Xianjun-Yang / PcMSP

PcMSP: EMNLP 2022 Findings https://arxiv.org/abs/2210.12401

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PcMSP

The source codes and dataset for our EMNLP 2022 findings paper: PcMSP: A Dataset for Scientific Action Graphs Extraction from Polycrystalline Materials Synthesis Procedure Text.

https://arxiv.org/abs/2210.12401

data

Original folder contains annotated raw data; json files are processed data

Due to license limit, the data is slightly different from results reported in our paper: 242 rather than 243 training files, 30 rather than 31 files for test.

MATKB: SEMANTIC SEARCH FOR POLYCRYSTALLINE MATERIALS SYNTHESIS PROCEDURES

Link will be made to the public soon.

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PcMSP: EMNLP 2022 Findings https://arxiv.org/abs/2210.12401

License:MIT License


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Language:Jupyter Notebook 68.3%Language:Python 31.7%