Thomson Reuters Global Resources Unlimited Company

Thomson Reuters Global Resources

Thomson Reuters Enterprise Centre Gmbh

Refinitiv US Organization LLC

Thornson Reuters Global Resources Unlimited Company

Frank Schilder

Dezhao Song

Blake Howald

Thomas W Vacek

Ravi Kumar Kondadadi

Tim Nugent

Ronald Teo

Conner Cowling

Christopher Dozier

Thomas Vacek

Jochen Lothar Leidner

James Shaw

Hugo Molina-Salgado

Charese Smiley

Christopher Hardie Brew

Don Teo

Daniel F Salas

Summit Chaudhuri

Damien Frennet

Peenaki Dam

Sarah L Andrews

Ricardo Rodriguez

Ashok Ganapam

Christopher Brew

The present disclosure relates to systems and methods for analyzing and extracting data related to a structured proceeding, and for identifying, based on the analysis, at least one outcome associated with the structured proceeding. Embodiments provide for receiving data associated with a structured proceeding involving at least one party, the data including at least one docket entry, and analyzing, by an outcome location detector, the data to identify one or more docket entries in the at least one docket entry that are likely to include evidence of an outcome. Embodiments further include analyzing, by an outcome detector, the one or more docket entries determined to be likely to include evidence of an outcome to determine outcomes. The outcomes include at least one of a final outcome and at least one party outcome. The final outcome is associated with the structured proceeding overall, and the at least one party outcome is associated with a party of the at least one party that may have been terminated early.

Systems and methods for determining structured proceeding outcomes

The present disclosure relates to systems and methods for analyzing and extracting docket data related to a structured proceeding, for identifying docket entries associated with motions and docket entries associated with orders, and for identifying motions affected by orders. Embodiments provide for receiving docket data associated with a structured proceeding, the docket data including at least one docket entry. Embodiments also include identifying, by an automated analysis, docket entries associated with motions in the structured proceeding, and docket entries associated with orders in the structured proceeding. In embodiments, identifying the docket entries associated with orders includes identifying at least one order that includes a results-affecting decision affecting at least one motion. Embodiments further include linking, by the automated analysis, the affected at least one motion to the affecting order.

Systems and methods for identifying and linking events in structured proceedings

A computer implemented method for mining risks includes providing a set of risk-indicating patterns on a computing device; querying a corpus using the computing device to identify a set of potential risks by using a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with the corpus; comparing the set of potential risks with the risk-indicating patterns to obtain a set of prerequisite risks; generating a signal representative of the set of prerequisite risks; and storing the signal representative of the set of prerequisite risks in an electronic memory. A computing device or system for mining risks includes an electronic memory; and a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with a corpus stored in the electronic memory.

Method and apparatus for risk mining

A computing system can receive a request to apply semantic token tagging on a specified domain, and can retrieve a set of data associated with the specified domain from a data storage facility. Canonical sequences can be formed from strings included in the data set. Each canonical sequence can be permutated to form sequence variations and each sequence variation can be verified against a generalized domain. Semantic token tagging can be applied to the specified domain using a subset of the sequence variations that are successfully verified as training data.

Systems and methods for automatic semantic token tagging

The present invention provides an improved docket search and analytics engine for determining the outcome of a case for a particular entity or party, for predicting the outcome of a case for a particular entity or party, or for predicting the time to resolution of a case for a particular entity or party. More specifically, the present invention provides a system and engine for accessing and retrieving docket and other data from a plurality of databases and applying by one or more engines a set of models to the retrieved data to make a determination or prediction as to the outcome of a case for an entity or party involved in the case.

Docket search and analytics engine

The present invention is directed towards systems and methods for querying a data repository using a flexible natural language interface, which comprises receiving an initiated user question at a graphical user interface and generating automatically one or more suggested completed questions in response to the receipt of the initiated user question. A selected completed question at the graphical user interface is received and subsequently parsed into a logic representation. The logic representation is translated into an executable query, which is executed against the data repository. One or more search results in response to the executed translated query and presented at the graphical user interface. The present invention further comprises generating one or more analytic results corresponding to the one or more search responsive to the translated query.

Systems and methods for natural language question answering and analysis

The present invention relates to a system and method for bootstrapping templates for use in natural language sentence generation. More specifically, the present invention relates to identifying a set of candidate sentences from a large corpus based on a set of original templates by using a similarity measure. The set of candidate sentences are then processed or cleaned to generate a set of templates for use in natural language sentence generation.

Template bootstrapping for domain-adaptable natural language generation

For automated text processing, the inventors devised, among other things, an exemplary system that automatically extracts financial events from various unstructured text based sources, such as press releases and news articles. Extracted events, such as mergers & acquisitions, earnings guidance reports, and actual earnings announcements, are represented as structured data records which can be linked, searched, and displayed and used as a basis for controlling accessing to the source documents and other related financial documents for named entities.

Financial event and relationship extraction

A method includes receiving a corpus comprising a set of pre-segmented texts. The method further includes creating a plurality of modified pre-segmented texts for the set of pre-segmented texts by extracting a set of semantic terms for each pre-segmented text within the set of pre-segmented texts and applying at least one domain tag for each pre-segmented text within the set of pre-segmented texts. The method further includes clustering the plurality of modified pre-segmented texts into one or more conceptual units, wherein each of the one or more conceptual units is associated with one or more templates, wherein each of the one or more templates corresponds to one of the plurality of modified pre-segmented texts.

Systems and methods for natural language generation

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Saint Paul, MN, United States of America

Frank Schilder