Abstract: Methods and apparatus to facilitate annotation projects to extract structured information from free-form text using NLP techniques. Annotators explore text documents via automated preannotation functions, flexibly formulate annotation schemes and guidelines, annotate text, and adjust annotation labels, schemes and guidelines in real-time as a project evolves. NLP models are readily trained on iterative annotations of sample documents by domain experts in an active learning workflow. Trained models are then employed to automatically annotate a larger body of documents in a project dataset. Experts in a variety of domains can readily develop an annotation project for a specific use-case or business question. In one example, documents relating to the health care domain are effectively annotated and employed to train sophisticated NLP models that provide valuable insights regarding many facets of health care.

Abstract: Cable designs and methods are provided herein to enable remote end access to active cable controllers for monitoring and upgrade operations. One illustrative network cable design includes: a first end connector configured to couple with a first host port and a second end connector configured to couple with a second host port, each of the first and second end connectors configured to convey a data stream in each direction via optical or electrical conductors connected between the first and second end connectors; a controller and a powered transceiver circuit included in the first end connector, the controller operable to configure operation of the powered transceiver circuit; and electrical contacts in the second end connector for a management bus to convey information from the second host port to the controller in the first end connector.

Abstract: Methods and apparatus to facilitate annotation projects to extract structured information from free-form text using NLP techniques. Annotators explore text documents via automated preannotation functions, flexibly formulate annotation schemes and guidelines, annotate text, and adjust annotation labels, schemes and guidelines in real-time as a project evolves. NLP models are readily trained on iterative annotations of sample documents by domain experts in an active learning workflow. Trained models are then employed to automatically annotate a larger body of documents in a project dataset. Experts in a variety of domains can readily develop an annotation project for a specific use-case or business question. In one example, documents relating to the health care domain are effectively annotated and employed to train sophisticated NLP models that provide valuable insights regarding many facets of health care.

Abstract: Cable designs and methods are provided herein to enable remote end access to active cable controllers for monitoring and upgrade operations. One illustrative network cable design includes: a first end connector configured to couple with a first host port and a second end connector configured to couple with a second host port, each of the first and second end connectors configured to convey a data stream in each direction via optical or electrical conductors connected between the first and second end connectors; a controller and a powered transceiver circuit included in the first end connector, the controller operable to configure operation of the powered transceiver circuit; and electrical contacts in the second end connector for a management bus to convey information from the second host port to the controller in the first end connector.

Abstract: Methods and apparatus to facilitate annotation projects to extract structured information from free-form text using NLP techniques. Annotators explore text documents via automated preannotation functions, flexibly formulate annotation schemes and guidelines, annotate text, and adjust annotation labels, schemes and guidelines in real-time as a project evolves. NLP models are readily trained on iterative annotations of sample documents by domain experts in an active learning workflow. Trained models are then employed to automatically annotate a larger body of documents in a project dataset. Experts in a variety of domains can readily develop an annotation project for a specific use-case or business question. In one example, documents relating to the health care domain are effectively annotated and employed to train sophisticated NLP models that provide valuable insights regarding many facets of health care.

Abstract: Methods and apparatus to facilitate annotation projects to extract structured information from free-form text using NLP techniques. Annotators explore text documents via automated preannotation functions, flexibly formulate annotation schemes and guidelines, annotate text, and adjust annotation labels, schemes and guidelines in real-time as a project evolves. NLP models are readily trained on iterative annotations of sample documents by domain experts in an active learning workflow. Trained models are then employed to automatically annotate a larger body of documents in a project dataset. Experts in a variety of domains can readily develop an annotation project for a specific use-case or business question. In one example, documents relating to the health care domain are effectively annotated and employed to train sophisticated NLP models that provide valuable insights regarding many facets of health care.