International Business Machines Corporation

Christopher F Ackermann

Charles Evan Beller

Kristen Maria Summers

Michael Drzewucki

Edward Graham Katz

Stephen Arthur Boxwell

Stanley John Vernier

Rob High

Andrew Doyle

Donna Karen Byron

David McQuenney

William G Dubyak

Nicole O'Connor

David McQueeney

The method provides for receiving a plurality of documents including mentions of a target entity from a search query about the entity. The mentions of the target entity are identified in respective documents of the plurality of documents. Content surrounding the one or more mentions of the target entity are extracted with the mentions within the respective documents and form section. A respective document includes a plurality of sections. Metrics of relevance and irrelevance to the target entity are determined within the plurality of sections of the respective documents. A density score is generated for the plurality of sections of the respective documents. A relevancy score is assigned to respective documents of the plurality of documents, based on the density scores of the sections of the respective documents. The documents are ranked based on the relevancy score and presented in an order based on the ranking.

Ranking entity search results based on information density

Provided are a method, system, and computer program product in which operations are performed to receive a question that includes a descriptor and an indication that indicates that a unique answer to the question is expected. A determination is made of instances of matching descriptors and descriptor targets from a set of documents. The determined descriptor targets are compared for consistency. In response to determining that the determined descriptor targets are inconsistent, more restrictive descriptors are iteratively generated via a selection model based on metadata associated with the question until the descriptor targets are consistent. An answer to the question is returned from consistent descriptor targets.

Identification of restrictors to form unique descriptions for generation of answers to questions

A computer device receives a request to search a corpus of documents for an entity, wherein the request includes a non-name identifier of the entity. The computing device identifies entries of text within the corpus of documents that reference the non-name identifier. The computing device applies natural language processing (NLP) to content associated with the identified entries within the corpus of documents, wherein the NLP identifies candidate entities associated with the non-name identifier. The computing device selects an entity from the candidate entities based, at least in part, on distances between the candidate entities and references to the non-name identifier in the identified entries. The computing device returns the selected entity to a submitter of the request.

Entity search system

Embodiments relate to an intelligent computer platform to selectively amend one or more document elements. A first document is subjected to natural language processing (NLP) and two or more document characteristics are subjected to an assessment to produce a characteristic value. The document characteristics and corresponding characteristic values are analyzed to produce a characteristic profile for each identified document characteristic. Upon receipt of a new document, document characteristic data and corresponding characteristic value(s) are identified. The corresponding characteristic value(s) of the new document is applied against the produced characteristic profile. New document characteristic data is selectively amended responsive to the comparison, and a new document version is created from the selective amendment.

Removal of personality signatures

A mechanism is provided in a data processing system to implement a cognitive natural language processing (NLP) system with descriptor uniqueness identification to support named entity mention clustering. The mechanism annotates a set of documents from a corpus of documents for entity types and mentions, collects descriptor usages from all documents in the corpus of documents, analyzes the descriptor usages to classify the descriptors as base terms or modifier terms, generates compatibility scores for the descriptors, and performs entity merging of entity clusters based on the compatibility scores.

Descriptor uniqueness for entity clustering

Approaches presented herein enable presenting, as an initial response to a search query from a user, a set of analytic summaries prior to initiating a document security protocol in a secured document environment. Each analytic summary represents a set or cluster of documents. A summary relevance value is calculated for each analytic summary and a document relevance value is calculated for each individual document. Analytic summaries are presented to the user while each document within each analytic summary are prioritized for a security review based on its related summary relevance value and document relevance value. Based on the priorities, a security review is initiated for the documents so that a highly relevant document within an analytic summary undergoes the security review before a less relevant document. Access to a particular document is granted to the user according to the security review of the document.

Tiered retrieval of secured documents

A system and a method for determining user synonyms in a query processing system is disclosed. A first query is received from a user of the query processing system. The query is processed through the query processing system to generate results for the first query. The user then provides a second query. The system determines a contextual similarity between the first query and the second query. When the first query and the second query are determined to be contextually similar, a first term is identified in the first query that is different from a second term in the second query. Once identified, the system determines if the first term and the second term are not listed as synonyms in the thesaurus. If they are not listed as synonyms they can be added as synonyms to the thesaurus.

