influencemapper 0.9.0

A tool for extracting information from disclosure statements.

InfluenceMapper

InfluenceMapper is a python library for extracting disclosure information from scholarly articles. It uses fine-tuned OpenAI's GPT models for the extraction of entities and relationships from the text. The functions included in the library are:

• Extract entities from the text.
• Extract relationships between authors and entities.
• Extract relationships between entities and the study.

Installation

To install the library, run the following command:

pip install influencemapper

Training the model

The model is trained on a dataset of scholarly articles. The dataset is available at the data folder. To train the model, clone the directory and run the following command:

python core/src/influencemapper/cli.py fine_tune -train_data data/train.jsonl -valid_data data/valid.jsonl -model_name gpt-4o-mini -threshold 1500 study_org 
python core/src/influencemapper/cli.py fine_tune -train_data data/train.jsonl -valid_data data/valid.jsonl -model_name gpt-4o-mini -threshold 1500 author_org

As of the writing of this README, the resulting file has to be uploaded manually to the OpenAI platform to fine-tune the model. The model will be available for use after the fine-tuning process is completed.The threshold parameter is used to restrict samples, allowing only those with a maximum token count that meets the training requirements to pass.

Inferring entities and relationships

To infer entities and relationships from a disclosure text, run the following command:

python core/src/influencemapper/cli.py infer -data data/test.jsonl -model_name gpt-4o-mini -API_KEY [API_KEY] study_org
python core/src/influencemapper/cli.py infer -data data/test.jsonl -model_name gpt-4o-mini -API_KEY [API_KEY] author_org

To get the results, you have to visit the OpenAI platform and download the results.