---
title: "Open Information Extraction: The Second Generation"
authors:
  - "Oren Etzioni"
  - "Anthony Fader"
  - "Janara Christensen"
  - "Stephen Soderland"
  - "Mausam"
doi: "10.5591/978-1-57735-516-8/IJCAI11-012"
url: "https://ijcai.org/proceedings/2011/12"
pdf: "https://ijcai.org/proceedings/2011/0012.pdf"
venue: "Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence"
year: 2011
pages: "3-9"
track: ""
keywords:
---

# Open Information Extraction: The Second Generation

Oren Etzioni, Anthony Fader, Janara Christensen, Stephen Soderland, Mausam

*Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence*, pages 3-9. DOI: [10.5591/978-1-57735-516-8/IJCAI11-012](https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-012)

## Abstract

How do we scale information extraction to the massive size and unprecedented heterogeneity of the Web corpus? Beginning in 2003, our KnowItAll project has sought to extract high-quality knowledge from the Web. In 2007, we introduced the Open Information Extraction (Open IE) paradigm which eschews handlabeled training examples, and avoids domain-specific verbs and nouns, to develop unlexicalized, domain-independent extractors that scale to the Web corpus. Open IE systems have extracted billions of assertions as the basis for both common-sense knowledge and novel question-answering systems. This paper describes the second generation of Open IE systems, which rely on a novel model of how relations and their arguments are expressed in English sentences to double precision/recall compared with previous systems such as TEXTRUNNER and WOE.