This is a companion paper to [6] where a natural deduction system for propositional hybrid logic is given. In the present paper we generalize the system to the first-order case. Our natural deduction system for first-order hybrid logic can be extended with additional inference rules corresponding to conditions on the accessibility relations and the quantifier domains expressed by so-called geom...

Large-scale natural language generation requires the integration of vast amounts of knowledge: lexical, grammatical, and conceptual. A robust generator must be able to operate well even when pieces of knowledge are missing. It must also be robust against incomplete or inaccurate inputs. To attack these problems, we have built a hybrid generator , in which gaps in symbolic knowledge are lled by ...

This paper describes the use of a statistical structural N-gram model in the natural language generation component of a Spanish-English generationheavy hybrid machine translation system. A structural N-gram model captures the relationship between words in a dependency representation without taking into account the overall structure at the phrase level. The model is used together with other comp...

In recent years, the Natural Language Processing scene has witnessed the steady growth of interest in connectionist modeling. The main appeal of such an approach is that one does not have to determine the grammar rules in advance: the learning abilities displayed by such systems take care of input regularities. Better and faster learning can be obtained through the implementation of a symbolic-...

This paper presents an overview of a robust, broad-coverage, and application-independent natural language generation system. It demonstrates how the different language generation components function within a multilingual Machine Translation (MT) system, using the languages that we are currently working on (English, Spanish, Japanese, and Chinese). Section 1 provides a system description. Sectio...

Large-scale natural language generation requires the integration of vast amounts of knowledge: lexical, grammatical, and conceptual. A robust generator must be able to operate well even when pieces of knowledge are missing. It must also be robust against incomplete or inaccurate inputs. To attack these problems, we have built a hybrid generator , in which gaps in symbolic knowledge are lled by ...

Event detection remains a challenge due to the difficulty at encoding the word semantics in various contexts. Previous approaches heavily depend on languagespecific knowledge and pre-existing natural language processing (NLP) tools. However, compared to English, not all languages have such resources and tools available. A more promising approach is to automatically learn effective features from...

Morphological Analyzer is a tool which performs syntactic analysis of a word and finds root form of input inflected word form. Morph analyzer serves as a pre-processing tool for many NLP applications. Significant amount of work has been done in this area for many Indian languages but not much work has been reported for Gujarati language. We present Morph analyzer for Gujarati language. The Morp...

In this paper, we present EXEMPLARS, an object-oriented, rule-based framework designed to support practical, dynamic text generation, emphasizing its novel features compared to .existing hybrid systems that mix template-style and more sophisticated techniques. These features-.include an extensible classification-based text planning mechanism, a definition language that is a superset of the Java...

European water frog hybrids Rana esculenta (Rana ridibunda x Rana lessonae) reproduce hemiclonally, transmitting only their ridibunda genome to gametes. We compared fitness-related larval life-history traits of natural R. esculenta from Poland with those of the two sympatric parental species and of newly generated F1 hybrids. Compared with either parental species, F1 hybrid offspring had higher...