GitHub - ml4ai/delphi: Framework for assembling causal probabilistic models from text and software. (original) (raw)

Complete documentation available atml4ai.github.io/delphi (the 'raw' version can be found in the docs directory.)

Modeling complex phenomena such as food insecurity requires reasoning over multiple levels of abstraction and fully utilizing expert knowledge about multiple disparate domains, ranging from the environmental to the sociopolitical.

Delphi is a Python/C++ library for assembling causal, dynamic, probabilistic models from information extracted from two sources:

• Text: Delphi utilizes causal relations extracted using machine reading from text sources such as UN agency reports, news articles, and technical papers.
• Software: Delphi also incorporates functionality to extract abstracted representations of scientific models from code that implements them, and convert these into probabilistic models.

Delphi builds upon INDRA and Eidos.

For a detailed description of our procedure to convert text to models, see this document.

Delphi is also part of theAutoMATES project.

Citing

If you use Delphi, please cite the following:

@InProceedings{sharp-EtAl:2019:N19-4, author = {Sharp, Rebecca and Pyarelal, Adarsh and Gyori, Benjamin and Alcock, Keith and Laparra, Egoitz and Valenzuela-Esc'{a}rcega, Marco A. and Nagesh, Ajay and Yadav, Vikas and Bachman, John and Tang, Zheng and Lent, Heather and Luo, Fan and Paul, Mithun and Bethard, Steven and Barnard, Kobus and Morrison, Clayton and Surdeanu, Mihai}, title = {Eidos, INDRA, & Delphi: From Free Text to Executable Causal Models}, booktitle = {Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations)}, month = {6}, year = {2019}, address = {Minneapolis, Minnesota}, publisher = {Association for Computational Linguistics}, pages = {42-47}, url = {http://www.aclweb.org/anthology/N19-4008}, keywords = {demo paper, causal relations, timelines, locations, information extraction}, } @misc{Delphi, Author = {Adarsh Pyarelal and Paul Hein and Jon Stephens and Pratik Bhandari and HeuiChan Lim and Saumya Debray and Clayton Morrison}, Title = {Delphi: A Framework for Assembling Causal Probabilistic Models from Text and Software.}, doi={10.5281/zenodo.1436915}, }

License and Funding

Delphi is licensed under the Apache License 2.0.

The development of Delphi was supported by the Defense Advanced Research Projects Agency (DARPA) under the World Modelers (grant no. W911NF1810014) and Automated Scientific Knowledge Extraction (agreement no. HR00111990011) programs.