Abstract: Methods and systems for indexing document passages are presented. In some embodiments, a computing device may identify a plurality of documents that comprise a plurality of passages. A passage index comprising a plurality of entries may be generated. Each entry may comprise keywords from a passage of the plurality of passages in one of the plurality of documents. Each entry may further comprise at least one annotation associated with the passage. A search query comprising at least one search keyword may be received. The passage index for each document of the plurality of documents may be analyzed using the at least one search keyword to identify at least one passage from the plurality of documents that matches the search query. In response to the query, the at least one passage may be presented.

Abstract: Methods and computer-readable media for associating words or groups of words distilled from content, such as reported speech or an attitude report, of a document to form semantic relationships collectively used to generate a semantic representation of the content are provided. Semantic representations may include elements identified or parsed from a text portion of the content, the elements of which may be associated with other elements that share a semantic relationship, such as an agent, location, or topic relationship. Relationships may also be developed by associating one element that is in relation to, or is about, another element, thereby allowing for rapid and effective comparison of associations found in a semantic representation with associations derived from queries. The semantic relationships may be determined based on semantic information, such as potential meanings and grammatical functions of each element within the text portion of the content.

Abstract: Methods and systems for indexing document passages are presented. In some embodiments, a computing device may identify a plurality of documents that comprise a plurality of passages. A passage index comprising a plurality of entries may be generated. Each entry may comprise keywords from a passage of the plurality of passages in one of the plurality of documents. Each entry may further comprise at least one annotation associated with the passage. A search query comprising at least one search keyword may be received. The passage index for each document of the plurality of documents may be analyzed using the at least one search keyword to identify at least one passage from the plurality of documents that matches the search query. In response to the query, the at least one passage may be presented.

Abstract: Methods and computer-readable media for associating words or groups of words distilled from content, such as reported speech or an attitude report, of a document to form semantic relationships collectively used to generate a semantic representation of the content are provided. Semantic representations may include elements identified or parsed from a text portion of the content, the elements of which may be associated with other elements that share a semantic relationship, such as an agent, location, or topic relationship. Relationships may also be developed by associating one element that is in relation to, or is about, another element, thereby allowing for rapid and effective comparison of associations found in a semantic representation with associations derived from queries. The semantic relationships may be determined based on semantic information, such as potential meanings and grammatical functions of each element within the text portion of the content.

Abstract: Methods and computer-readable media for associating words or groups of words distilled from content, such as reported speech or an attitude report, of a document to form semantic relationships collectively used to generate a semantic representation of the content are provided. Semantic representations may include elements identified or parsed from a text portion of the content, the elements of which may be associated with other elements that share a semantic relationship, such as an agent, location, or topic relationship. Relationships may also be developed by associating one element that is in relation to, or is about, another element, thereby allowing for rapid and effective comparison of associations found in a semantic representation with associations derived from queries. The semantic relationships may be determined based on semantic information, such as potential meanings and grammatical functions of each element within the text portion of the content.

Abstract: Methods, systems and computer readable media for finding documents in a data store that match a natural language query submitted by a user are provided. The documents and queries are matched by determining that words within the query have the same relationship to each other as the same words in the document. Documents are semantically analyzed and words in the document are indexed along with the role the word plays in a sentence. The initial semantic role may be generalized using a role hierarchy and stored in the index along with the original role. A similar analysis may be used with the search query to find words used in the same role in both the query and the document.

Abstract: Techniques are provided for segmenting text into categorized discourse constituents and attaching discourse constituents into a structural representation of discourse. Techniques for determining hybrid structural and non-structural summaries of a text are also provided. A text is segmented based on a theory of discourse analysis into at least a main discourse constituent containing spatio-temporal information about a single event in a possible world view. The discourse constituents are then inserted into a structural representation of discourse. Non-structural techniques are used to determine relevance scores and important discourse constituents are determined. Relevance scores are percolated through the structural representation of discourse to determine supporting preceding discourse constituents that preserve grammaticality. A hybrid text summary is then determined based on the structural representation of the discourse and relevance scores.

