Effective Crowdsourcing of Multiple Tasks for Comprehensive Information Extraction The source code in this repository is related to each crowdsourcing tasks;

1. Data preparation
2. Data post-processing
3. Quality evaluator
4. Other utility codes

All other dataset and source code are listed below:

• Crowdsourcing data and all other resources, such as pretrained embedding
• OKBQA KBP Task, Description and sample

• Entity Linking
• Co-reference resolution
• Relation Extraction: PCNN and GAN
• Relation Extraction: RL
• Relation Extraction: BERT

• KBox
• Korean KBP Demo

• CC BY-NC-SA Attribution-NonCommercial-ShareAlike
• If you want to commercialize this resource, please contact to us

Machine Reading Lab @ KAIST

• Nam, Sangha, et al. "Effective Crowdsourcing of Multiple Tasks for Comprehensive Knowledge Extraction." Proceedings of The 12th Language Resources and Evaluation Conference. 2020.

• This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (2013-0-00109, WiseKB: Big data based self-evolving knowledge base and reasoning platform)
• 2019년도 KI과학기술선도기초연구사업 (KI Science Technology Leading Primary Research)