In the realm of natural language processing, machine comprehension of textual documents is an incredibly important problem that presents various challenges and difficulties. A benchmark dataset for question answering named SQuAD is comprised of around a hundred thousand question-answer pairs, along with context paragraphs for each. The answer to each question is a span within the context, and i...

Recent work in markup studies suggests a profound role for context in understanding critical semantic distinctions in the use of XML markup. Specifically we argue that markup has illocutionary force, which can vary with context even while the syntax and propositional content of a markup utterance remains constant, and that the development of this insight can generalize and unify existing soluti...

This paper presents the QALL-ME Framework, a reusable architecture for building multiand cross-lingual Question Answering (QA) systems working on structured data modelled by an ontology. It is released as free open source software with a set of demo components and extensive documentation, which makes it easy to use and adapt. The main characteristics of the QALL-ME Framework are: (i) its domain...

Abstract
 First, it should be noted that the Alevi culture was created, transmitted and maintained mainly as an oral discourse. poetry played biggest role in this process. In study on poetic discourse, cem, poetry, dance, semah, prayer recitation of hymns, which are ritual, will discussed. The is creation Bektaşi, urbanite poets who used poetical forms classical Ottoman literature, or cour...

This paper introduces the methods employed by University of Houston team participating in the CL-SciSumm 2017 Shared Task at BIRNDL 2017 to identify reference spans in a reference document given sentences from citing papers. The following approaches were investigated: structural correspondence learning, positional language models, and textual entailment. In addition, we refined our methods from...

We propose new parse-free event-based features to be used in conjunction with lexical, syntactic, and semantic features of texts and hypotheses for Machine Learning-based Recognizing Textual Entailment. Our new similarity features are extracted without using shallow semantic parsers, but still lexical and compositional semantics are not left out. Our experimental results demonstrate that these ...

This paper presents the first round of the task on Cross-lingual Textual Entailment for Content Synchronization, organized within SemEval-2012. The task was designed to promote research on semantic inference over texts written in different languages, targeting at the same time a real application scenario. Participants were presented with datasets for different language pairs, where multi-direct...

In this paper we report the results obtained in the Semantic Textual Similarity (STS) task, with a system primarily developed for textual entailment. Our results are quite promising, getting a run ranked 39 in the official results with overall Pearson, and ranking 29 with the Mean metric.

Discourse references, notably coreference and bridging, play an important role in many text understanding applications, but their impact on textual entailment is yet to be systematically understood. On the basis of an in-depth analysis of entailment instances, we argue that discourse references have the potential of substantially improving textual entailment recognition, and identify a number o...