System and/or method for an autonomous linked managed semantic model based knowledge graph generation framework

1. A method comprising:

acquiring knowledge from one or more knowledge sources;

storing the acquired knowledge in a memory;

parsing a natural language query; and

in response to parsing the natural language query, accessing one or more electronic documents, the one or more electronic documents expressing a knowledge graph including a plurality of nodes expressed in the electronic document;

traversing the knowledge graph to detect an absence of detail sufficient to completely answer the parsed natural language query;

invoking an application program interface (API) to extract at least a portion of the stored acquired knowledge and create a managed semantic object to be included as a node in a modified knowledge graph in the one or more electronic documents, wherein:

the modified knowledge graph is capable of answering the natural language query based, at least in part, on the created managed semantic object, semantic labels generated with the created managed semantic object and an edge connecting the created managed semantic object to the modified knowledge graph;

the managed semantic object comprising:

a container, the container comprising:

one or more attributes relating the managed semantic object to a real-world object, the one or more attributes of the container to be determined based, at least in part, on the extracted at least a portion of the stored acquired knowledge, the one or more attributes of the container modelling behavior of the real-world object based, at least in part, on a statistical analysis of observations obtained from the extracted at least a portion of the stored acquired knowledge and enabling the managed semantic object to dynamically change relative to other elements in the modified knowledge graph based, at least in part, on the one or more attributes of the real-world object;

an indication of at least one of the one or more knowledge sources;

one or more linguistic rules associated with the real-world object;

at least one discovery objective to at least in part determine the acquired knowledge;

an indication of one or more sourcing methods associated with at least one of the one or more knowledge sources; and

evidence of an availability of content in the one or more knowledge sources according to a particular format.

2. The method of claim 1 , wherein the one or more attributes of the container to be determined based, at least in part, on tribal knowledge obtained from the one or more knowledge sources.

3. The method of claim 2 , and further comprising capturing the tribal knowledge as one or more annotations to a visual depiction of an item of knowledge.

4. The method of claim 3 , wherein the annotations are received in a text format, audio format, emoji format, image format or video format, or a combination thereof.

5. The method of claim 2 , wherein at least one of the one or more attributes of the container that relate the managed semantic object to the real-world object comprise one or more inferences based, at least in part, on one or more observed facts, the method further comprising determining the at least one of the one or more attributes of the container based, at least in part, on a computed degree of corroboration of the one or more observed facts with the tribal knowledge.

6. The method of claim 1 , wherein at least one of the one or more knowledge sources comprises one or more sensors.

7. The method of claim 1 , wherein the acquired knowledge is obtained based, at least in part, on at least one discovery objective.

8. The method of claim 1 , and wherein:

the acquired knowledge is based, at least in part, on one or more items of evidence; and

the container further comprises an indication of confidence in one or more inferences regarding the acquired knowledge, the indication of confidence being computed based, at least in part, on one or more semantic expressions observed in the one or more items of evidence.

9. The method of claim 8 , and wherein the confidence in the one or more inferences regarding the acquired knowledge is further based, at least in part, on one or more observations of evidence expressed in the managed semantic object.

10. The method of claim 1 , wherein creating the managed semantic object further comprises sampling the acquired knowledge according to a sampling methodology, and wherein the container further comprises an indication of the sampling methodology.

11. The method of claim 1 , wherein creating the managed semantic object further comprises transforming the acquired knowledge to a particular format.

12. The method of claim 1 , and wherein the container further comprises an indication of statistics regarding at least one aspect of the acquired knowledge.

13. The method of claim 1 , and wherein the container further comprises an indication of natural language descriptors of the real-world object.

14. A method comprising:

acquiring knowledge from one or more knowledge sources;

storing the acquired knowledge in a memory;

parsing a natural language query;

in response to parsing the natural language query,

accessing one or more electronic documents, the one or more electronic documents expressing a knowledge graph including a plurality of nodes expressed in the one or more electronic documents;

traversing the knowledge graph to detect an absence in the knowledge graph of sufficient detail to completely answer the parsed natural language query; and

responsive to detecting the absence in the knowledge graph of sufficient detail to completely answer the parsed natural language query, creating a managed semantic object via an application program interface (API), the created managed semantic object to be included as a node in a modified knowledge graph expressed in the accessed one or more electronic documents, the managed semantic object comprising:

a container comprising one or more attributes relating the managed semantic object to a real-world object, the one or more attributes of the container to be determined based, at least in part, on the stored acquired knowledge, wherein:

the one or more attributes of the container relate the managed semantic object to one or more attributes of the real-world object, the one or more attributes of the container to model behavior of the real-world object based, at least in part, on a statistical analysis of observations obtained from the stored acquired knowledge and to enable the managed semantic object to dynamically change relative to other elements in the modified knowledge graph based, at least in part, on the one or more attributes of the real-world object;

the created managed semantic object enables the modified knowledge graph to at least partially answer the parsed natural language query; and

the parsed natural language query is answerable based, at least in part, on semantic labels associated with the created managed semantic object and an edge connecting the created managed semantic object to the modified knowledge graph.

