EventExtractionPapers

Why we included this project

Putting together a reading list on event extraction from scratch takes weeks, and this curated bibliography does that work for you. It sorts the research by approach, from pattern matching and classical machine learning through deep learning and semi- or unsupervised methods, and it also gathers work on event coreference, surveys, linguistics, and the datasets and tools people actually use. Within each section the papers are ordered by year, so you can watch the field move from dictionary-based systems like AutoSlog in the early 1990s to modern neural models. That historical shape helps newcomers find a structured entry point and lets practitioners jump straight to a specific technique or benchmark. It is a reference index rather than runnable software, but as a map of the literature it is a solid place to start when scoping an event extraction project.