Encoding Lexicalized Tree Adjoining Grammars with a Nonmonotonic Inheritance Hierarchy

This paper shows how DATR, a widely used formal language for lexical knowledge representation, can be used to define an LTAG lexicon as an inheritance hierarchy with internal lexical rules. A bottom-up featural encoding is used for LTAG trees and this allows lexical rules to be implemented as covariation constraints within feature structures. Such an approach eliminates the considerable redundancy otherwise associated with an LTAG lexicon.Comment: Latex source, needs aclap.sty, 8 page

Inheritance hierarchies and historical reconstruction: towards a history of Slavonic colour terms

The last decade has witnessed an interest in inheritance hierarchies for the representation of linguistic knowledge. An obvious application is to historical reconstruction of a language family, but this is largely unexplored territory. We demonstrate the merits of such an approach with a default inheritance treatment of the colour terms of Slavonic: Slavonic because it is uncontroversially a genetic unit, and colour terms both because of their universality and because of the tight constraints on a language\u27s colour term inventory (Berlin & Kay 1969, and subsequent work). In section I we discuss the colour terms of Slavonic and introduce Berlin and Kay\u27s typology and the notion of basic colour term. Section 2 describes our methodology and in section 3 we show how it is applied to Slavonic. The main results are discussed in section 4

`Lexical rules' are just lexical rules

The question we address in this paper is whether `Lexical Rules' deserve their grand status, a status that is often conveyed by a special purpose formalism and/or a separate component, one that may even be external to the lexicon proper. We will argue that they do not and that a lexical knowledge representation language that is as expressive as it needs to be for other lexical purposes will, ipso facto, be expressive enough to encode `Lexical Rules' internally as lexical rules. Such internal encoding is not only possible but also desirable since `Lexical Rules' will then automatically acquire other characteristics which are now standardly associated with common or garden lexical rules, including inheritance, generalization by default, and the ability to relate lexical information from different levels of linguistic description. We give examples of what we take to be instances of common or garden lexical rules and then show how the same formal machinery provides for the stateme..

The acquisition of asserted, presupposed, and pragmatically implied exhaustivity in Hungarian

The paper reports on three experiments in which the exhaustive interpretation of sentences containing the focus particle csak ‘only’, structural focus constructions, and sentences with neutral intonation and word order were investigated. The results obtained not only reveal the developmental trajectory of the adult-like comprehension of each sentence type, but also contribute to the discussion concerning the semantic or pragmatic nature of their exhaustive meaning component. As the three construction types were judged in different ways on a three-point scale, the findings appear to support the hypothesis according to which exhaustivity is part of the asserted content of sentences with csak ‘only’, it is context-independently presupposed in the case of structural focus, and in certain contexts it can arise as an implicature in the case of neutral utterances, as well

A Genome-Wide Screen for Promoter Methylation in Lung Cancer Identifies Novel Methylation Markers for Multiple Malignancies

BACKGROUND: Promoter hypermethylation coupled with loss of heterozygosity at the same locus results in loss of gene function in many tumor cells. The “rules” governing which genes are methylated during the pathogenesis of individual cancers, how specific methylation profiles are initially established, or what determines tumor type-specific methylation are unknown. However, DNA methylation markers that are highly specific and sensitive for common tumors would be useful for the early detection of cancer, and those required for the malignant phenotype would identify pathways important as therapeutic targets. METHODS AND FINDINGS: In an effort to identify new cancer-specific methylation markers, we employed a high-throughput global expression profiling approach in lung cancer cells. We identified 132 genes that have 5′ CpG islands, are induced from undetectable levels by 5-aza-2′-deoxycytidine in multiple non-small cell lung cancer cell lines, and are expressed in immortalized human bronchial epithelial cells. As expected, these genes were also expressed in normal lung, but often not in companion primary lung cancers. Methylation analysis of a subset (45/132) of these promoter regions in primary lung cancer (n = 20) and adjacent nonmalignant tissue (n = 20) showed that 31 genes had acquired methylation in the tumors, but did not show methylation in normal lung or peripheral blood cells. We studied the eight most frequently and specifically methylated genes from our lung cancer dataset in breast cancer (n = 37), colon cancer (n = 24), and prostate cancer (n = 24) along with counterpart nonmalignant tissues. We found that seven loci were frequently methylated in both breast and lung cancers, with four showing extensive methylation in all four epithelial tumors. CONCLUSIONS: By using a systematic biological screen we identified multiple genes that are methylated with high penetrance in primary lung, breast, colon, and prostate cancers. The cross-tumor methylation pattern we observed for these novel markers suggests that we have identified a partial promoter hypermethylation signature for these common malignancies. These data suggest that while tumors in different tissues vary substantially with respect to gene expression, there may be commonalities in their promoter methylation profiles that represent targets for early detection screening or therapeutic intervention

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Pragmatics

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