Understanding the experimental results of a scientific paper is crucial to understanding its contribution and to comparing it with related work. We introduce a structured, queryable representation for experimental results and a baseline system that automatically populates this representation. The representation can answer compositional questions such as: “Which are the best published results reported on the NIST 09 Chinese to English dataset?” and “What are the most important methods for speeding up phrase-based decoding?” Answering such questions usually involves lengthy literature surveys. Current machine reading for academic papers does not usually consider the actual experiments, but mostly focuses on understanding abstracts. We describe annotation work to create an initial hscientific paper; experimental results representationi corpus. The corpus is composed of 67 papers which were manually annotated with a structured representation of experimental results by domain experts. Additionally, we present a baseline algorithm that characterizes the difficulty of the inference task.

We describe resources aimed at increasing the usability of the semantic representations utilized within the DELPH-IN (Deep Linguistic Processing with HPSG) consortium. We concentrate in particular on the Dependency Minimal Recursion Semantics (DMRS) formalism, a graph-based representation designed for compositional semantic representation with deep grammars. Our main focus is on English, and specifically English Resource Semantics (ERS) as used in the English Resource Grammar. We first give an introduction to ERS and DMRS and a brief overview of some existing resources and then describe in detail a new repository which has been developed to simplify the use of ERS/DMRS. We explain a number of operations on DMRS graphs which our repository supports, with sketches of the algorithms, and illustrate how these operations can be exploited in application building. We believe that this work will aid researchers to exploit the rich and effective but complex DELPH-IN resources.