We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the associated FinCausal dataset, and discuss the participating systems and results. Two sub-tasks are proposed: a binary classification task (Task 1) and a relation extraction task (Task 2). A total of 16 teams submitted runs across the two Tasks and 13 of them contributed with a system description paper. This workshop is associated to the Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation (FNP-FNS 2020), held at The 28th International Conference on Computational Linguistics (COLING'2020), Barcelona, Spain on September 12, 2020
This thesis mainly studies the causality in natural language processing. Understanding causality is ...
The thesis investigates the question of causal relationships identification and characterization in ...
International audienceThis is a preliminary paper describing the concepts and principles for a seque...
We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the asso...
Welcome to the 1st Joint Workshop on financial Narrative Processing and MultiLing financial Summaris...
Welcome to the 4th Financial Narrative Processing Workshop (FNP 2022). This year the workshop is hel...
The Event Causality Identification Shared Task of CASE 2022 involved two subtasks working on the Cau...
abstract: Natural Language Processing (NLP) techniques have increasingly been used in finance, accou...
This paper presents the FinTOC-2020 Shared Task on structure extraction from financial documents, it...
We aim to develop a text mining framework capable ofidentifying and extractingcausal depend...
Abstract: This article investigates causality structure of financial time series. We concentrate on ...
This paper presents the results and findings of the Financial Narrative Summarisation Shared Task on...
Causality detection is the task of extracting information about causal relations from text. It is an...
[Context & motivation:] System behavior is often expressed by causal relations in requiremen...
Causal relations in natural language (NL) requirements convey strong, semantic information. Automati...
This thesis mainly studies the causality in natural language processing. Understanding causality is ...
The thesis investigates the question of causal relationships identification and characterization in ...
International audienceThis is a preliminary paper describing the concepts and principles for a seque...
We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the asso...
Welcome to the 1st Joint Workshop on financial Narrative Processing and MultiLing financial Summaris...
Welcome to the 4th Financial Narrative Processing Workshop (FNP 2022). This year the workshop is hel...
The Event Causality Identification Shared Task of CASE 2022 involved two subtasks working on the Cau...
abstract: Natural Language Processing (NLP) techniques have increasingly been used in finance, accou...
This paper presents the FinTOC-2020 Shared Task on structure extraction from financial documents, it...
We aim to develop a text mining framework capable ofidentifying and extractingcausal depend...
Abstract: This article investigates causality structure of financial time series. We concentrate on ...
This paper presents the results and findings of the Financial Narrative Summarisation Shared Task on...
Causality detection is the task of extracting information about causal relations from text. It is an...
[Context & motivation:] System behavior is often expressed by causal relations in requiremen...
Causal relations in natural language (NL) requirements convey strong, semantic information. Automati...
This thesis mainly studies the causality in natural language processing. Understanding causality is ...
The thesis investigates the question of causal relationships identification and characterization in ...
International audienceThis is a preliminary paper describing the concepts and principles for a seque...