In this paper, we present a system for Arabic semantic role labeling (SRL) based on SVMs and standard features. The system is evaluated on the released SEMEVAL 2007 development and test data. The results show an Fβ=1 score of 94.06 on argument boundary detection and an overall Fβ=1 score of 81.43 on the complete semantic role labeling task using gold parse trees.

We present a system for the semantic role labeling task. The system combines a machine learning technique with an inference procedure based on integer linear programming that supports the incorporation of linguistic and structural constraints into the decision process. The system is tested on the data provided in CoNLL2004 shared task on semantic role labeling and achieves very competitive resu...

The focus of this study was to thoroughly exploit the capability of very high-resolution VHR satellite imagery such as Ikonos and QuickBird for disaster mitigation. An efficient automated methodology that detects damage was implemented to derive the rich information available from VHR satellite imagery. Consequently, the detected results and the VHR satellite imagery are attractively presented ...

Extracting water-bodies accurately is a great challenge from very high resolution (VHR) remote sensing imagery. The boundaries of water body are commonly hard to identify due the complex spectral mixtures caused by aquatic vegetation, distinct lake/river colors, silts near bank, shadows surrounding tall plants, and so on. diversity semantic information features need be increased for better extr...

IMPORTANCE Follow-up with a primary care provider (PCP) in addition to the surgical team is routinely recommended to patients discharged after major surgery despite no clear evidence that it improves outcomes. OBJECTIVE To test whether PCP follow-up is associated with lower 30-day readmission rates after open thoracic aortic aneurysm (TAA) repair and ventral hernia repair (VHR), surgical proc...

In this paper, we present a Chinese event extraction system. We point out a language specific issue in Chinese trigger labeling, and then commit to discussing the contributions of lexical, syntactic and semantic features applied in trigger labeling and argument labeling. As a result, we achieved competitive performance, specifically, F-measure of 59.9 in trigger labeling and F-measure of 43.8 i...

The PropBank primarily adds semantic role labels to the syntactic constituents in the parsed trees of the Treebank. The goal is for automatic semantic role labeling to be able to use the domain of locality of a predicate in order to find its arguments. In principle, this is exactly what is wanted, but in practice the PropBank annotators often make choices that do not actually conform to the Tre...

In this paper we present an intuitive way of semantic labeling of image content suited for query by image content from remote sensing image databases. The space of image content understanding is separated into a syntactic and a semantic space. The syntactic space contains objective, signaloriented classes of certain types of structures and the semantic space contains subjective, user-oriented c...

In this paper, we propose a semantic role labeling method using a maximum entropy model, which enables not only to exploit rich features but also to alleviate the data sparseness problem in a well-founded model. For applying the maximum entropy model to semantic role labeling, we take a incremental approach as follows: firstly, the semantic roles are assigned to the arguments in the immediate c...

Large-scale annotated corpora are a prerequisite to developing high-performance semantic role labeling systems. Unfortunately, such corpora are expensive to produce, limited in size, and may not be representative. Our work aims to reduce the annotation effort involved in creating resources for semantic role labeling via semi-supervised learning. The key idea of our approach is to find novel ins...