An important task in NLP applications such as sentence simplification is the ability to take a long, complex sentence and split it into shorter sentences, rephrasing as necessary. We introduce a novel dataset and a new model for this split and rephra
se' task. Our BiSECT training data consists of 1 million long English sentences paired with shorter, meaning-equivalent English sentences. We obtain these by extracting 1-2 sentence alignments in bilingual parallel corpora and then using machine translation to convert both sides of the corpus into the same language. BiSECT contains higher quality training examples than the previous Split and Rephrase corpora, with sentence splits that require more significant modifications. We categorize examples in our corpus and use these categories in a novel model that allows us to target specific regions of the input sentence to be split and edited. Moreover, we show that models trained on BiSECT can perform a wider variety of split operations and improve upon previous state-of-the-art approaches in automatic and human evaluations.
The state-of-the-art on basic, single-antecedent anaphora has greatly improved in recent years. Researchers have therefore started to pay more attention to more complex cases of anaphora such as split-antecedent anaphora, as in Time-Warner is conside
ring a legal challenge to Telecommunications Inc's plan to buy half of Showtime Networks Inc--a move that could lead to all-out war between the two powerful companies''. Split-antecedent anaphora is rarer and more complex to resolve than single-antecedent anaphora; as a result, it is not annotated in many datasets designed to test coreference, and previous work on resolving this type of anaphora was carried out in unrealistic conditions that assume gold mentions and/or gold split-antecedent anaphors are available. These systems also focus on split-antecedent anaphors only. In this work, we introduce a system that resolves both single and split-antecedent anaphors, and evaluate it in a more realistic setting that uses predicted mentions. We also start addressing the question of how to evaluate single and split-antecedent anaphors together using standard coreference evaluation metrics.
Increasing data rate in optical communication systems leads to nonlinear electromagnet phenomenon in optical signal along fiber, and causes distortion in it.Thefiber dispersion is a linear phenomenon that causes difficulties toachieve high bit rate a
nd distance product.The limiting of nonlinear effects requireslow input power level, but this induces lowsignal to noise ratio. So, we search another solutions.
This paper studies Split Step Fourier Transform Algorithm (SSFTM) used to solve partial differential nonlinear Schrödinger equation (NLSE).Then, we use it for simulating optical signal propagating in fiber by using MATLAB program, and designing fiber optic block could add it to MATLAB Simulink Library. Finally ,in this paper, we achieved results for selecting important parameters in single mode fiber for high bit rate, for improving bit error rate and Qcoefficient.
Treatment of dentofacial deformities with jaw osteotomies has an effect on
airway anatomy, therefore mandibular setback surgery has potential to diminish airway size.
The aim of this study was evaluation the effect of mandibular setback surgery by
bilateral sagittal split
ramus osteotomy (BSSRO) on lower pharyngeal airway size in anteroposterior direction retrolingually
and hyoid bone position.
