Models of story understanding in artificial intelligence and cognitive psychology typically concentrate on the construction of representations of story content. Construction of a 'complete' representation (informally equivalent to an 'understanding') requires inferences which establish coherence links between text statements. This report examines how reality-based links (e.g. causal connections...

A common practice in Linguistics today is to analyze the meaning of natural language (NL) using logic. The meaning of a sentence is defined in terms of some truth conditions on a set-theoretical model structure. The translation from sentences to truth conditions is done via an intermediate precise logical language in a compositional way: each syntactic tree of a phrase in the NL is associated w...

Theoretical models of text processing, such as the construction-integration framework, pose fundamental questions about causal inference making that are not easily addressed by behavioral studies. In particular, a common result is that causal relatedness has a different effect on text reading times than on memory for the text: Whereas reading times increase linearly as causal relatedness decrea...

the commentary of mir sayyed sharif jurjani on ibn hajib’s kafaya is the most valid persian commentary on this grammar book. jurjani has expressed the arabic grammar principles through an eloquent and simple language, yet in a robust and logical style. the discussion of triptote and diptote is among the most elaborate and complex topics of arabic grammar. however, jurjani has discussed differen...

The problem of deciding what is implied by a written text. of “reading between the lines” is the problem of text Inference. To extract proper inferences from a text requires a great deal of generol knowledge on the port of the reader. Past approaches have often used a “strong method” tuned to process a particular kind of knowledge structure (such OS a script, or a plan). The alternative is a “w...

Current results in basic Information Extraction tasks such as Named Entity Recognition or Event Extraction suggest that we are close to achieving a stage where the fundamental units for text understanding are put together; namely, predicates and their arguments. However, other layers of information, such as event modality, are essential for understanding, since the inferences derivable from fac...

Our goal is the automatic abstraction of journal articles, initially in the field of crop protection. We build a set of templates against which the original text is compared. The templates are designed so that they match the text at points of high information content, where inferences can be made about which expressions best reflect the content of the document. Strings found by matching templat...

In my opinion, the ultimate goal of NLP is to create a computer that really understands the meaning and information conveyed by a Natural Language (NL) text or speech. From a practical point of view, we would like computers to read and understand information in texts so that they could answer correctly questions about that information.2 From a scientific perspective, if a computer is able to un...

It has become nearly axiomatic (and even likely true) to hold that inference generation during language comprehension is a function of two things: (1) the nature of the inference under consideration and (2) the conditions under which the inference is examined. Thus, in the first case, we find the literature rife with observations that while there is little evidence of "automatic" generation of ...

To study false memories in older adults, a lot of experiments used the DRM paradigm (Deese, Roediger et McDermott). Most of the time, the results showed that older adults make more false memories than young adults. To test this hypothesis with a more ecological material, we used a situation of text reading. When we read a text, we activate predictive inferences, which are anticipations of what ...