This repository contains the code used in the following paper:
Ipek Baris, Lukas Schmelzeisen, and Steffen Staab (2019). “CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against Rumors”. In: SemEval@NAACL-HLT. Association for Computational Linguistics, pp. 1105–1109. [ACL Anthology] [arXiv] [Poster]
If you use this in your work, please cite as:
@inproceedings{DBLP:conf/semeval/BarisSS19,
author = {Ipek Baris and
Lukas Schmelzeisen and
Steffen Staab},
title = {{CLEAR}umor at {S}em{E}val-2019 Task 7: {C}onvo{L}ving {ELM}o
{A}gainst {R}umors},
booktitle = {SemEval@NAACL-HLT},
pages = {1105--1109},
publisher = {Association for Computational Linguistics},
year = {2019},
url = {https://www.aclweb.org/anthology/S19-2193},
}
Python 3.6+ is required.
- See the PyTorch Getting Started page for how to install it.
- Install AllenNLP:
pip3 install allennlp
- Install the tokenizer for Twitter and Reddit posts:
pip3 install git+https://github.com/erikavaris/tokenizer.git
- Place the ELMo weights and options files
elmo_2x4096_512_2048cnn_2xhighway_5.5B_weights.hdf5
andelmo_2x4096_512_2048cnn_2xhighway_5.5B_options.json
in thedata/external
subdirectory. They can be obtained from the ELMo website. - Place the training, test data, and evaluation files
rumoureval-2019-training-data.zip
,rumoureval-2019-test-data.zip
, andhome_scorer_macro.py
in thedata/external/
subdirectory. They can be obtained from the RumorEval 2019 competetion page. - If you also want to evaluate on the final evaluation data from RumorEval,
place the
final-eval-key.json
file in thedata/external
subdirectory. So far, this file has only been shared privately with all participants in the competition. It is under an embargo for a couple of months, but will be released publicly later.
If you have any questions regarding the code or the employed machine learning architectures, please, don't hesitate to contact the authors or report an issue.
- Lukas Schmelzeisen, [email protected], @lschmelzeisen
- Ipek Baris, [email protected], @ipekbrs
- Institute for Web Science and Technoloogies, University of Koblenz-Landau
All code is license under the Apache License Version 2.0.