An emerging task in text understanding and generation is to categorize information as fact or opinion and to further attribute it to the appropriate source. Corpus annotation schemes aim to encode such distinctions for NLP applications concerned with such tasks, such as information extraction, question answering, summarization, and generation. We describe an annotation scheme for marking the attribution of abstract objects such as propositions, facts and eventualities associated with discourse relations and their arguments annotated in the Penn Discourse TreeBank. The scheme aims to capture the source and degrees of factuality of the abstract objects. Key aspects of the scheme are annotation of the text spans signalling the attribution, and annotation of features recording the source, type, scopal polarity, and determinacy of attribution.

The annotations of the Penn Discourse Treebank (PDTB) include (1) discourse connectives and their arguments, and (2) attribution of each argument of each connective and of the relation it denotes. Because the PDTB covers the same text as the Penn TreeBank WSJ corpus, syntactic and discourse annotation can be compared. This has revealed significant differences between syntactic structure and discourse structure, in terms of the arguments of connectives, due in large part to attribution. We describe these differences, an algorithm for detecting them, and finally some experimental results. These results have implications for automating discourse annotation based on syntactic annotation.

This paper considers the problem of checking whether an organization conforms to a body of regulation. Conformance is cast as a trace checking question-the regulation is represented in a logic that is evaluated against an abstract trace or run representing the operations of an organization. We focus on a problem in designing a logic to represent regulation. A common phenomenon in regulatory texts is for sentences to refer to others for conditions or exceptions. We motivate the need for a formal representation of regulation to accommodate such references between statements. We then extend linear temporal logic to allow statements to refer to others. The semantics of the resulting logic is defined via a combination of techniques from Reiter's default logic and Kripke's theory of truth. Comments

We consider the problem of checking whether the operations of an organization conform to a body of regulation. The immediate motivation comes from the analysis of the U.S. Food and Drug Administration regulations that apply to bloodbanks -organizations that collect, process, store, and use donations of blood and blood components. Statements in such regulations convey constraints on operations or sequences of operations that are performed by an organization. It is natural to express these constraints in a temporal logic.There are two important features of regulatory texts that need to be accommodated by a representation in logic. First, the constraints conveyed by regulation can be obligatory (required) or permitted (optional). Second, statements in regulation refer to others for conditions or exceptions. An organization conforms to a body of regulation if and only if it satisfies all the obligations. However, permissions provide exceptions to obligations, indirectly affecting conformance.In this paper, we extend linear temporal logic to distinguish between obligations and permissions, and to allow statements to refer to others. While the resulting logic allows for a direct representation of regulation, evaluating references between statements has high complexity. We discuss an empirically motivated assumption that lets us replace references with tests of lower complexity, leading to efficient trace-checking algorithms in practice.Abstract. We consider the problem of checking whether the operations of an organization conform to a body of regulation. The immediate motivation comes from the analysis of the U.S. Food and Drug Administration regulations that apply to bloodbanks -organizations that collect, process, store, and use donations of blood and blood components. Statements in such regulations convey constraints on operations or sequences of operations that are performed by an organization. It is natural to express these constraints in a temporal logic. There are two important features of regulatory texts that need to be accommodated by a representation in logic. First, the constraints conveyed by regulation can be obligatory (required) or permitted (optional). Second, statements in regulation refer to others for conditions or exceptions. An organization conforms to a body of regulation if and only if it satisfies all the obligations. However, permissions provide exceptions to obligations, indirectly affecting conformance. In this paper, we extend linear temporal logic to distinguish between obligations and permissions, and to allow statements to refer to others. While the resulting logic allows for a direct representation of regulation, evaluating references between statements has high complexity. We discuss an empirically motivated assumption that lets us replace references with tests of lower complexity, leading to efficient trace-checking algorithms in practice. ⋆

No abstract