# Overview
This demo demonstrates the extraction of the graphs from a specified article, cleaning and optimizing them, enhancing citation information, merging them, and expanding literature nodes through web retrieval. The complete pipeline mentioned above is now operational.
*entity.csv* and *relation.csv* are the files that constitute the graph.
*visualization/knowledge-graph.html* is the visualization file of the graph.
*abs_subgraph_info.txt* and *rw_subgraph_info.txt* contain the information for the subgraphs.
The other files contain the intermediate results.

# Basic information
- Starting Point Article for Graph construction: **MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning**
    - the format of the input file is referenced in *input/raw_content.json*, which includes
        - paper title
        - abstract
        - related work
        - reference
- Parameters of the graph
    - total entity 

# Problem
- unexpected dicrete entity nodes still exist even after the cleaning process
- failed to provide recommendation for starting point article

# Further work
- get stable result by repeated sampling
- complete relation by a search strategy
