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This paper investigates the relation between TT-MCTAG, a formalism used in computational linguistics, and RCG. RCGs are known to describe exactly the class PTIME; simple RCG even have been shown to be equivalent to linear context-free rewriting systems, i.e., to be mildly context-sensitive. TT-MCTAG has been proposed to model free word order languages. In general, it is NP-complete. In this paper, we will put an additional limitation on the derivations licensed in TT-MCTAG. We show that TT-MCTAG with this additional limitation can be transformed into equivalent simple RCGs. This result is interesting for theoretical reasons (since it shows that TT-MCTAG in this limited form is mildly context-sensitive) and, furthermore, even for practical reasons: We use the proposed transformation from TT-MCTAG to RCG in an actual parser that we have implemented.
The distribution of linguistic structures in the world is the joint product of universal principles, inheritance from ancestor languages, language contact, social structures, and random fluctuation. This paper proposes a method for evaluating the relative significance of each factor — and in particular, of universal principles — via regression modeling: statistical evidence for universal principles is found if the odds for families to have skewed responses (e.g. all or most members have postnominal relative clauses) as opposed to having an opposite response skewing or no skewing at all, is significantly higher for some condition (e.g. VO order) than for another condition, independently of other factors.
Friedrich Schlegel's lasting contribution to linguistics is usually seen in the impact that his book "Über die Sprache und Weisheit der Indier" from 1808 left on comparative linguistics and on the study of Sanskrit. Schlegel was one of the first European scholars to have studied Sanskrit extensively and he made a number of translations of Sanskrit literature into German which make up one third of "Über die Sprache und Weisheit der Indier". Schlegel's book is widely regarded as a founding document both of comparative linguistics and of indology, a fact which is quite remarkable in light of the development of Schlegel's thought after this text. His interest in Indian studies ceased more or less directly with the publication of this work, while his thoughts on language became more and more suffused by transcendental philosophy.
Focus asymmetries in Bura
(2008)
This article presents the central aspects of the focus system of Bura (Chadic), which exhibits a number of asymmetries: Grammatical focus marking is obligatory only with focused subjects, where focus is marked by the particle án following the subject. Focused subjects remain in situ and the complement of án is a regular VP. With nonsubject foci, án appears in a cleft-structure between the fronted focus constituent and a relative clause. We present a semantically unified analysis of focus marking in Bura that treats the particle as a focusmarking copula in T that takes a property-denoting expression (the background) and an individual-denoting expression (the focus) as arguments. The article also investigates the realization of predicate and polarity focus, which are almost never marked. The upshot of the discussion is that Bura shares many characteristic traits of focus marking with other Chadic languages, but it crucially differs in exhibiting a structural difference in the marking of focus on subjects and non-subject constituents.
A series of production and perception experiments investigating the prosody and well-formedness of special sentences, called Wide Focus Partial Fronting (WFPF), which consist of only one prosodic phrase and a unique initial accented argument, are reported on here. The results help us to decide between different models of German prosody. The absence of pitch height difference on the accent of the sentence speaks in favor of a relative model of prosody, in which accents are scaled relative to each other, and against models in which pitch accents are scaled in an absolute way. The results also speak for a model in which syntax, but not information structure, influences the prosodic phrasing. Finally, perception experiments show that the prosodic structure of sentences with a marked word order needs to be presented for grammaticality judgments. Presentation of written material only is not enough, and falsifies the results.
This paper deals with the variable position of adjectives in the Romanian DP. As all other Romance languages, Romanian allows for adjectives to appear in both prenominal and post-nominal position. In addition, however, Romanian has a third pattern: the so-called cel construction, in which the adjective in the post-nominal position is preceded by a determiner-like element, cel. This pattern is superficially similar to Determiner Spreading in Greek. In this paper we contrast the cel construction to Greek DS and discuss the similarities and differences between the two. We then present an analysis of cel as involving an appositive specification clause, building on de Vries (2002). We argue that the same structure is also involved in the context of nominal ellipsis, the second environment in which cel is found.
The ACL 2008 Workshop on Parsing German features a shared task on parsing German. The goal of the shared task was to find reasons for the radically different behavior of parsers on the different treebanks and between constituent and dependency representations. In this paper, we describe the task and the data sets. In addition, we provide an overview of the test results and a first analysis.
The problem of vocalization, or diacritization, is essential to many tasks in Arabic NLP. Arabic is generally written without the short vowels, which leads to one written form having several pronunciations with each pronunciation carrying its own meaning(s). In the experiments reported here, we define vocalization as a classification problem in which we decide for each character in the unvocalized word whether it is followed by a short vowel. We investigate the importance of different types of context. Our results show that the combination of using memory-based learning with only a word internal context leads to a word error rate of 6.64%. If a lexical context is added, the results deteriorate slowly.