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The paper presents some aspects involved in the formalization and implementation of HPSG theories. As basis, the logical setups of Carpenter (1992) and King (1989, 1994) are briefly compared regarding their usefulness as basis for HPSGII (Pollard and Sag 1994). The possibilities for expressing HPSG theories in the HPSGII architecture and in various computational systems (ALE, Troll, CUF, and TFS) are discussed. Beside a formal characterization of the possibilities, the paper investigates the specific choices for constraints with certain linguistic motivations, i.e. the lexicon, structure licencing, and grammatical principles. An ALE implementation of a theory for German proposed by Hinrichs and Nakazawa (1994) is used as example and the ALE grammar is included in the appendix.
Finding simple, non-recursive, base noun phrases is an important subtask for many natural language processing applications. While previous empirical methods for base NP identification have been rather complex, this paper instead proposes a very simpl
Constituent and dependency parsing, the two classic forms of syntactic parsing, have been found to benefit from joint training and decoding under a uniform formalism, Head-driven Phrase Structure Grammar (HPSG). However, decoding this unified grammar
We survey several problems related to logical aspects of quantum structures. In particular, we consider problems related to completions, decidability and axiomatizability, and embedding problems. The historical development is described, as well as recent progress and some suggested paths forward.
We develop an approach to choice principles and their contrapositive bar-induction principles as extensionality schemes connecting an intensional or effective view of respectively ill-and well-foundedness properties to an extensional or ideal view of
Instance segmentation models today are very accurate when trained on large annotated datasets, but collecting mask annotations at scale is prohibitively expensive. We address the partially supervised instance segmentation problem in which one can tra