25 citations · 39 across the 5 of their papers we have counts for
6 papers
Constructing and Interpreting Causal Knowledge Graphs from News
Fiona Anting Tan, Debdeep Paul, Sahim Yamaura +2
Many financial jobs rely on news to learn about causal events in the past and present, to make informed decisions and predictions about the future. With the ever-increasing amount…
Event Causality Identification with Causal News Corpus -- Shared Task 3, CASE 2022
Fiona Anting Tan, Hansi Hettiarachchi, Ali Hürriyetoğlu +4
The Event Causality Identification Shared Task of CASE 2022 involved two subtasks working on the Causal News Corpus. Subtask 1 required participants to predict if a sentence contai…
UniCausal: Unified Benchmark and Repository for Causal Text Mining
Fiona Anting Tan, Xinyu Zuo, See-Kiong Ng
Current causal text mining datasets vary in objectives, data coverage, and annotation schemes. These inconsistent efforts prevent modeling capabilities and fair comparisons of mode…
The Causal News Corpus: Annotating Causal Relations in Event Sentences from News
Fiona Anting Tan, Ali Hürriyetoğlu, Tommaso Caselli +7
Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
NUS-IDS at FinCausal 2021: Dependency Tree in Graph Neural Network for Better Cause-Effect Span Detection
Fiona Anting Tan, See-Kiong Ng
Automatic identification of cause-effect spans in financial documents is important for causality modelling and understanding reasons that lead to financial events. To exploit the o…