A Survey and Classification of Controlled Natural Languages <s> Types and Properties <s> PENG is a computer-processable controlled natural language designed for writing unambiguous and precise specifications. PENG covers a strict subset of standard English and is precisely defined by a controlled grammar and a controlled lexicon. In contrast to other controlled languages, the author does not need to know the grammatical restrictions explicitly. ECOLE, a look-ahead text editor, indicates the restrictions while the specification is written. The controlled lexicon contains domain-specific content words that can be defined by the author on the fly and predefined function words. Specifications written in PENG can be deterministically translated into discourse representations structures to cope with anaphora and presuppositions and also into first-order predicate logic. To test the formal properties of PENG, we reformulated Schubert's steamroller puzzle in PENG, translated the resulting specification via discourse representation structures into first-order predicate logic with equality, and proved the steamroller's conclusion with OTTER, a standard theorem prover. <s> BIB001 </s> A Survey and Classification of Controlled Natural Languages <s> Types and Properties <s> Many AI applications require a base of world knowledge to support reasoning. However, construction of such inferencecapable knowledge bases, even if constrained in coverage, remains one of the major challenges of AI. Authoring knowledge in formal logic is too complex a task for many users, while knowledge authored in unconstrained natural language is generally too difficult for computers to understand. However, there is an intermediate position, which we are pursuing, namely authoring knowledge in a restricted subset of natural language. Our claim is that this approach hits a “sweet spot” between the former two extremes, being both usable by humans and understandable by machines. We have developed such a language (called CPL, Computer-Processable Language), an interpreter, and a reasoner, and have used them to encode approximately 1000 “commonsense” rules (a mixture of general and domain-specific). The knowledge base is being used experimentally for semantic retrieval of video clips based on their captions, also expressed in CPL. In this paper, we describe CPL, its interpretation, and its use for reasoning, and discuss the strengths and weaknesses of restricted natural language as a the basis for knowledge representation. <s> BIB002 </s> A Survey and Classification of Controlled Natural Languages <s> Types and Properties <s> In a multilingual Semantic Web, authors might write in precise, expressive varieties of diverse languages. Do such controlled languages exist? Of 41 candidates, just 4 were (1) designed for multiple domains and genres and (2) documented enough for evaluation. A sample of Web statements on health and human rights revealed limited expressivity or precision in each language. The most expressive one avoided structural ambiguity but allowed semantic ambiguity that could frustrate human and machine comprehension. The possibility of a practical Web-scale controlled language remains undemonstrated but unrefuted. <s> BIB003
Let us now turn to the nature of CNLs. To bring order to their seemingly chaotic variety, more than 40 properties of such languages and their environments have been identified  ). Many of these properties, however, are fuzzy and do not allow for a strict categorization. For the survey to be presented in Section 4, we collect nine general and clear-cut properties and give them letter codes. As it turns out, however, these properties mainly describe the application environment of languages and not so much the languages themselves. For that reason, a classification scheme is introduced in the next section to describe the fundamental nature of CNLs and other languages. In general, controlled natural languages can be roughly subdivided according to the problem they are supposed to solve BIB001 : to improve communication among humans, especially speakers with different native languages (we will use the letter code C for these languages); to improve manual, computer-aided, semi-automatic, or automatic translation (T); and to provide a natural and intuitive representation for formal notations (F). The last type includes approaches for automatic execution of texts, which requires, at least conceptually, a mapping to an executable formalism. As we will see, these three types emerged at different points in time: Type C is the oldest, type T emerged later, and type F is the most recent of the three. Although this seems to be a sensible and useful subdivision, a simpler version based on just two types dominates the literature.  introduced the distinction between "humanoriented" and "computer-oriented" languages. The former roughly corresponds to type C, the latter to the types T and F. However, Huijsen observes that "it is often difficult to qualify a controlled language as either human-oriented or machine-oriented, since often simplification works both ways." Because these types describe problems rather than languages, reusing a language in a different problem domain can change its type even if the language itself has not changed at all. Other similar categorizations include the distinction between "naturalistic" (type C and T) and "formalistic" (type F) languages BIB003 BIB002 ) and the distinction between readability and translatability  . Another apparent fact is that some languages originated from academia (letter code A), some from industry (I), some from a government or a UN agency (G), and others from a combination of the three. In addition, the distinction between general purpose languages and those for a particular restricted domain is often discussed BIB003 . This is related to the distinction of whether the lexicon is open or closed (Adriaens and Schreors 1992). We will use the letter code D to denote languages targeting a specific and narrow domain. A further important difference is the one between written and spoken languages. We will use W to denote languages that are intended to be written, and S for those that are intended to be spoken. However, none of these distinctions seems to describe a fundamental language property: Languages that originated in one environment can later be used in another; the lexicon can later be declared open or closed; written languages can be read aloud; and spoken languages can be written down. The rules that define a CNL can be proscriptive or prescriptive (Nyberg, Mitamura The language originated from a government form of a given (natural) language. Languages with only prescriptive rules, in contrast, typically start from scratch. As we will see, there is a close connection of this distinction to the concept of simplicity as introduced in the next section. Because of their lack of generality, we do not include here more specific low-level properties such as the support for subclauses and free compounding (Adriaens and Schreors 1992), specific restrictions on grammatical tenses and modal verbs  , and support for interrogative and imperative sentences  . Table 1 summarizes the letter codes. Any two of these properties can overlap, and therefore any combination is possible in theory (with the exception that no language should be neither W nor S). Finally, there is one additional aspect of constructed languages that deserves attention: their life cycle. Some languages are not much more than abstract ideas, others have left this stage being applied to concrete problems, and yet others have progressed to widespread application in productive environments. At different stages of maturity, languages can be discontinued or abandoned, which signifies the end of their life cycle. Obviously, these different stages flow into each other and it is often difficult to name a concrete year of birth or death (especially the latter, as most CNLs die silently). Where possible, we will keep track of these life cycle properties.