE, Alves, P & Young, SE 2018, Towards a Multilingual Financial Narrative Processing System. in M El-Haj, P Rayson & A Moore (eds), The First Financial Narrative Processing Workshop: Proceedings of the 11th Edition of the Language Resources and Evaluation Conference - Miyazaki, Japan. pp. 52-58, The 1st Financial Narrative Processing Workshop in LREC 2018, Miyazaki, Japan, 7/05/18. <http://lrec-conf.org/workshops/lrec2018/W27/pdf/book_of_proceedings.pdf>

APA

El Haj, M., Rayson, P. E., Alves, P., & Young, S. E. (2018). Towards a Multilingual Financial Narrative Processing System. In M. El-Haj, P. Rayson, & A. Moore (Eds.), The First Financial Narrative Processing Workshop: Proceedings of the 11th Edition of the Language Resources and Evaluation Conference - Miyazaki, Japan (pp. 52-58) http://lrec-conf.org/workshops/lrec2018/W27/pdf/book_of_proceedings.pdf

Vancouver

El Haj M, Rayson PE, Alves P, Young SE. Towards a Multilingual Financial Narrative Processing System. In El-Haj M, Rayson P, Moore A, editors, The First Financial Narrative Processing Workshop: Proceedings of the 11th Edition of the Language Resources and Evaluation Conference - Miyazaki, Japan. 2018. p. 52-58

Author

El Haj, Mahmoud ; Rayson, Paul Edward ; Alves, Paulo ; Young, Steven Eric. / Towards a Multilingual Financial Narrative Processing System. The First Financial Narrative Processing Workshop: Proceedings of the 11th Edition of the Language Resources and Evaluation Conference - Miyazaki, Japan. editor / Mahmoud El-Haj ; Paul Rayson ; Andrew Moore. 2018. pp. 52-58

Bibtex

@inproceedings{7554d446875346a6b5c53419d87e5b8d,
title = "Towards a Multilingual Financial Narrative Processing System",
abstract = "Large scale financial narrative processing for UK annual reports has only become possible in the last few years with our prior work on automatically understanding and extracting the structure of unstructured PDF glossy reports. This has levelled the playing field somewhat relative to US research where annual reports (10-K Forms) have a rigid structure imposed on them by legislation and are submitted in plain text format. The structure extraction is just the first step in a pipeline of analyses to examine disclosure quality and change over time relative to financial results. In this paper, we describe and evaluate the use of similar Information Extraction and Natural Language Processing methods for extraction and analysis of annual financial reports in a second language (Portuguese) in order to evaluate the applicability of our techniques in another national context (Portugal). Extraction accuracy varies between languages with English exceeding 95%. To further examine the robustness of our techniques, we apply the extraction methods on a comprehensivesample of annual reports published by UK and Portuguese non-financial firms between 2003 and 2015.",
keywords = "Financial Narrative Processing, NLP, annual reports, Information Extraction, Multilingual",
author = "{El Haj}, Mahmoud and Rayson, {Paul Edward} and Paulo Alves and Young, {Steven Eric}",
year = "2018",
month = may,
day = "7",
language = "English",
isbn = "9791095546238",
pages = "52--58",
editor = "Mahmoud El-Haj and Paul Rayson and Moore, {Andrew }",
booktitle = "The First Financial Narrative Processing Workshop",
note = "The 1st Financial Narrative Processing Workshop in LREC 2018, FNP 2018 ; Conference date: 07-05-2018",
url = "http://wp.lancs.ac.uk/cfie/",

}

RIS

TY - GEN

T1 - Towards a Multilingual Financial Narrative Processing System

AU - El Haj, Mahmoud

AU - Rayson, Paul Edward

AU - Alves, Paulo

AU - Young, Steven Eric

PY - 2018/5/7

Y1 - 2018/5/7

N2 - Large scale financial narrative processing for UK annual reports has only become possible in the last few years with our prior work on automatically understanding and extracting the structure of unstructured PDF glossy reports. This has levelled the playing field somewhat relative to US research where annual reports (10-K Forms) have a rigid structure imposed on them by legislation and are submitted in plain text format. The structure extraction is just the first step in a pipeline of analyses to examine disclosure quality and change over time relative to financial results. In this paper, we describe and evaluate the use of similar Information Extraction and Natural Language Processing methods for extraction and analysis of annual financial reports in a second language (Portuguese) in order to evaluate the applicability of our techniques in another national context (Portugal). Extraction accuracy varies between languages with English exceeding 95%. To further examine the robustness of our techniques, we apply the extraction methods on a comprehensivesample of annual reports published by UK and Portuguese non-financial firms between 2003 and 2015.

AB - Large scale financial narrative processing for UK annual reports has only become possible in the last few years with our prior work on automatically understanding and extracting the structure of unstructured PDF glossy reports. This has levelled the playing field somewhat relative to US research where annual reports (10-K Forms) have a rigid structure imposed on them by legislation and are submitted in plain text format. The structure extraction is just the first step in a pipeline of analyses to examine disclosure quality and change over time relative to financial results. In this paper, we describe and evaluate the use of similar Information Extraction and Natural Language Processing methods for extraction and analysis of annual financial reports in a second language (Portuguese) in order to evaluate the applicability of our techniques in another national context (Portugal). Extraction accuracy varies between languages with English exceeding 95%. To further examine the robustness of our techniques, we apply the extraction methods on a comprehensivesample of annual reports published by UK and Portuguese non-financial firms between 2003 and 2015.

KW - Financial Narrative Processing

KW - NLP

KW - annual reports

KW - Information Extraction

KW - Multilingual

M3 - Conference contribution/Paper

SN - 9791095546238

SP - 52

EP - 58

BT - The First Financial Narrative Processing Workshop

A2 - El-Haj, Mahmoud

A2 - Rayson, Paul

A2 - Moore, Andrew

T2 - The 1st Financial Narrative Processing Workshop in LREC 2018

Y2 - 7 May 2018

ER -