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\title{A GF/MMT, a Framework for Computational Semantics} 
\author{Michael Kohlhase, Dennis M\"uller, Frederik Sch\"afer\\Computer Science,  FAU
  Erlangen-N\"urnberg\\\url{http://kwarc.info}}

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\begin{abstract}
  In this note we present how a combination of GF and MMT can be used as a development
  framework for natural language semantics.
\end{abstract}
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\section{Introduction}\label{sec:intro}

Natural language semantics studies systems that represent and compute the meaning of
natural language utterances. It focuses on models that can predict the truth conditions of
an utterance $u$, i.e. for all possible contexts $C$ of $u$, it can predict whether $C(u)$
is valid. Following the ``\defemph{method of fragments}'' introduced in Montague's seminal
paper ``\emph{The proper Treatment of Quantifiers in ordinary Emnglish}''
(PTQ~\cite{Montague:tptoqi73}) such models usually involve
\begin{compactenum}
\item a \defemph{grammar formalism} $G$ that determines a natural language fragment and
  can parse this into syntax trees,
\item a \defemph{formal (logical) system} $L$ consisting of a formal language, a model
  theory, and a calculus that specifies derivability,
\item a \defemph{semantics construction} process that transforms syntax frees of $G$ into
  terms in $L$,  and
\item possibly a \defemph{semantic/pragmatic analysis} process that further specifies the
  $L$ with respect to the utterance context. 
\end{compactenum}

In the three decades following PTQ a plethora of semantics models have been proposed.  In
the past, this has been a largely pen-and-paper endeavor.  Even though parts of the models
have been implemented, there is no general-purpose framework\footnote{We do not count
  high-level programming languages as frameworks here; for these we have extensive,
  integrated develoments of models in Prolog~\cite{BlaBos:rainl05} and
  Haskell~\cite{EijUng:csfp10} } that allows the effective experimentation with language
models.



\ednote{cite~\cite{BerChattsfts17}}

\section{Conclusion}\label{sec:concl}

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