15. The method of claim 14 , wherein creating the managed semantic object further comprises:

determining a discovery objective based, at least in part, on the natural language query; and

obtaining the acquired knowledge based, at least in part, on the discovery objective.

16. The method of claim 14 , and further comprising connecting the created managed semantic object to an existing managed semantic object in the modified knowledge graph by an edge, wherein semantic labels associated with the created managed semantic object, the existing managed semantic object and the edge define a relationship between the created managed semantic object and the existing managed semantic object.

17. An article comprising:

a non-transitory storage medium, the non-transitory storage medium comprising stored thereon, instructions executable by one or more processors of a computer device to:

acquire knowledge from one or more knowledge sources;

store the acquired knowledge in a memory;

parse a natural language query; and

in response to parsing the natural language query,

access one or more electronic documents, the one or more electronic documents expressing a knowledge graph including a plurality of nodes expressed in the electronic document;

traverse the knowledge graph to detect an absence of detail sufficient to completely answer the parsed natural language query;

invoke an application program interface (API) to extract at least a portion of the stored acquired knowledge and create a managed semantic object, wherein:

the created managed semantic object is included as a node in a modified knowledge graph expressed in the one or more electronic documents;

the modified knowledge graph is capable of answering the natural language query based, at least in part, on the created managed semantic object, semantic labels generated with the created managed semantic object and an edge connecting the created managed semantic object to the modified knowledge graph; and the managed semantic object comprises:

a container comprising one or more attributes relating the managed semantic object to a real-world object, the one or more attributes of the container to be based, at least in part, on acquired knowledge obtained from one or more knowledge sources, wherein:

the one or more attributes of the container relate the managed semantic object to one or more attributes of the real-world object, the one or more attributes of the container to model behavior of the real-world object based, at least in part, on a statistical analysis of observations obtained from the acquired knowledge and to enable the managed semantic object to dynamically change relative to other elements in the knowledge graph based, at least in part, on the one or more attributes of the real-world object; and

the container further comprises:

an indication of at least one of the one or more knowledge sources;

one or more linguistic rules associated with the real-world object;

at least one discovery objective to at least in part determine the acquired knowledge;

an indication of one or more sourcing methods associated with at least one of the one or more knowledge sources; and

evidence of an availability of content in the one or more knowledge sources according to a particular format.

18. An apparatus comprising:

one or more processors to:

acquire knowledge from one or more knowledge sources;

store the acquired knowledge in memory;

parse a natural language query; and

in response to the parsed natural language query,

access one or more electronic documents, the accessed one or more electronic documents expressing a knowledge graph including a plurality of nodes expressed in the one or more electronic documents;

traverse the knowledge graph to detect an absence in the knowledge graph of at least one node or managed semantic object sufficient to answer the natural language query;

invoke an application program interface (API) to extract at least a portion of the stored acquired knowledge and create a managed semantic object, wherein the created managed semantic object is included as a node in a modified knowledge graph expressed in the one or more electronic documents;

the managed semantic object enabling the modified knowledge graph to answer the parsed natural language query, the managed semantic object comprising:

a container comprising one or more attributes relating the managed semantic object to a rea-world object, the one or more attributes of the container to be determined based, at least in part, on the extracted at least a portion of knowledge, wherein:

the one or more attributes of the container relate the managed semantic object to one or more attributes of the real-world object, the one or more attributes of the container to model behavior of the real-world object based, at least in part, on a statistical analysis of observations obtained from the extracted at least portion of knowledge and enables the managed semantic object to dynamically change relative to other elements in the modified knowledge graph based, at least in part, on the one or more attributes of the real-world object; and

the parsed natural language query is answered based, at least in part, on the created managed semantic object, semantic labels generated with the managed semantic object and an edge connecting the created managed semantic object to the modified knowledge graph.

19. The apparatus of claim 18 , wherein the one or more attributes of the container to be determined based, at least in part, on tribal knowledge obtained from the one or more knowledge sources.

20. The apparatus of claim 18 , wherein the one or more processors are further to:

capture tribal knowledge as one or more annotations to a visual depiction of an item of knowledge, the visual depiction of the item of knowledge to be based, at least in part, on the knowledge graph; and

update the knowledge graph based, at least in part, on the one or more annotations to the visual depiction.

21. The apparatus of claim 20 , and further comprising one or more input devices to receive at least some of the one or more annotations in a text format, audio format, emoji format, image format or video format, or a combination thereof.