Abstract: Aspects of the present disclosure include determining, by a processor, an ontology, the ontology comprising a plurality of ontological relationships, receiving, by the processor, a plurality of passages, determining, by the processor, a target set of co-occurring entities comprising a first entity and a second entity, determining a first passage in the plurality of passages that includes the first entity and the second entity, determining, from the ontology, a first ontological relationship between the first entity and the second entity, analyzing the first passage to determine a congruency score for the first ontological relationship, and generating a relationship annotation between the first entity and the second entity in the first passages based on the congruency score being within a threshold.

Abstract: Techniques for natural language processing based on user context include identifying a context of a user and responsive to receiving a request from the user intended for processing by a natural language processing (NLP) model, accounting for the context of the user in relation to the request. A result from the NLP model having accounted for the context of the user is provided.

Abstract: Embodiments include methods, system and computer program products for extracting attributes from embedded table structures in a document. Aspects include identifying a table in the document and identifying one or more headers of the table by locating co-occurring attributes in the table. Aspects also include identifying a plurality of values in the table and creating an annotation for each of the plurality of values value in the table, wherein each annotation includes text extracted from the one or more headers that correspond to the location of the value in the table.

Abstract: Techniques for natural language processing based on user context include identifying a context of a user and responsive to receiving a request from the user intended for processing by a natural language processing (NLP) model, accounting for the context of the user in relation to the request. A result from the NLP model having accounted for the context of the user is provided.

Abstract: Aspects of the present disclosure include determining, by a processor, an ontology, the ontology comprising a plurality of ontological relationships, receiving, by the processor, a plurality of passages, determining, by the processor, a target set of co-occurring entities comprising a first entity and a second entity, determining a first passage in the plurality of passages that includes the first entity and the second entity, determining, from the ontology, a first ontological relationship between the first entity and the second entity, analyzing the first passage to determine a congruency score for the first ontological relationship, and generating a relationship annotation between the first entity and the second entity in the first passages based on the congruency score being within a threshold.

Abstract: Examples described herein provide a computer-implemented method that includes performing a text analysis on unstructured text to identify a restriction associated with a subject. The method further includes identifying an environmental requirement associated with the subject based at least in part on the restriction. The method further includes identifying one or more devices associated with the subject based at least in part on the environmental requirement. The method further includes receiving data from the one or more devices. The method further includes determining device usage information based at least in part on the data. The method further includes determining a compliance of the subject to the restriction based at least in part on the device usage information. The method further includes, responsive to determining non-compliance of the subject, changing a function of the one or more devices.

Abstract: Methods, systems, and computer program products for auto-suggestion of expanded terms for concepts are provided. Aspects include analyzing, by a cognitive model, a seed dictionary to determine one or more concepts associated with the seed dictionary, determining a target ontology, analyzing, by the cognitive model, the target ontology to determine one or more expanded terms for each concept of the one or more concepts, determining, by the cognitive model, a confidence score for each of the one or more expanded terms, and updating the seed dictionary by associating the one or more expanded terms with a corresponding concept from the one or more concepts based at least in part on the confidence score exceeding a first threshold confidence score.

Abstract: An artifact identification engine identifies artifacts from structured and unstructured data in one or more documents based on pre-defined artifacts, by using cognitive annotations. The identified artifacts are analyzed based at least on received inputs. A cartridge that includes artifacts that are relevant to the structured and unstructured data is generated, based on the analyzing.

Abstract: Methods, systems, and computer program products for cognitive model modification are provided. Aspects include receiving a plurality of documents, receiving a cognitive model, identifying a set of cognitive model modification based on an alteration to the cognitive model, and for each cognitive model modification in the set of cognitive model modifications determining an updated concept or surface form based on each cognitive model modification, identifying one or more documents from the plurality of documents based on the updated concept or surface form, adding the one or more documents to a subset of documents, and generating an updated cognitive model based on one or more text analytics performed, by the cognitive model, on the subset of documents.

Abstract: Embodiments include methods, system and computer program products for extracting attributes from embedded table structures in a document. Aspects include identifying a table in the document and identifying one or more headers of the table by locating co-occurring attributes in the table. Aspects also include identifying a plurality of values in the table and creating an annotation for each of the plurality of values value in the table, wherein each annotation includes text extracted from the one or more headers that correspond to the location of the value in the table.

Abstract: An artifact identification engine identifies artifacts from structured and unstructured data in one or more documents based on pre-defined artifacts, by using cognitive annotations. The identified artifacts are analyzed based at least on received inputs. A cartridge that includes artifacts that are relevant to the structured and unstructured data is generated, based on the analyzing.