This paper presents a source language diagnostic system for controlled translation. Diagnostics were designed and implemented to address the most difficult rewrites for authors, based on an empirical analysis of log files containing over 180,000 sentences. The design and implementation of the diagnostic system are presented, along with experimental results from an empirical evaluation of the completed system. We found that the diagnostic system can correctly identify the problem in 90.2% of the cases. In addition, depending on the type of grammar problem, the diagnostic system may offer a rewritten sentence. We found that 89.4% of the rewritten sentences were correctly rewritten. The results suggest that these methods could be used as the basis for an automatic rewriting system in the future.

This paper presents an overview of the tools provided by KANTOO MT system for controlled source language checking, source text analysis, and terminology management. The steps in each process are described, and screen images are provided to illustrate the system architecture and example tool interfaces.

This paper describes the results of a feasibility study which focused on deriving semantic networks from descriptive texts using controlled language. The KANT system [3,6] was used to analyze input paragraphs, producing sentence-level interlingua representations. The interlinguas were merged to construct a paragraph-level representation, which was used to create a semantic network in Conceptual Graph (CG) [1] format. The interlinguas are also translated (using the KANTOO generator) into OWL statements for entry into the Ontology Works electrical power factbase [9]. The system was extended to allow simple querying in natural language.

We will present the KANTOO machine translation environment, a set of software servers and tools for multilingual document production. KANTOO includes modules for source language analysis, target language generation, source terminology management, target terminology management, and knowledge source development (see Figure 1).

We describe the automatic resolution of pronominal anaphora using KANT Controlled English (KCE) and the KANTOO English-to-Spanish MT system. Our algorithm is based on a robust, syntax-based approach that applies a set of restrictions and preferences to select the correct antecedent. We report a success rate of 89.6% on a training corpus with 289 anaphors, and 87.5% on held-out data containing 145 anaphors. Resolution of anaphors is important in translation, due to gender mismatches among languages; our approach translates anaphors to Spanish with 97.2% accuracy.