Per Anker Jensen

A Semantic Analysis of the English Genitive. Interaction of Lexical and Formal Semantics

Some earlier treatments of the semantics of the prenominal genitive assume two syntactic types for genitive NPs like the girls, one which combines with relational nouns like sister, and another that combines with non-relational nouns like car. In the former case the genitive relation is provided by the relational head noun, in the latter the source of the relation is taken to be provided by the utterance context. Our analysis uniformly assumes only one syntactic type for genitive NPs, viz., one that forces a genitive NP to combine only with relational nouns. In cases with inherently non-relational head nouns, such as the girls car, we hypothesize that the genitive NP coerces a shift of the meaning of the head noun so that it becomes relational. To determine the sort of meaning shift which is carried out, we appeal to the qualia structure of the lexical entry for the head noun. A consequence of this analysis is an extension of the area of lexically determined interpretations and a corresponding reduction of the context-determined, pragmatic area.

Content-based text querying with ontological descriptors

This paper describes a method and a system for content-based querying of texts based on the availability of an ontology for the concepts in the text domain. A key principle in the system is the extraction of conceptual content of noun phrases into descriptors forming an integral part of the ontology.The retrieval of text passages rests on matching descriptors from the text against descriptors from the noun phrases in the query. The match does not need to be exact but is mediated by the ontology invoking in particular taxonomic reasoning with sub- and super-concepts. The paper also reports on a prototype implementation of the system.

Ontological Extraction of Content for Text Querying

This paper describes a method and a system ONTOQUERY for content-based querying of texts based on the availability of an ontology for the concepts in the text domain. A key principle in the system is the extraction of conceptual content of noun phrases into descriptors forming an integral part of the ontology.The retrieval of text passages rests on matching descriptors from the text against descriptors from the noun phrases in the query. The match need not be exact but is mediated by the ontology, invoking in particular taxonomic reasoning with sub- and super concepts. The paper also reports on a prototype implementation of the system.

Ontology-Based Semantics for Prepositions

This paper addresses the elaboration of a relation-logical compositional semantics for the meaning content of nominals using formal ontologies as semantic domains. Prepositions are conceived as denoting binary semantic role relations between concepts in the ontology. The ontology comes with ontological affinities specifying the admissible ontological combinations. The key idea is to establish a many-many relation between lexical items and nodes in an ontology. This mapping is then systematically extended to phrases, appealing to a relational compositionality principle. The paper focuses on the semantics of prepositions and prepositional phrases, examining in particular disambiguation of nominal phrases containing multiple embedded prepositional phrases, utilizing the ontological affinities. Danish, which offers a rich system of prepositions, is used in the example material.

Conceptual Indexing of Text Using Ontologies and Lexical Resources

This paper describes an approach to indexing texts by their conceptual content using ontologies along with lexico-syntactic information and semantic role assignment provided by lexical resources. The conceptual content of meaningful chunks of text is transformed into conceptual feature structures and mapped into concepts in a generative ontology. Synonymous but linguistically quite distinct expressions are mapped to the same concept in the ontology. This allows us to perform a content-based search which will retrieve relevant documents independently of the linguistic form of the query as well as the documents.

ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora.

Conceptual Pathway Querying of Natural Logic Knowledge Bases from Text Bases

We describe a framework affording computation of conceptual pathways between a pair of terms presented as a query to a text database. In this framework, information is extracted from text sentences and becomes represented in natural logic, which is a form of logic coming much closer to natural language than predicate logic. Natural logic accommodates a variety of scientific parlance, ontologies and domain models. It also supports a semantic net or graph view of the knowledge base. This admits computation of relationships between concepts simultaneously through pathfinding in the knowledge base graph and deductive inference with the stored assertions. We envisage use of the developed pathway functionality, e.g., within bio-, pharma-, and medical sciences for calculating bio-pathways and causal chains.

Extracting conceptual feature structures from text

This paper describes the an approach to indexing texts by their conceptual content using ontologies. Central to this approach is a two-phase extraction principle divided into a syntactic annotation phase and a semantic generation phase drawing on lexico-syntactic information and semantic role assignment provided by existing lexical resources. Meaningful chunks of text are transformed into conceptual feature structures and mapped into concepts in a generative ontology. By this approach, synonymous but linguistically quite distinct expressions are extracted and mapped to the same concept in the ontology, providing a semantic indexing which enables content-based search.

The ontogram-approach to text processing and semantic relation spotting for indexing

This paper describes the OntoGram-approach to indexing texts by their conceptual content using ontologies along with syntactic grammars and lexico-syntactic information and semantic role assignment provided by lexical resources. The conceptual content of meaningful chunks of text is transformed into concept feature structures and mapped into concepts in a generative ontology. By this approach, synonymous but linguistically quite distinct expressions are mapped to the same concept in the ontology. This allows us to perform a content-based search which will retrieve relevant documents independently of the linguistic form of the query as well as the documents.

On the Relationship between a Computational Natural Logic and Natural Language

This paper makes a case for adopting appropriate forms of natural logic as target language for computational reasoning with descriptive natural language. Natural logics are stylized fragments of natural language where reasoning can be conducted directly by natural reasoning rules reflecting intuitive reasoning in natural language. The approach taken in this paper is to extend natural logic stepwise with a view to covering successively larger parts of natural language. We envisage applications for computational querying and reasoning, in particular within the life-sciences.