The string2string library is an open-source tool that offers a comprehensive suite of efficient algorithms for a broad range of string-to-string problems. It includes both traditional algorithmic solutions and recent advanced neural approaches to address various problems in pairwise string alignment, distance measurement, lexical and semantic search, and similarity analysis. Additionally, the library provides several helpful visualization tools and metrics to facilitate the interpretation and analysis of these methods.
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