Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …

The rapid increase in the flow rate of published digital information in all disciplines has
resulted in a pressing need for techniques that can simplify the use of this information. The …

This paper proposes a Hidden Markov Model (HMM) and an HMM-based chunk tagger, from
which a named entity (NE) recognition (NER) system is built to recognize and classify …

Methods and systems for providing start and stop properties to Semantic Web structured
resources and statements are disclosed. The start and stop properties can specify a lifetime …

In this chapter we present a brief overview of Information Extraction, which is an area of
natural language processing that deals with finding factual information in free text. In formal …

Natural language processing (NLP) is crucial in the current processing of data because it
takes into account many sources, formats, and purposes of data as well as information from …

The most important attribute of geospatial platforms is their unique potential to aggregate a
multitude of public and private geographic data sets, providing access to data from …

We present an implemented system for processing definite descriptions in arbitrary domains.
The design of the system is based on the results of a corpus analysis previously reported …

Interpreting anaphoric references is a fundamental aspect of our language competence that
has long attracted the attention of computational linguists. The appearance of ever-larger …

In this paper, we pose the classifier ensemble problem under single and multiobjective
optimization frameworks, and evaluate it for Named Entity Recognition (NER), an important …