Abstract: Computer-readable media and computer systems for conducting semantic processes to facilitate navigation of search results that include sets of tuples representing facts associated with content of documents in response to queries for information. Content of documents is accessed and semantic structures are derived by distilling linguistic representations from the content. Groups of two or more related words, called tuples, are extracted from the documents or the semantic structures. Tuples can be stored at a tuple index. Representations of the relational tuples are displayed in addition to documents retrieved in response to a query.

Abstract: Methods, systems and computer readable media for finding documents in a data store that match a natural language query submitted by a user are provided. The documents and queries are matched by determining that words within the query have the same relationship to each other as the same words in the document. Documents are semantically analyzed and words in the document are indexed along with the role the word plays in a sentence. The initial semantic role may be generalized using a role hierarchy and stored in the index along with the original role. A similar analysis may be used with the search query to find words used in the same role in both the query and the document.

Abstract: Methods and computer-readable media for associating words or groups of words distilled from content, such as reported speech or an attitude report, of a document to form semantic relationships collectively used to generate a semantic representation of the content are provided. Semantic representations may include elements identified or parsed from a text portion of the content, the elements of which may be associated with other elements that share a semantic relationship, such as an agent, location, or topic relationship. Relationships may also be developed by associating one element that is in relation to, or is about, another element, thereby allowing for rapid and effective comparison of associations found in a semantic representation with associations derived from queries. The semantic relationships may be determined based on semantic information, such as potential meanings and grammatical functions of each element within the text portion of the content.

Abstract: Techniques are provided for detecting entailment and contradiction. Packed knowledge representations for a premise and conclusion text are determined comprising facts about the relationships between concept and/or context denoting terms. Concept and context alignments are performed based on alignments scores. A union is determined. Terms are marked as to their origin and conclusion text terms replaced with by corresponding terms from the premise text. Subsumption and specificity, instantiability, spatio-temporal and relationship based packed rewrite rules are applied in conjunction with the context denoting facts to remove entailed terms and to mark contradictory facts within the union. Entailment is indicated by a lack of any facts from the packed knowledge representation of the conclusion in the union. Entailment and contradiction markers are then displayed.

Abstract: Techniques managing syntactic and semantic ambiguity allow two different kinds of processing and representation of ambiguity to work together. The techniques allow linear logic semantic assembly to work with packed functional (f) structures and provide for contexted version of linear logic where semantic contributions are read from the packed functional (f) structure and pre-pended with the contents of the functional (f) structure to which they pertain. Linear logic reasoning may then be performed in the contexted linear logic to derive possible meanings from the contexted contributions from the packed functional (f) structure. Deductions in the contexted linear logic do not require fully expanding each syntactic parse. Techniques applying skeleton/modifier techniques to contexted reasoning are provided by creating a contexted modifier applicable only for certain syntactic readings.

Abstract: Techniques are provided for determining grammatical condensed text structures. Packed structures are determined for text structures based on a parsing grammar. Reduced packed structures are determined by applying transformation rules to packed and/or unpacked elements of the packed structures. A disambiguation model is applied to the reduced packed structure to determine candidate structures. A grammatically correct generation grammar is applied to the candidate structures to determine grammatical condensed text structures.

Abstract: Techniques managing syntactic and semantic ambiguity allow two different kinds of processing and representation of ambiguity to work together. The techniques allow linear logic semantic assembly to work with packed functional (f) structures and provide for contexted version of linear logic where semantic contributions are read from the packed functional (f) structure and pre-pended with the contents of the functional (f) structure to which they pertain. Linear logic reasoning may then be performed in the contexted linear logic to derive possible meanings from the contexted contributions from the packed functional (f) structure. Deductions in the contexted linear logic do not require fully expanding each syntactic parse. Techniques applying skeleton/modifier techniques to contexted reasoning are provided by creating a contexted modifier applicable only for certain syntactic readings.