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EvidenceMap

Corpora:

A gold standard dataset of randomized controlled trial (RCT) abstracts annotated with the EvidenceMap representation including two corpora are provided.
The “General” corpus includes a broad range of disease domains by randomly selecting 229 RCT article abstracts. The “COVID-19” corpus includes 80 randomly selected COVID-19 RCT article abstracts to accommodate the increased demand for related evidence retrieval and synthesis resources during the pandemic.

The descriptive statistics of these two annotated corpora are listed in Table.

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Dependent evidence relationships were used for constructing MEPs, and independent relationships can serve as negative samples for training machine learning based NLP models.

All annotations were conducted using the web-based interactive annotation tool Brat (https://brat.nlplab.org/). An example abstract with annotations is presented:

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Pretrained Models:

Download pretrained models here.

Running Environment:

  1. Install tensorflow==2.3
  2. Install bert-for-tf2
  3. Install https://s3-us-west-2.amazonaws.com/ai2-s2-scispacy/releases/v0.4.0/en_core_sci_lg-0.4.0.tar.gz

Running the Code:

  1. Unzip model.zip
  2. Move all files under model/
  3. Modify parser configuration parser_config.py
  4. Run examples in wrapper.sh

Yingcheng Sun, Tian Kang, Chunhua Weng ([email protected])