Abstract. This collaborative report highlights the properties and prospects of Controlled Natural Languages (CNLs). The report poses a range of questions concerning the goals of the CNL, the design, the linguistic aspects, the relationships and evaluation of CNLs, and the application tools. In posing the questions, the report attempts to structure the field of CNLs and to encourage further systematic discussion by researchers and developers.

We present an algorithm for incremental statistical parsing with Parallel Multiple Context-Free Grammars (PMCFG). This is an extension of the algorithm by Angelov (2009) to which we added statistical ranking. We show that the new algorithm is several times faster than other statistical PMCFG parsing algorithms on real-sized grammars. At the same time the algorithm is more general since it supports non-binarized and non-linear grammars.We also show that if we make the search heuristics non-admissible, the parsing speed improves even further, at the risk of returning sub-optimal solutions.

No abstract

Abstract. The paper introduces GF, Grammatical Framework, as a tool for implementing controlled languages. GF provides a high-level grammar formalism and a resource grammar library that make it easy to write grammars that cover similar fragments in several natural languages at the same time. Authoring help tools and automatic translation are provided for all grammars. As an example, a grammar of Attempto Controlled English is implemented and then ported to French, German, and Swedish.

Parallel Multiple Context-Free Grammar (PMCFG) is an extension of context-free grammar for which the recognition problem is still solvable in polynomial time. We describe a new parsing algorithm that has the advantage to be incremental and to support PMCFG directly rather than the weaker MCFG formalism. The algorithm is also top-down which allows it to be used for grammar based word prediction.

This paper presents an architecture and a prototype for speech-to-speech translation on Android devices, based on GF (Grammatical Framework). From the user's point of view, the advantage is that the system works off-line and yet has a lean size; it also gives, as a bonus, grammatical information useful for language learners. From the developer's point of view, the advantage is the open architecture that permits the customization of the system to new languages and for special purposes. Thus the architecture can be used for controlled-language-like translators that deliver very high quality, which is the traditional strength of GF. However, this paper focuses on a general-purpose system that allows arbitrary input. It covers eight languages.

No abstract

We present a web service for natural language parsing, prediction, generation, and translation using grammars in Portable Grammar Format (PGF), the target format of the Grammatical Framework (GF) grammar compiler. The web service implementation is open source, works with any PGF grammar, and with any web server that supports FastCGI. The service exposes a simple interface which makes it possible to use it for interactive natural language web applications. We describe the functionality and interface of the web service, and demonstrate several applications built on top of it.