This paper presents Coral, an interface in which complex corpus queries can be expressed in a controlled subset of natural English. With the help of a predictive editor, users can compose queries and submit them to the Coral system, which then automatically translates them into formal AQL statements. The paper gives an overview of the controlled natural language developed for Coral and describes the functionalities of the predictive editor provided for it. It also reports on a user experiment in which the system was evaluated. The results show that, with Coral, corpora of annotated texts can be queried easier and faster than with the existing ANNIS interface. Our system demonstrates that complex corpora can be accessed without the need to learn a complicated formal query language. AbstractIn this paper, we present Coral, an interface in which complex corpus queries can be expressed in a controlled subset of natural English. With the help of a predictive editor, users can compose queries and submit them to the Coral system, which then automatically translates them into formal AQL statements. We give an overview of the controlled natural language developed for Coral and describe the functionalities of the predictive editor provided for it. We also report on a user experiment in which the system was evaluated.The results show that, with Coral, corpora of annotated texts can be queried more easily and more quickly than with the existing ANNIS interface. Our system demonstrates that complex corpora can be accessed without the need to learn a complicated, formal query language.

Attempto Controlled English (ACE) is a knowledge representation language with an English syntax. Thus ACE can be used by anyone, even without being familiar with formal notations. The Attempto Parsing Engine translates ACE texts into discourse representation structures, a variant of first-order logic. Hence, ACE turns out to be a logic language equivalent to full first-order logic. The two views of ACE -natural language and logic language -complement each other, and render ACE both human-and machine-readable. This paper covers both views of ACE. In the first part we present the language ACE in a nutshell, and in the second part we give an overview of the discourse representation structures derived from ACE texts.

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Legislative language exhibits some characteristics typical of languages of administration that are particularly prone to eliciting ambiguities. However, ambiguity is generally undesirable in legislative texts and can pose problems for the interpretation and application of codified law. In this paper, we demonstrate how methods of controlled natural languages can be applied to prevent ambiguities in legislative texts. We investigate what types of ambiguities are frequent in legislative language and therefore important to control, and we examine which ambiguities are already controlled by existing drafting guidelines. For those not covered by the guidelines, we propose additional control mechanisms. Wherever possible, the devised mechanisms reflect existing conventions and frequency distributions and exploit domain-specific means to make ambiguities explicit. Abstract. Legislative language exhibits some characteristics typical of languages of administration that are particularly prone to eliciting ambiguities. However, ambiguity is generally undesirable in legislative texts and can pose problems for the interpretation and application of codified law. In this paper, we demonstrate how methods of controlled natural languages can be applied to prevent ambiguities in legislative texts. We investigate what types of ambiguities are frequent in legislative language and therefore important to control, and we examine which ambiguities are already controlled by existing drafting guidelines. For those not covered by the guidelines, we propose additional control mechanisms. Wherever possible, the devised mechanisms reflect existing conventions and frequency distributions and exploit domain-specific means to make ambiguities explicit.

While human-oriented controlled languages developed and applied in the domain of technical documentation have received considerable attention, language control exerted in the process of legislative drafting has, until recently, gone relatively unnoticed by the controlled language community. This paper considers existing legislative drafting guidelines from the perspective of controlled language. It presents the results of a qualitative comparison of the rule sets of four German-language legislative drafting guidelines from Austria, Germany and Switzerland with a representative collection of controlled language rules published by the German Professional Association for Technical Communication. The analysis determines the extent to which the respective rule sets control the same or similar aspects of language use and identifies the main differences between legislative drafting guidelines and controlled language rules for technical writing.