Automatically Clustering Ontological Annotated Sentences to Detect Semantic Frames

Automatically Clustering Ontological Annotated Sentences to Detect Semantic Frames

Lexical databases of semantic frames have been shown to be useful in problems related to natural language processing. However, creation of such databases is a task that is time consuming and involves many manual steps. One of these steps is selection and grouping of sentences to identify frames. However, we advocate that if sentences were previously annotated with ontological information, this ...

From Ontological to Semantic Disagreement

Among Quine’s main concerns in his “On What There Is”, there was that of solving a problem of expressibility for ontological denials. His proposed solution to such a problem was, in a purely Carnapian vein, a shift of attention to the semantic features of ontological claims – what Quine called the strategy of “semantic ascent”. Quine’s relevant assumption is that talk about language is much les...

Clustering Sentences - Making Sense of Synonymous Sentences

Automatically Converting Tabular Data to Rdf: an Ontological Approach

Information residing in relational databases and delimited file systems are inadequate for reuse and sharing over the web. These file systems do not adhere to commonly set principles for maintaining data harmony. Due to these reasons, the resources have been suffering from lack of uniformity, heterogeneity as well as redundancy throughout the web. Ontologies have been widely used for solving su...

POS error detection in automatically annotated corpora

Recent work on error detection has shown that the quality of manually annotated corpora can be substantially improved by applying consistency checks to the data and automatically identifying incorrectly labelled instances. These methods, however, can not be used for automatically annotated corpora where errors are systematic and cannot easily be identified by looking at the variance in the data...