A key task in intelligent language processing is obtaining semantic representations that abstract away from surface lexical and syntactic decisions. The Abstract Meaning Representation (AMR) is one such representation, which represents the meaning of a sentence as labeled nodes in a graph (concepts) and labeled, directed edges between them (relations). A traditional problem of semantic represen...

In this paper, the system of language and architecture has been studied in three levels of elemental, structural and semantic in cases of traditional and modern mosques in Iran through the method of analyzing the content of texts and in a conceptual model. Then, in a comparative method, the common patterns of these systems have been explained at all three levels. The common features at the elem...

The patterns of semantic errors in speaking and writing are used to constrain claims about the structure of lexical access mechanisms in speech and written language production. It is argued that it is not necessary to postulate a modality-neutral level of lexical representation (lemma) that is intermediate between lexical-semantic representations and modality-specific lexical representations. A...

The investigation of language processing following brain damage may be used to constrain models of normal language processing. We review the literature on semantic and lexical processing deficits, focusing on issues of representation of semantic knowledge and the mechanisms of lexical access. The results broadly support a componential organization of lexical knowledge-the semantic component is ...

this paper, based on two dialects of kurdish, studies the -g{r suffix of farsi morphologically and semantically. in the sorani (so:rani) dialect of kurdish this suffix is -k{r. in hawrami (h{wrami) dialect of kurdish the present verbal stem of (k{rdaj) (to do) is -k{r and in sorani it is -k{. sorani has a suffix called -{r similar to english -er that produces nouns with mainly agent and instrum...

Semantic inference is an important component in many natural language understanding applications. Classical approaches to semantic inference rely on complex logical representations. However, practical applications usually adopt shallower lexical or lexical-syntactic representations, but lack a principled inference framework. We propose a generic semantic inference framework that operates direct...