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: Summaries of entities (e.g., people, places, things, concepts, etc.) may provide additional useful information to user. For example, a search engine may provide a summary of an entity within search results. A category (e.g., “writer”, “politician”, etc.) of the entity that is short and concise may be advantageous to provide within a summary of the entity. The category may allow a user to quickly determine whether the information of the entity relates to the intended entity (e.g., search results of an entity as “a writer” vs. search results of an entity as “a politician”). Potential categories and summary text may be extracted from pre-labeled data. The potential categories and summary text may be intersected to determine a set of candidate categories that may be ranked. An entity category having a desired ranked may be determined as the entity category that describes the entity in a desired way.

Abstract: The present technology is related to identifying, from within a corpus of documents, a subject (e.g., person, location, date, etc.) that is relevant to a topic and that is usable to enhance a topic-describing document. Documents within the corpus of documents share a link structure, such that some documents include hyperlinks that enable navigation to the topic-describing document, and the topic-describing document includes hyperlinks that enable navigation to other documents. Text of documents within the corpus is parsed to identify the subject, and a context of the subject suggests a degree of relevance of the subject to the topic. An enhancement type of the subject is determined, and a version of the topic-describing document is enhanced to include a presentation of the subject.

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: Technologies are described herein for coreference resolution in an ambiguity-sensitive natural language processing system. Techniques for integrating reference resolution functionality into a natural language processing system can processes documents to be indexed within an information search and retrieval system. Ambiguity awareness features, as well as ambiguity resolution functionality, can operate in coordination with coreference resolution. Annotation of coreference entities, as well as ambiguous interpretations, can be supported by in-line markup within text content or by external entity maps. Information expressed within documents can be formally organized in terms of facts, or relationships between entities in the text. Expansion can support applying multiple aliases, or ambiguities, to an entity being indexed so that all of the possibly references or interpretations for that entity are captured into the index.

Abstract: Computer-readable media and a computer system for implementing a natural language search using fact-based structures and for generating such fact-based structures are provided. A fact-based structure is generated using a semantic structure, which represents information, such as text, from a document, such as a web page. Typically, a natural language parser is used to create a semantic structure of the information, and the parser identifies terms, as well as the relationship between the terms. A fact-based structure of a semantic structure allows for a linear structure of these terms and their relationships to be created, while also maintaining identifiers of the terms to convey the dependency of one fact-based structure on another fact-based structure. Additionally, synonyms and hypernyms are identified while generating the fact-based structure to improve the accuracy of the overall search.

Abstract: Concept disambiguation is provided for search queries by analyzing search results in conjunction with an ontology of concepts. An ontology of concepts is identified, and at least one document is associated with each concept. The document associated with a concept is representative of the concept and used to generate a concept signature. When a search query is received, it is processed to obtain search results. The search results are used to generate a search results signature, which is compared to the concept signatures to identify one or more concepts that are relevant to the search query.

Abstract: Referring expressions are identified for concepts by analyzing search query and result selection information. An ontology of concepts is identified, and at least one document is associated with each concept. The document associated with a concept is representative of the concept. Search query information from a search engine is analyzed to identify search queries that resulted in user selections of documents associated with the concepts. Referring expressions that refer to the concepts are identified based on the search queries that resulted in user selections of documents corresponding with the concepts. After identifying referring expressions for concepts, search queries may be mapped to referring expressions to identify concepts to which the search queries pertain, and search result pages may be generated based on knowledge of the concepts.

Abstract: Word sense probabilities are compressed for storage in a semantic index. Each word sense for a word is mapped to one of a number of “buckets” by assigning a bucket score to the word sense. A scoring function is utilized to assign the bucket scores that maximizes the entropy of the assigned bucket scores. Once the bucket scores have been assigned to the word senses, the bucket scores are stored in the semantic index. The bucket scores stored in the semantic index may be utilized to prune one or more of the word senses prior to construction of the semantic index. The bucket scores may also be utilized to prune and rank the word senses at the time a query is performed using the semantic index.

Abstract: Computer-readable media and a computing device are described for providing geotemporal search and a search interface therefor. A search interface having a location portion and a timeline portion is provided. A geographic area is selected in the location portion by adjusting the visible area of a map. A temporal window is selected in the timeline portion by adjusting sliders along a timeline to a desired start and end time. The start and end times can be in the past, present, or future. A geotemporal search is executed based on the selected geographic area and temporal window to identify search results having associated metadata indicating a relationship to the selected geographic area and temporal window. One or more search terms are optionally provided to further refine the geotemporal search.

Abstract: A role tree having nodes corresponding to semantic roles in a hierarchy is defined. A posting list is generated for each association of a term and a semantic role in the hierarchy. The posting lists are stored contiguously on a physical storage medium such that a subtree of the hierarchy of semantic roles can be loaded from the storage medium as a single contiguous block. The posting lists for a subtree of the hierarchy are retrieved by obtaining data identifying the beginning location on the physical storage medium of the posting lists for the term at the top of a desired subtree of the hierarchy and data identifying the length of the posting lists of the desired subtree of the hierarchy. A single contiguous block that includes the posting lists for the desired subtree of the hierarchy is then retrieved from the beginning location through the specified length.

