FinCausal-2022 Shared Task: “Financial Document Causality Detection”
To be held at The 4th Financial Narrative Processing Workshop (FNP 2022), Marseille, France 24 June 2022.
New: Participation form is now out, click here to register your team.
New: Winners of the shared task will receive a free registration to attend the FNP 2022 workshop at LREC 2022 generously provided by the European Language Resources Association (ELRA) http://www.elra.info/en/.
Training set release: 15 March 2022 Blind test set release: 25 March 2022 Systems submission: 15 April 2022 Release of results: 20 April 2022 Paper submission deadline: 20 April 2022
- Papers notification of acceptance: 3 May 2022
The winning team of the FinCausal 2022 Shared task is 🏅Team SPOCK🏅 from Rensselaer Polytechnic Institute and IBM, USA. Congratulations 😀🥳👍👏!
SPOCK team members:
Anik Saha, Jian Ni, Oktie Hassanzadeh, Alex Gittens, Kavitha Srinivas and Bulent Yener
Winners of the shared task will receive a free registration to attend the FNP 2022 workshop at LREC 2022 generously provided by the European Language Resources Association (ELRA)
The free registrations are provided by the European Language Resources Association (ELRA) http://www.elra.info/en/.
The free registration can be only used by one of the team members, we’ll get it touch with the winning team and ask for the name of the person attending and presenting the paper.
FinCausal 2022 is supported by the European Language Resources Association (ELRA) http://www.elra.info/en/. ELRA will provide a free workshop registration to attend LREC 2022 to the winning team of FinCausal 2022. See details in the Awards section above.
Financial analysis needs factual data, but also explanation on the variability of these data. Data state facts, but provide little to no knowledge regarding how these facts materialised. The Financial Document Causality Detection Task aims to develop an ability to explain, from external sources, the reasons why a transformation occurs in the financial landscape, as a preamble to generating accurate and meaningful financial narrative summaries. Its goal is to evaluate which events or which chain of events can cause a financial object to be modified or an event to occur, regarding a given external context. This context is available in the financial news, but due to the high volatility of such information, mapping an external cause to a given consequence is not trivial.
The task dataset has been extracted from different 2019 financial news kindly provided by Qwam, and additional SEC data from the Edgar Database, and has been normalised for the research task.
Participants will be asked to detect, in causal sentences, which elements of the sentence relate to the cause and which relate to the effect.
This paper details the data processing and the labelling scheme used to create the training data for this task.
As part of the Financial Narrative workshop, we propose the FinCausal Task, focusing on detecting if an object, an event or a chain of events is considered a cause for a prior event. This shared task focuses on determining causality associated with a quantified fact. An event is defined as the arising or emergence of a new object or context in regard to a previous situation. So the task will emphasise the detection of causality associated with transformation of financial objects embedded in quantified facts.
Participants will be provided with a sample of text blocks extracted from financial news, labelled through inter annotator agreement.
Cause and Effect Detection
This task is a relation detection task. The aim is to identify, in a causal sentence or text block, the causal elements and the consequential ones.
|Boussard Gavaudan Investment Management LLP bought a new position in shares of GENFIT S A/ADR in the second quarter worth about $199,000. Morgan Stanley increased its stake in shares of GENFIT S A/ADR by 24.4% in the second quarter.Morgan Stanley now owns 10,700 shares of the company’s stock worth $211,000 after purchasing an additional 2,100 shares during the period||Morgan Stanley increased its stake in shares of GENFIT S A/ADR by 24.4% in the second quarter||Morgan Stanley now owns 10,700 shares of the company’s stock worth $211,000 after purchasing an additional 2,100 shares during the period.|
|Zhao found himself 60 million yuan indebted after losing 9,000 BTC in a single day (February 10, 2014)||losing 9,000 BTC in a single day (February 10, 2014)||Zhao found himself 60 million yuan indebted|
Table 1: Cause and Effect Detection Sample
Participants are free to use any method they see fit (regex, corpus linguistics, entity relationship models, deep learning methods) to identify the causes and effects.
FinCausal Shared Task Organisers
- Dominique Mariko – Yseop Lab
- Hanna Abi Akl – Yseop Lab
- Hugues de Mazancourt – Yseop Lab
- Anubhav Gupta – Yseop Lab
Shared Task Contact
The participants to this task will access the data after registering, and thereby pledge to contribute to the workshop by submitting an experiment paper.
Participant can register for this shared task by filling this form, and get access to the datasets.
For any question please contact the organisers at firstname.lastname@example.org