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This paper proposes an annotating scheme that encodes honorifics (respectful words). Honorifics are used extensively in Japanese, reflecting the social relationship (e.g. social ranks and age) of the referents. This referential information is vital for resolving zero
pronouns and improving machine translation outputs. Annotating honorifics is a complex task that involves identifying a predicate with honorifics, assigning ranks to referents of the
predicate, calibrating the ranks, and connecting referents with their predicates.
The process of turning a hand-written HPSG theory into a working computational grammar requires complex considerations. Two leading platforms are available for implementing HPSG grammars: The LKB and TRALE. These platforms are based on different approaches, distinct in their underlying logics and implementation details. This paper adopts the perspective of a computational linguist whose goal is to implement an HPSG theory. It focuses on ten different dimensions, relevant to HPSG grammar implementation, and examines, compares, and evaluates the different means which the two approaches provide for implementing them. The paper concludes that the approaches occupy opposite positions on two axes: faithfulness to the hand-written theory and computational accessibility. The choice between them depends largely on the grammar writer's preferences regarding those properties.
We present a novel well-formedness condition for underspecified semantic representations which requires that every correct MRS representation must be a net. We argue that (almost) all correct MRS representations are indeed nets, and apply this condition to identify a set of eleven rules in the English Resource Grammar (ERG) with bugs in their semantics component. Thus we demonstrate that the net test is useful in grammar debugging.
The Deep Linguistic Processing with HPSG Initiative (DELH-IN) provides the infrastructure needed to produce open-source semantic transfer-based machine translation systems. We have made available a prototype Japanese-English machine translation system built from existing resources include parsers, generators, bidirectional grammars and a transfer engine.