This paper provides a brief description of the system for recognizing textual entailment (RTE) Language Computer Corporation (LCC) used in the 2008 TAC RTE-4 Evaluation. Our RTE-4 work follows our previous work (Hickl and Bensley, 2007; Bensley and Hickl, 2008; Hickl, 2008) in using a pipeline of lightweight, largely statistical systems for commitment extraction, lexical alignment, and entailme...

This paper covers the recognition of textual entailment by means of different approaches based on lexical similarities and syntactic trees. These approaches are easily portable to other languages. We present the achieved results for each individual approach and we propose a simple voting strategy between these approaches and our previous system (presented in Second PASCAL Recognising Textual En...

Systems designed to recognize textual entailment typically employ both syntax and semantics. Our goal in this paper is to explore the degree to which semantics alone can be used to accurately detect entailment so that we can gain a better understanding of this single component within an entailment system. This paper reports the knowledge-bases considered and selected for person names, locations...

Most Web-based Q/A systems work by finding pages that contain an explicit answer to a question. These systems are helpless if the answer has to be inferred from multiple sentences, possibly on different pages. To solve this problem, we introduce the HOLMES system, which utilizes textual inference (TI) over tuples extracted from text. Whereas previous work on TI (e.g., the literature on textual ...

In the logic approach to Recognizing Textual Entailment, identifying phrase-tophrase semantic relations is still an unsolved problem. Resources such as the Paraphrase Database offer limited coverage despite their large size whereas unsupervised distributional models of meaning often fail to recognize phrasal entailments. We propose to map phrases to their visual denotations and compare their me...

Contextual information plays a key role in the automatic interpretation of text. This paper is concerned with the identification of textual contexts. A context taxonomy is introduced first, followed by an algorithm for detecting context boundaries. Experiments on the detection of subjective contexts using a machine learning model were performed using a set of syntactic features.

Today, the syntax of visual specification languages such as UML is typically defined using meta-modelling techniques. However, this kind of syntax definition has drawbacks. In particular, graphic meta-models are not powerful enough, so they must be augmented by a textual constraint language. As an alternative, we present in this paper, a text-based technique for the syntax definition of a graph...

This study aimed to explore the function and frequency of textual metadiscourse markers (MDMs) in scientific English and Persian texts. Based on the qualitative and quantitative analysis of textual markers characterizing the selected genre, four different textbooks, two written in English and two in Persian were analyzed to identify the textual metadiscourse categories (including logical marker...

textual coherence in cloudy semantic relations through which the relation is each piece of speech or writing acts as context. ma.k holliday and r.hassan played a key ale estabhshing the relationship in contchal shachre and the relationship among sentence elements. the believe that coherence applies to all kids of relations which link one element of the sentence to the element in previous senten...