T-Rex (Trainable Relation Extraction) is a highly configurable machine learning-based Information Extraction from Text framework, which includes tools for document classification, entity extraction and relation extraction.
RelEx, a narrow-AI component of OpenCog, is an English-language semantic relationship extractor, built on the Carnegie-Mellon link parser. It can identify subject, object, indirect object and many other dependency relationships between words in a sentence; it generates dependency trees, resembling those of dependency grammars.
The objective of the ACE Program is to develop extraction technology to support automatic processing of source language data (in the form of natural text, and as text derived from ASR and OCR). This includes classification, filtering, and selection based on the language content of the source data, i.e., based on the meaning conveyed by the data. Thus the ACE program requires the development of technologies that automatically detect and characterize this meaning. The ACE research objectives are viewed as the detection and characterization of Entities, Relations, and Events.
Semantic MediaWiki (SMW) is a free extension of MediaWiki that helps to search, organise, tag, browse, evaluate, and share the wiki's content. While traditional wikis contain only texts which computers can neither understand nor evaluate, SMW adds semantic annotations that bring the power of the Semantic Web to the wiki.
M. Mintz, S. Bills, R. Snow, and D. Jurafsky. Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, page 1003--1011. Suntec, Singapore, Association for Computational Linguistics, (August 2009)