4,701 research outputs found
Digital Three-Dimensional Atlas of Quail Development Using High-Resolution MRI
We present an archetypal set of three-dimensional digital atlases of the quail embryo based on microscopic magnetic resonance imaging (µMRI). The atlases are composed of three modules: (1) images of fixed ex ovo quail, ranging in age from embryonic day 5 to 10 (e05 to e10); (2) a coarsely delineated anatomical atlas of the µMRI data; and (3) an organ system–based hierarchical graph linked to the anatomical delineations. The atlas is designed to be accessed using SHIVA, a free Java application. The atlas is extensible and can contain other types of information including anatomical, physiological, and functional descriptors. It can also be linked to online resources and references. This digital atlas provides a framework to place various data types, such as gene expression and cell migration data, within the normal three-dimensional anatomy of the developing quail embryo. This provides a method for the analysis and examination of the spatial relationships among the different types of information within the context of the entire embryo
A Corpus-Based Investigation of Definite Description Use
We present the results of a study of definite descriptions use in written
texts aimed at assessing the feasibility of annotating corpora with information
about definite description interpretation. We ran two experiments, in which
subjects were asked to classify the uses of definite descriptions in a corpus
of 33 newspaper articles, containing a total of 1412 definite descriptions. We
measured the agreement among annotators about the classes assigned to definite
descriptions, as well as the agreement about the antecedent assigned to those
definites that the annotators classified as being related to an antecedent in
the text. The most interesting result of this study from a corpus annotation
perspective was the rather low agreement (K=0.63) that we obtained using
versions of Hawkins' and Prince's classification schemes; better results
(K=0.76) were obtained using the simplified scheme proposed by Fraurud that
includes only two classes, first-mention and subsequent-mention. The agreement
about antecedents was also not complete. These findings raise questions
concerning the strategy of evaluating systems for definite description
interpretation by comparing their results with a standardized annotation. From
a linguistic point of view, the most interesting observations were the great
number of discourse-new definites in our corpus (in one of our experiments,
about 50% of the definites in the collection were classified as discourse-new,
30% as anaphoric, and 18% as associative/bridging) and the presence of
definites which did not seem to require a complete disambiguation.Comment: 47 pages, uses fullname.sty and palatino.st
LFG without C-structures
We explore the use of two dependency parsers, Malt and MST, in a Lexical Functional Grammar parsing pipeline. We compare this to the traditional LFG parsing pipeline which uses constituency parsers. We train the dependency parsers not on classical LFG f-structures but rather on modified
dependency-tree versions of these in which all words in the input sentence are represented and multiple heads are removed. For the purposes of comparison, we also modify the existing CFG-based LFG parsing pipeline so that these "LFG-inspired" dependency trees are produced. We find that the differences in parsing accuracy over the various parsing architectures is small
Refining Implicit Argument Annotation for UCCA
Predicate-argument structure analysis is a central component in meaning
representations of text. The fact that some arguments are not explicitly
mentioned in a sentence gives rise to ambiguity in language understanding, and
renders it difficult for machines to interpret text correctly. However, only
few resources represent implicit roles for NLU, and existing studies in NLP
only make coarse distinctions between categories of arguments omitted from
linguistic form. This paper proposes a typology for fine-grained implicit
argument annotation on top of Universal Conceptual Cognitive Annotation's
foundational layer. The proposed implicit argument categorisation is driven by
theories of implicit role interpretation and consists of six types: Deictic,
Generic, Genre-based, Type-identifiable, Non-specific, and Iterated-set. We
exemplify our design by revisiting part of the UCCA EWT corpus, providing a new
dataset annotated with the refinement layer, and making a comparative analysis
with other schemes.Comment: DMR 202
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