Abstract: Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a natural language document orchestrator. In some example embodiments, a method is provided that comprises generating natural language text. The method of this embodiment may also include executing document orchestration requests from a scripted input language file.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a natural language document orchestrator. In some example embodiments, a method is provided that comprises generating natural language text. The method of this embodiment may also include executing document orchestration requests from a scripted input language file.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a natural language document orchestrator. In some example embodiments, a method is provided that comprises generating natural language text. The method of this embodiment may also include executing document orchestration requests from a scripted input language file.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to enable updating of an output text. In some example embodiments, a method is provided that comprises generating a new message for each updateable data element based on a predetermined indication. The method of this embodiment may also include determining a classification for each new message by comparing each new message with a corresponding message that describes the updateable data element. The method of this embodiment may also include generating an additional document plan tree that contains at least a portion of the new messages. The method of this embodiment may also include combining the additional document plan tree with an original document plan tree.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a natural language realizer in the form of a lightweight multilingual realizer. In some example embodiments, a method is provided that comprises generating syntactically correct natural language. The method of this embodiment may also include at a syntax processor, propagating features among a group of words, and adding closed class function words and morphological inflections.

Abstract: Various methods are provided for generating and annotating a graph. One example method may include determining one or more key patterns in a primary data channel, wherein the primary data channel is derived from raw input data in response to a constraint being satisfied. A method may further include determining one or more significant patterns in one or more related data channels. A method may further include generating a natural language annotation for at least one of the one or more key patterns or the one or more significant patterns. A method may further include generating a graph that is configured to be displayed in a user interface, the graph having at least a portion of the one or more key patterns, the one or more significant patterns and the natural language annotation.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to enable updating of an output text. In some example embodiments, a method is provided that comprises generating a new message for each updateable data element based on a predetermined indication. The method of this embodiment may also include determining a classification for each new message by comparing each new message with a corresponding message that describes the updateable data element. The method of this embodiment may also include generating an additional document plan tree that contains at least a portion of the new messages. The method of this embodiment may also include combining the additional document plan tree with an original document plan tree.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a natural language document orchestrator. In some example embodiments, a method is provided that comprises generating natural language text. The method of this embodiment may also include executing document orchestration requests from a scripted input language file.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a natural language realizer in the form of a lightweight multilingual realizer. In some example embodiments, a method is provided that comprises generating syntactically correct natural language. The method of this embodiment may also include at a syntax processor, propagating features among a group of words, and adding closed class function words and morphological inflections.

Abstract: Various methods are provided for generating and annotating a graph. One example method may include determining one or more key patterns in a primary data channel, wherein the primary data channel is derived from raw input data in response to a constraint being satisfied. A method may further include determining one or more significant patterns in one or more related data channels. A method may further include generating a natural language annotation for at least one of the one or more key patterns or the one or more significant patterns. A method may further include generating a graph that is configured to be displayed in a user interface, the graph having at least a portion of the one or more key patterns, the one or more significant patterns and the natural language annotation.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a configurable microplanner. In some example embodiments, a method is provided that comprises accessing a document plan containing one or more messages. The method of this embodiment may also include generating a text specification containing one or more phrase specifications that correspond to the one or more messages in the document plan. The method of this embodiment may also include applying a set of lexicalization rules to each of the one or more messages to populate the one or more phrase specifications. In some example embodiments, the set of lexicalization rules are specified using a microplanning rule specification language that is configured to hide linguistic complexities from a user. In some example embodiments, genre parameters may also be used to specify constraints that provide default behaviors for the realization process.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to enable updating of an output text. In some example embodiments, a method is provided that comprises generating a new message for each updateable data element based on a predetermined indication. The method of this embodiment may also include determining a classification for each new message by comparing each new message with a corresponding message that describes the updateable data element. The method of this embodiment may also include generating an additional document plan tree that contains at least a portion of the new messages. The method of this embodiment may also include combining the additional document plan tree with an original document plan tree.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a natural language document orchestrator. In some example embodiments, a method is provided that comprises generating natural language text. The method of this embodiment may also include executing document orchestration requests from a scripted input language file.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a natural language realizer in the form of a lightweight multilingual realizer. In some example embodiments, a method is provided that comprises generating syntactically correct natural language. The method of this embodiment may also include at a syntax processor, propagating features among a group of words, and adding closed class function words and morphological inflections.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to perform aggregation of phrase specifications. In some example embodiments, a method is provided that comprises identifying two or more generalized phrase specifications. In some example embodiments, the two or more generalized phrase specifications contain at least one aggregatable constituent. The method of this embodiment may also include generating an aggregated phrase specification from the two or more generalized phrase specifications. In some example embodiments, the aggregated phrase specification comprises a combined noun phrase generated from the aggregatable constituents and one or more additional constituents based on a determined level of generalization.

Abstract: Various methods are provided for generating and annotating a graph. One example method may include determining one or more key patterns in a primary data channel, wherein the primary data channel is derived from raw input data in response to a constraint being satisfied. A method may further include determining one or more significant patterns in one or more related data channels. A method may further include generating a natural language annotation for at least one of the one or more key patterns or the one or more significant patterns. A method may further include generating a graph that is configured to be displayed in a user interface, the graph having at least a portion of the one or more key patterns, the one or more significant patterns and the natural language annotation.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to perform aggregation of phrase specifications. In some example embodiments, a method is provided that comprises identifying two or more generalized phrase specifications. In some example embodiments, the two or more generalized phrase specifications contain at least one aggregatable constituent. The method of this embodiment may also include generating an aggregated phrase specification from the two or more generalized phrase specifications. In some example embodiments, the aggregated phrase specification comprises a combined noun phrase generated from the aggregatable constituents and one or more additional constituents based on a determined level of generalization.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to perform aggregation of phrase specifications. In some example embodiments, a method is provided that comprises identifying two or more generalized phrase specifications. In some example embodiments, the two or more generalized phrase specifications contain at least one aggregatable constituent. The method of this embodiment may also include generating an aggregated phrase specification from the two or more generalized phrase specifications. In some example embodiments, the aggregated phrase specification comprises a combined noun phrase generated from the aggregatable constituents and one or more additional constituents based on a determined level of generalization.

Abstract: Methods, apparatuses, and computer program products are described herein that are configured to perform aggregation of phrase specifications. In some example embodiments, a method is provided that comprises identifying two or more generalized phrase specifications. In some example embodiments, the two or more generalized phrase specifications contain at least one aggregatable constituent. The method of this embodiment may also include generating an aggregated phrase specification from the two or more generalized phrase specifications. In some example embodiments, the aggregated phrase specification comprises a combined noun phrase generated from the aggregatable constituents and one or more additional constituents based on a determined level of generalization.

Abstract: Various methods are provided for generating and annotating a graph. One example method may include determining one or more key patterns in a primary data channel, wherein the primary data channel is derived from raw input data in response to a constraint being satisfied. A method may further include determining one or more significant patterns in one or more related data channels. A method may further include generating a natural language annotation for at least one of the one or more key patterns or the one or more significant patterns. A method may further include generating a graph that is configured to be displayed in a user interface, the graph having at least a portion of the one or more key patterns, the one or more significant patterns and the natural language annotation.