Example-based controlled translation

The first research on integrating controlled language data in an Example-Based Machine Translation (EBMT) system was published in [Gough & Way, 2003]. We improve on their sub-sentential alignment algorithm to populate the system’s databases with more than six times as many potentially useful fragments. Together with two simple novel improvements—correcting mistranslations in the lexicon, and allowing multiple translations in the lexicon—translation quality improves considerably when target language translations are constrained. We also develop the first EBMT system which attempts to filter the source language data using controlled language specifications. We provide detailed automatic and human evaluations of a number of experiments carried out to test the quality of the system. We observe that our system outperforms Logomedia in a number of tests. Finally, despite conflicting results from different automatic evaluation metrics, we observe a preference for controlling the source data rather than the target translations

Controlled generation in example-based machine translation

The theme of controlled translation is currently in vogue in the area of MT. Recent research (Sch¨aler et al., 2003; Carl, 2003) hypothesises that EBMT systems are perhaps best suited to this challenging task. In this paper, we present an EBMT system where the generation of the target string is filtered by data written according to controlled language specifications. As far as we are aware, this is the only research available on this topic. In the field of controlled language applications, it is more usual to constrain the source language in this way rather than the target. We translate a small corpus of controlled English into French using the on-line MT system Logomedia, and seed the memories of our EBMT system with a set of automatically induced lexical resources using the Marker Hypothesis as a segmentation tool. We test our system on a large set of sentences extracted from a Sun Translation Memory, and provide both an automatic and a human evaluation. For comparative purposes, we also provide results for Logomedia itself

RuleCNL: A Controlled Natural Language for Business Rule Specifications

Business rules represent the primary means by which companies define their business, perform their actions in order to reach their objectives. Thus, they need to be expressed unambiguously to avoid inconsistencies between business stakeholders and formally in order to be machine-processed. A promising solution is the use of a controlled natural language (CNL) which is a good mediator between natural and formal languages. This paper presents RuleCNL, which is a CNL for defining business rules. Its core feature is the alignment of the business rule definition with the business vocabulary which ensures traceability and consistency with the business domain. The RuleCNL tool provides editors that assist end-users in the writing process and automatic mappings into the Semantics of Business Vocabulary and Business Rules (SBVR) standard. SBVR is grounded in first order logic and includes constructs called semantic formulations that structure the meaning of rules.Comment: 12 pages, 7 figures, Fourth Workshop on Controlled Natural Language (CNL 2014) Proceeding

Generating natural language descriptions of Z test cases

Critical software most often requires an independent validation and verification (IVV). IVV is usually performed by domain experts, who are not familiar with specific, many times formal, development technologies. In addition, model-based testing (MBT) is a promising testing technique for the verification of critical software. Test cases generated by MBT tools are logical descriptions. The problem is, then, to provide natural language (NL) descriptions of these test cases, making them accessible to domain experts. In this paper, we present ongoing research aimed at finding a suitable method for generating NL descriptions from test cases in a formal specification language. A first prototype has been developed and applied to a real-world project in the aerospace sector

Automatic Unbounded Verification of Alloy Specifications with Prover9

Alloy is an increasingly popular lightweight specification language based on relational logic. Alloy models can be automatically verified within a bounded scope using off-the-shelf SAT solvers. Since false assertions can usually be disproved using small counter-examples, this approach suffices for most applications. Unfortunately, it can sometimes lead to a false sense of security, and in critical applications a more traditional unbounded proof may be required. The automatic theorem prover Prover9 has been shown to be particularly effective for proving theorems of relation algebras [7], a quantifier-free (or point-free) axiomatization of a fragment of relational logic. In this paper we propose a translation from Alloy specifications to fork algebras (an extension of relation algebras with the same expressive power as relational logic) which enables their unbounded verification in Prover9. This translation covers not only logic assertions, but also the structural aspects (namely type declarations), and was successfully implemented and applied to several examples