Extracting semantic roles is one of the major steps in representing text meaning. It refers to finding the semantic relations between a predicate and syntactic constituents in a sentence. In this paper we present a semantic role labeling system for Persian, using memory-based learning model and standard features. We show that good semantic parsing results can be achieved with a small 1300-sente...

In this article, we present a novel hybrid framework, which integrates spatial-temporal semantic segmentation with postclassification relearning, for multitemporal land use and cover (LULC) classification based on very high resolution (VHR) satellite imagery. To efficiently obtain optimal LULC maps, the framework utilizes model to harness temporal dependency extracting high-level features. addi...

State-of-the-art semantic role labeling (SRL) performance has been achieved using neural network models by incorporating syntactic feature information such as dependency trees. In recent years, breakthroughs end-to-end have resulted in a state-of-the-art SRL even without features. With the advent of language model called bidirectional encoder representations from transformers (BERT), another br...

AIM To assess development of reaching and head stability in infants at very high risk (VHR-infants) of cerebral palsy (CP) who did and did not develop CP. METHOD This explorative longitudinal study assessed the kinematics of reaching and head sway in sitting in 37 VHR-infants (18 CP) one to four times between 4.7 months and 22.6 months corrected age. Developmental trajectories were calculated...

We present a novel annotation framework for representing predicate-argument structures, which uses dependency trees to encode the syntactic and semantic roles of a sentence simultaneously. The main contribution is a semantic role transmission model, which eliminates the structural gap between syntax and shallow semantics, making them compatible. A Chinese semantic treebank was built under the p...

The new spaceborne very high resolution (VHR) SAR sensors onboard the TerraSAR-X and COSMO-SkyMED satellites have a spatial resolution of up to 1 meter. In VHR SAR data, features from individual urban structures, like buildings, can be identified in their characteristic settings in urban settlement patterns. In the context of situation assessment as initial reaction to man made or natural crisi...

Monitoring post-fire vegetation response using remotely-sensed images is a top priority for post-fire management. This study investigated the potential of very-high-resolution (VHR) GeoEye images on detecting the field-measured burn severity of a forest fire that occurred in Evros (Greece) during summer 2011. To do so, we analysed the role of topographic conditions and burn severity, as measure...

Detection of semantic roles associated with linguistic elements is important to the textual classification of communicative context into specific identities. In this paper, a new model for semantically identifying sentences is presented through contextual patterns. The proposed contextual pattern originated its structure from a labeling process of the semantic roles provided by constituents of ...

Semantic roles, which constitute a shallow form of meaning representation, have attracted increasing interest in recent years. Various applications have been shown to benefit from this level of semantic analysis, and a large number of publications has addressed the problem of semantic role labeling, i.e., the task of automatically identifying semantic roles in arbitrary sentences. A major limit...