Learning user synonyms from sequenced query sessions

An embodiment for extracting information from semi-structured text is provided. The embodiment may include identifying one or more high confidence alignments of one or more entities and identifiers in a set of documents. The embodiment may also include analyzing one or more blocks of semi-structured text containing the one or more entities and identifiers. The embodiment may further include identifying one or more known alignments in each of the one or more blocks of semi-structured text. The embodiment may also include generating a structure template. The embodiment may further include applying the structure template to each of the one or more blocks of semi-structured text. The embodiment may also include annotating the set of documents with metadata reflecting the structure template and a location of each of the one or more blocks of semi-structured text.

Flexible pseudo-parsing of dense semi-structured text

Embodiments relate to an intelligent computer platform to selectively amend one or more tokens in a document. A first document set is subjected to natural language processing (NLP) and a vector score is identified for two or more documents of the first document set. Upon receipt of a new document, the new document is subjected to NLP and a new document vector score is identified. The new document is analyzed against the first document set, and the identified vector score of the first document set is compared to the vector score of the new document. One or more tokens of the new document are amended responsive to the comparison, and a new document version is created from the selective amendment.

Document anonymization including selective token modification

Embodiments for identifying entities relevant to queries are provided. At least one query is received from a user. The at least one query is associated with at least one entity. Results of the at least one query are analyzed to identify related entities. The related entities are analyzed based on a relevancy score and an information enhancement score for each of the related entities to generate a ranking of the related entities. At least one of the related entities is provided to the user based on the ranking of the related entities.

Methods and systems for providing suggestions to complete query sessions

Embodiments for generating a timeline associated with an entity are provided. A plurality of events referenced in a corpus are identified. Each of the plurality of events is associated with an entity. An event time is determined for each of the plurality of events based on information associated with at least one reference to the respective event within the corpus. A score is calculated for each of the plurality of events based on at least one of a number of references to the respective event within the corpus and information associated with a user. A timeline for at least some of the plurality of events is generated based on the calculated scores of the plurality of events and the determined event time for each of the plurality of events.

Methods and systems for generating timelines for entities

The present invention may receive the question, a plurality of the candidate answers, and a plurality of documents associated with the plurality of candidate answers in the natural language. Then the present invention may tokenize the question, the plurality of the candidate answers, and the plurality of the documents into a corresponding n-gram sequence. The present invention may map n-gram elements from the tokenized question to the n-gram elements of the plurality of the tokenized candidate answers and the plurality of the tokenized documents using the latent token representation technique. The present invention may score the plurality of tokenized candidate answers based on the latent token representation technique. Then, the present invention may determine the precise answer based on the plurality of scored candidate answers.

Latent token representations for passage and answer scoring in question answering systems

Query service receives a query comprising at least a name component. The query service searches a document corpus to identify multiple passages, each comprising a mention of the name component within a selection of one or more documents of the document corpus. The query service collects bins, each bin comprising a distinct selection of the passages from the one or more documents, each of the bins identifying a separate relationship the name component participates in within the distinct selection of passages. The query service assesses a separate score of each respective bin reflecting the relevance of each respective bin to the query. The query service returns a response to the query with the bins each ranked according to each separate score.

Ranking collections of document passages associated with an entity name by relevance to a query

Embodiments for generating descriptions of entities are provided. A plurality of references to an entity within a corpus are identified. The corpus includes a plurality of documents. Descriptors for the entity are extracted from portions of the plurality of documents associated with the plurality of references to the entity. A score for each of the descriptors is calculated based on at least one of a location of the reference associated with the descriptor within the respective document and a location of the descriptor within the respective document. A description of the entity is generated utilizing at least some of the descriptors based on said calculated scores.

Methods and systems for generating descriptions utilizing extracted entity descriptors

Identifying alternative names of entities includes receiving a query associated with a name of an entity and a corpus. References to the name of the entity within the corpus are identified. The references to the name of the entity within the corpus are analyzed to determine at least one first alternative name of the entity. References to the determined at least one first alternative name of the entity within the corpus are identified. The references to the determined at least one first alternative name of the entity within the corpus are analyzed to determine at least one second alternative name of the entity.

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Fairfax Station, VA, United States of America

Christopher F Ackermann