sohomghosh/cepn

Code for causality extraction.

This repository presents team LIPI coltion for FinCausal 2022. It has been forked from this repository and artifacts from this repository have been used.

Publication

If you use the source code or models from this work, please cite the papers:

@inproceedings{kao-etal-2020-ntunlpl,
    title = "{NTUNLPL} at {F}in{C}ausal 2020, Task 2:Improving Causality Detection Using {V}iterbi Decoder",
    author = "Kao, Pei-Wei  and
      Chen, Chung-Chi  and
      Huang, Hen-Hsen  and
      Chen, Hsin-Hsi",
    booktitle = "Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "COLING",
    url = "https://aclanthology.org/2020.fnp-1.11",
    pages = "69--73",
}

@inproceedings{nayak2022cepn,
	author    = {Tapas Nayak, Soumya Sharma, Yash Butala, Koustuv Dasgupta, Pawan Goyal, and Niloy Ganguly},
	title     = {A Generative Approach for Financial Causality Extraction},
	booktitle = {Proceedings of The 2nd Workshop on Financial Technology on the Web (FinWeb)},
	year      = {2022}

}


@inProceedings{ghosh-naskar:2022:FNP,
  author    = {Ghosh, Sohom  and  Naskar, Sudip},
  title     = {LIPI at FinCausal 2022: Mining Causes and Effects from Financial Texts},
  booktitle      = {Proceedings of the The 4th Financial Narrative Processing Workshop @LREC2022},
  month          = {June},
  year           = {2022},
  address        = {Marseille, France},
  publisher      = {European Language Resources Association},
  pages     = {130--132},
  abstract  = {While reading financial documents, investors need to know the causes and their effects. This empowers them to make data-driven decisions. Thus, there is a need to develop an automated system for extracting causes and their effects from financial texts using Natural Language Processing. In this paper, we present the approach our team LIPI followed while participating in the FinCausal 2022 shared task. This approach is based on the winning solution of the first edition of FinCausal held in the year 2020.},
  url       = {https://aclanthology.org/2022.fnp-1.21}
}