A tool introduced by Rastier (and based on Sowa, 1984), the semantic graph can be used to represent any semantic structure in terms of semes and the relations between them. The semes are the nodes of the semantic graph (shown in boxes or brackets) and the relations are the links (shown in ellipses or parentheses). The arrows indicate the direction of the relation between nodes. Most semantic st...

Semantic relationships between words comprised by thesauri are essential features for IR, text mining and information extraction systems. This paper introduces a new approach to identification of semantic relations such as synonymy by a lexical graph. The graph is generated from a text corpus by embedding syntactically parsed sentences in the graph structure. The vertices of the graph are lexic...

We describe a new approach to disambiguating semantic frames evoked by lexical predicates previously unseen in a lexicon or annotated data. Our approach makes use of large amounts of unlabeled data in a graph-based semi-supervised learning framework. We construct a large graph where vertices correspond to potential predicates and use label propagation to learn possible semantic frames for new o...

Large scale of semantically enriched data is the foundation of the semantic web. We introduce the model used in SESQ* system as the presentation layer of the semantic contents. It is an abstract graph independent of the data storage layer and application layer. Semantic contents of a specified domain are organized as nodes and arcs in the graph. GQML, a manipulation language, is designed for th...

The need for efficient methods for archiving and retrieving personal digital photo collections arises due to a significant increase in the number of digital images and videos that people have to manage. We propose a semantic face matching approach for managing consumer photographs based on semantic face attributes. These attributes are organized as a semantic face graph (derived from a 3D gener...

Semantic maps are a means of representing universal structure underlying crosslanguage semantic variation. However, no algorithm has existed for inferring a graph-based semantic map from data. Here, we note that this open problem is formally identical to the known problem of inferring a social network from disease outbreaks. From this identity it follows that semantic map inference is computati...

Abstract We describe two mathematical representations for what have come to be called “semantic maps”, that is, of typological universals linguistic co-expression with the aim inferring similarity relations between concepts from those universals. The are a graph structure and Euclidean space, latter as inferred through multidimensional scaling. Graph in types. In both types, meanings represente...

A semantic network or net is a graph structure for representing knowledge in patterns of interconnected nodes and arcs. Computer implementations of semantic networks were first developed for artificial intelligence and machine translation, but earlier versions have long been used in philosophy, psychology, and linguistics. The Giant Global Graph of the Semantic Web is a large semantic network (...

Using the SemEval-2014 Task 8 data, we profile the syntactic tree parsing techniques for semantic graph parsing. In particular, we implement different transitionbased and graph-based models, as well as a parser ensembler, and evaluate their effectiveness for semantic dependency parsing. Evaluation gauges how successful data-driven dependency graph parsing can be by applying existing techniques.

Shallow semantic parsing, the automatic identification and labeling of sentential constituents, has recently received much attention. Our work examines whether semantic role information is beneficial to question answering. We introduce a general framework for answer extraction which exploits semantic role annotations in the FrameNet paradigm. We view semantic role assignment as an optimization ...