Abstract: Computer-readable media, computerized methods, and computer systems for conducting semantic processes to present search results that include highlighted regions which are relevant to a conceptual meaning of a query are provided. Initially, content of document(s) is accessed and semantic representations are derived by distilling linguistic representations from the content. These semantic representations may be stored at a semantic index. Also, a proposition is derived from the query by parsing search terms of the query, and distilling the proposition from the search terms. Typically, the proposition is a logical representation of the conceptual meaning of the query. The proposition is compared against the semantic representations at the semantic index to identify a matching set. Regions of the content within the document, from which the matching set of semantic representations are derived, are targeted.

Abstract: Concept disambiguation is provided for search queries by analyzing search results in conjunction with an ontology of concepts. An ontology of concepts is identified, and at least one document is associated with each concept. The document associated with a concept is representative of the concept and used to generate a concept signature. When a search query is received, it is processed to obtain search results. The search results are used to generate a search results signature, which is compared to the concept signatures to identify one or more concepts that are relevant to the search query.

Abstract: Referring expressions are identified for concepts by analyzing search query and result selection information. An ontology of concepts is identified, and at least one document is associated with each concept. The document associated with a concept is representative of the concept. Search query information from a search engine is analyzed to identify search queries that resulted in user selections of documents associated with the concepts. Referring expressions that refer to the concepts are identified based on the search queries that resulted in user selections of documents corresponding with the concepts. After identifying referring expressions for concepts, search queries may be mapped to referring expressions to identify concepts to which the search queries pertain, and search result pages may be generated based on knowledge of the concepts.

Abstract: Summaries of entities (e.g., people, places, things, concepts, etc.) may provide additional useful information to user. For example, a search engine may provide a summary of an entity within search results. A category (e.g., “writer”, “politician”, etc.) of the entity that is short and concise may be advantageous to provide within a summary of the entity. The category may allow a user to quickly determine whether the information of the entity relates to the intended entity (e.g., search results of an entity as “a writer” vs. search results of an entity as “a politician”). Potential categories and summary text may be extracted from pre-labeled data. The potential categories and summary text may be intersected to determine a set of candidate categories that may be ranked. An entity category having a desired ranked may be determined as the entity category that describes the entity in a desired way.

Abstract: Technologies are described herein for generating a semantic translation rule to support natural language search. In one method, a first expression and a second expression are received. A first representation is generated based on the first expression, and a second representation is generated based on the second expression. Aligned pairs of a first term in the first representation and a second term in the second representation are determined. For each aligned pair, the first term and the second term are replaced with a variable associated with the aligned pair. Word facts that occur in both the first representation and the second representation are removed from the first representation and the second representation. The remaining word facts in the first representation are replaced with a broader representation of the word facts. The translation rule including the first representation, an operator, and the second semantic representation is generated.

Abstract: Tools and techniques are described that relate to iterators for applying term occurrence-level constraints in natural language searching. These tools may receive a natural language input query, and define term occurrence-level constraints applicable to the input query. The methods may also identify facts requested in the input query, and may instantiate an iterator to traverse a fact index to identify candidate facts responsive to the input query. This iterator may traverse through at least a portion of the fact index. The methods may receive candidate facts from this iterator, with these candidate facts including terms, referred to as term-level occurrences. The methods may apply the term occurrence-level constraints to the term-level occurrences. The methods may select the candidate fact for inclusion in search results for the input query, based at least in part on applying the term occurrence-level constraint.

Abstract: Computer-readable media and a computing device are described for providing geotemporal search and a search interface therefor. A search interface having a location portion and a timeline portion is provided. A geographic area is selected in the location portion by adjusting the visible area of a map. A temporal window is selected in the timeline portion by adjusting sliders along a timeline to a desired start and end time. The start and end times can be in the past, present, or future. A geotemporal search is executed based on the selected geographic area and temporal window to identify search results having associated metadata indicating a relationship to the selected geographic area and temporal window. One or more search terms are optionally provided to further refine the geotemporal search.

Abstract: The present technology is related to identifying, from within a corpus of documents, a subject (e.g., person, location, date, etc.) that is relevant to a topic and that is usable to enhance a topic-describing document. Documents within the corpus of documents share a link structure, such that some documents include hyperlinks that enable navigation to the topic-describing document, and the topic-describing document includes hyperlinks that enable navigation to other documents. Text of documents within the corpus is parsed to identify the subject, and a context of the subject suggests a degree of relevance of the subject to the topic. An enhancement type of the subject is determined, and a version of the topic-describing document is enhanced to include a presentation of the subject.