In this paper we introduce a system that is designed to automatically populate a knowledge base from both structured and unstructured text given an ontology. Our system is designed as a modular end-to-end system that takes structured or unstructured data as input, extracts information, maps relevant information to an ontology, and finally disambiguates entities in the knowledge base. The novelty of our approach is that it is domain independent and can easily be adapted to new ontologies and domains. Unlike most knowledge base population systems, ours includes entity detection. This feature allows one to employ very complex ontologies that include events and the entities that are involved in the events.

Negation is present in all human languages and it is used to reverse the polarity of parts of a statement. It is a complex phenomenon that interacts with many other aspects of language. Besides the direct meaning, negated statements often carry a latent positive meaning. Negation can be interpreted in terms of its scope and focus. This paper explores the importance of both scope and focus to capture the meaning of negated statements. Some issues on detecting negation from text are outlined, the forms in which negation occurs are depicted and heuristics to detect its scope and focus are proposed.

In this paper, we discuss the question of closure conditions for dialogues in three different frameworks: W. C. Mann's DMT framework, Vanderveken's illocutionary theory of discourse and Asher and Lascarides SDRT approach. We are interested in formal frameworks that aim to describe the logical structure of conversations between diversely bounded agents who are — to some extent — rational, intelligent, linguistically competent and who possess some awareness of their environment and some knowledge of the circumstances of their interactions. We use the notion of closure conditions as a benchmark for theory comparison.

Linguistic and semantic annotations are important features for text-based applications. However, achieving and maintaining a good quality of a set of annotations is known to be a complex task. Many ad hoc approaches have been developed to produce various types of annotations, while comparing those annotations to improve their quality is still rare. In this paper, we propose a framework in which both linguistic and domain information can cooperate to reason with annotations. The underlying knowledge representation issues are carefully analyzed and solved by studying a higher order logic, which accounts for the cooperation of different sorts of knowledge. Our prototype implements this logic based on a reduction to classical description logics by preserving the semantics, allowing us to benefit from cutting-edge Semantic Web reasoners. An application scenario shows interesting merits of this framework on reasoning with annotations of texts.

In this paper, we present an image and text mining tool named TNT. This tool is based on Contextual Exploration and work on different points of view. It can process a corpus of all sizes in French or in English. The web interface associated with this tool, offers a reorganization of the text guided by the images and annotated segments that are associated.

In computer science, ontology is a model of a domain in the form of classes and of relationships between these classes. Classes are organized in a graph the arrows of which are semantic relations. Ontology is static because the class hierarchy is fixed. In paleontology, systematic (i.e., the class hierarchies and the class relationships) is complicated by the time variable. Morphological changes over time yield, by natural selection, the emergence of new forms (taxa) differing from the ancestral morph and contemporaneous taxa of the same class hierarchy. Discovering new taxa implies, therefore, the rearrangement of the class hierarchy or the definition of new classes, based on the degree of atypicality of the new morph. Note that this phenomenon occurs in many domains such as physics, biology, linguistics, for example.

We define sentence generalization and generalization diagrams as a special case of least general generalization (LGG) as applied to linguistic parse trees. Similarity measure between linguistic parse trees is developed as LGG operation on the lists of sub-trees of these trees. The diagrams introduced are representation of mapping between the syntactic generalization level and semantic generalization level. Generalization diagrams are intended as a framework to compute semantic similarity between texts relying on linguistic parse tree data. Such structured approach significantly improves text relevance assessment in a horizontal domain, where ontologies are not available

We introduce a search engine and information retrieval system for providing access to opinion data. Natural language technology of generalization of syntactic parse trees is introduced as a similarity measure between subjects of textual opinions to link them on the fly. Information extraction algorithm for automatic summarization of web pages in the format of Google sponsored links is presented. We outline the usability of the implemented system, integrated opinion delivery environment (IODE).

But each They are linked by an arrow which is labeled by discourse method for representing a context is quite different. Our relations R. We represent SDRS in the form of boxes like study is based on two representational methods of temporal DRS. To induce a temporal and hierarchical structure, relations: the Segmented Discourse Representation Theory SDRT distinguish discourse relations'coordinating' from (SDRT) and the model of Cognitive and Applicative'subordinating', therefore coordination and subordination Grammar (CAG). This paper presents a comparison of affect the temporal order of text: the former indicate a continuation these two approaches about aspect and tense by an analysis of some discourses pattern, like relations of'Narration' of relations between events. We are not going to show all or'Result' in discourse segmentation, and the later steps of SDRT's representations, but we take a simple discourse indicate with types of information like relations of'Elaboration' (Asher and Lascarides 2003) and we analyze the or'Explanation'. These relations are appeared same discourse with the framework of the CAG.

Agreement asymmetries are the most debated issue in Arabic linguistics. Even though the facts suggest a unified treatment based on the properties of agreement, most of the researchers in this field don’t take into account the essential difference between grammatical agreement and anaphoric agreement. We do propose such a distinction to explain these asymmetries and we propose an analysis that we implement in the ACCG framework.