This paper presents a hybrid approach for named entity (NE) tagging which combines Maximum Entropy Model (MaxEnt), Hidden Markov Model (HMM) and handcrafted grammatical rules. Eac...
This paper describes an approach to using semantic rcprcsentations for learning information extraction (IE) rules by a type-oriented inductire logic programming (ILl)) system. NLP...
In this paper, we propose a named-entity recognition (NER) system that addresses two major limitations frequently discussed in the field. First, the system requires no human interv...
We introduce a computable framework for Lebesgue’s measure and integration theory in the spirit of domain theory. For an effectively given second countable locally compact Hausd...
We present a model for data organized as graphs. Regular expressions over the types of the node and edge labels are used to qualify connected subgraphs. An algebraic language base...