WeLT-TablERT-CNN: Table-filling JNERE Using WeLT

Authors: Ghadeer Mobasher*, Olga Krebs, Wolfgang Müller, and Michael Gertz

Installation

Please make sure to install all the required dependencies.

Data Preparation

Follow TablERT-CNN's instructions to properly download data -Fetch Data : (CoNLL04)

python3 preprocessing/spert2tabcnn.py $SPERT_DATA_DIR data/datasets/conll04/ 

Examples

(1) Train CoNLL04 on train dataset:

python run.py train --config configs/train_conll04.conf

(2) Evaluation of CoNLL04:

python run.py eval --config config/eval_conll04.conf

Citation

The manuscript is in preparation (TBD)

References

• Markus Eberts and Adrian Ulges, 2020, 'Span-based joint entity and relation extraction with transformer pre-training' In 24th European Conference on Artificial Intelligence (ECAI).
• Youmi Ma, Tatsuya Hiraoka, and Naoaki Okazaki. Named Entity Recognition and Relation Extraction Using Enhanced Table Filling by Contextualized Representations. 自然言語処理, 29(1):187–223, March 2022. (doi: 10.5715/jnlp.29.187).
• Youmi Ma, Tatsuya Hiraoka, and Naoaki Okazaki. Joint Entity and Relation Extraction Based on Table Labeling Using Convolutional Neural Networks.6th Workshop on Structured Prediction for NLP (SPNLP), May 2022.

Acknowledgment

Ghadeer Mobasher* is part of the PoLiMeR-ITN and is supported by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement PoLiMeR, No 812616.