Extracting higher-order logic formulas from English sentences

We proposed a framework and its implementation as a Python library for converting English utterances into higher-order logic (HOL) formulas. HOL extends first-order logic and provides flexibility for representing natural language semantics. Our library uses a broad-coverage and robust HPSG grammar for English to produce minimal recursive semantics (MRS) structures. These open-source technologies from the DELPH-IN Consortium balance a rigorous linguistic grounding and compositionality with practical aspects for natural language processing applications. Finally, we evaluated our approach over SICK, a popular dataset for text entailment.