Abstract: The present invention provides a facility for determining, for a semantic relation that does not occur in a lexical knowledge base, whether this semantic relation should be inferred despite its absence from the lexical knowledge base. This semantic relation to be inferred is preferably made up of a first word, a second word, and a relation type relating the meanings of the first and second words. In a preferred embodiment, the facility identifies a salient semantic relation having the relation type of the semantic relation to be inferred and relating the first word to an intermediate word other than the second word. The facility then generates a quantitative measure of the similarity in meaning between the intermediate word and the second word. The facility further generates a confidence weight for the semantic relation to be inferred based upon the generated measure of similarity in meaning between the intermediate word and the second word.

Abstract: The present invention provides a facility for determining similarity between two input words utilizing the frequencies with which path patterns occurring between the words occur between words known to be synonyms. A preferred embodiment of the facility utilizes a training phase and a similarity determination phase. In the training phase, the facility first identifies, for a number of pairs of synonyms, the most salient semantic relation paths between each pair of synonyms. The facility then extracts from these semantic relation paths their path patterns, which each comprise a series of directional relation types. The number of times that each path pattern occurs between pairs of synonyms, called the frequency of the path pattern, is counted. In the training phase, the facility identifies the most salient semantic relation paths between the input words, and extracts their path patterns.

Abstract: The present invention is directed to performing information retrieval utilizing semantic representation of text. In a preferred embodiment, a tokenizer generates from an input string information retrieval tokens that characterize the semantic relationship expressed in the input string. The tokenizer first creates from the input string a primary logical form characterizing a semantic relationship between selected words in the input string. The tokenizer then identifies hypernyms that each have an "is a" relationship with one of the selected words in the input string. The tokenizer then constructs from the primary logical form one or more alternative logical forms. The tokenizer constructs each alternative logical form by, for each of one or more of the selected words in the input string, replacing the selected word in the primary logical form with an identified hypernym of the selected word. Finally, the tokenizer generates tokens representing both the primary logical form and the alternative logical forms.

Abstract: The present invention identifies salient semantic relation paths between two words using a knowledge base. For a group of semantic relations occurring in the knowledge base, the facility models with a mathematical function the relation between a frequency of occurrence of unique semantic relations and the number of unique semantic relations that occur at that frequency. This mathematical function has a vertex frequency identifying a transition point in the mathematical function. The facility then determines the level of salience of unique semantic relations of the group such that the level of salience of unique semantic relations increases with the frequency of occurrence of the unique semantic relations approaches the vertex frequency of the mathematical function with which the relation between the frequency of occurrence of the unique semantic relations and the number of unique semantic relations occurring at that frequency is modeled.