Source code to repeat the paper evaluation: We present the first unsupervised approach to the problem of learning a semantic parser, using Markov logic. Our USP system transforms dependency trees into quasi-logical forms, recursively induces lambda forms from these, and clusters them to abstract away syntactic variations of the same meaning. The MAP semantic parse of a sentence is obtained by recursively assigning its parts to lambda-form clusters and composing them. We evaluate our approach by using it to extract a knowledge base from biomedical abstracts and answer questions. USP substantially outperforms TextRunner, DIRT and an informed baseline on both precision and recall on this task.
In October, I read a fascinating article on GQ.com about head injuries among former NFL players. Written by Jeanne Marie Laskas, the article was a forensic
TIGER API is a library which allows Java programmers to easily access the structure of any corpus given as a TIGER-XML file. It can process the TIGER corpus and any other corpus encoded in TIGER-XML. The underlying API specifies a Java object model for corpora encoded in TIGER-XML and provides methods for traversing syntax trees and accessing elements such as sentences, syntax graph nodes, and their attributes.
OpenNLP is an organizational center for open source projects related to natural language processing. It hosts a variety of java-based NLP tools which perform sentence detection, tokenization, pos-tagging, chunking and parsing, named-entity detection, and coreference using the OpenNLP Maxent machine learning package.