Hillel Taub-Tabib

We present a light-weight query language that does not require the user to know the details of the underlying syntactic representations, and instead to query the corpus by providing an example sentence coupled with simple markup. Expand

We present a system that allows life-science researchers to search a linguistically annotated corpus of scientific texts using patterns over dependency graphs, as well as using a powerful variant of boolean keyword queries. Expand

In this paper we present a kernel based approach to automated feature generation in the context of graph-based parsing. Expand

The advent of neural-networks in NLP brought with it substantial improvements in supervised relation extraction. Expand