Xiaolan Wang, Jiyu Komiya, Yoshihiko Suhara, Aaron Feng, Behzad Golshan, Alon Y. Halevy, Wang-Chiew Tan
KOKO is a declarative information extraction system that incorporates advances in natural language processing techniques in its extraction language. KOKO’s extraction language supports simultaneous specification of conditions over the surface syntax and on the structure of the dependency parse tree of sentences, thereby allowing for more refined extractions. Furthermore, the KOKO extraction language allows for aggregating evidence from an input document and supports conditions that are tolerant of linguistic variation of expressing concepts. In this demo, we outline the design of KOKO, a system for extracting information and understanding the results of the extraction. KOKO provides an interactive interface that allows participants to write queries, understand the input and results of the queries. In particular, the user can customize the input text, visualize the input text’s dependency parse trees, and understand the correspondences between query components, dependency tree nodes, text tokens, and the computation and associated scores that led to an extraction.