Abstract: An entity grammar that specifies a computer conversational agent may be received. User utterances are interpreted based on the entity grammar and prompts for the conversational agent to pose are determined based on the entity grammar. An outcome of the dialog is built by storing words in the user utterances and the prompts that match tokens in the entity grammar. The entity grammar specifies both a dialog flow and data structure of the outcome.

Abstract: A computer-implemented conversational agent engages in a natural language conversation with a user, interpreting the natural language conversation by parsing and tokenizing utterances in the natural language conversation. Based on interpreting, a set of utterances in the natural language conversation to be recorded as a macro is determined. The macro is stored in a database with an associated macro identifier. Replaying of the macro executes a function specified in the set of utterances.

Abstract: A computer natural language conversational agent authors an event-processing rule by carrying out a dialog in natural language with a user. A data model that customizes a dialog and building of the event-processing rule is received. A partial tree data structure is constructed based on a rule's grammar, and specialized based on tokens extracted from the data model. An utterance is received from a user and interpreted according to the grammar as specialized to the data model. Based on the interpreting of the utterance, the grammar, the data model, and context of interactions with the user, a natural language prompt is determined for the computer natural language conversational agent to output to the user. The partial tree data structure is filled based on the natural language prompt and the utterance from the user. The event-processing rule is generated based on the partial tree data structure filled during the dialog.

Abstract: Database compiler with environment support may be provided. Database operators in a database compiler may be extended to include environment as an input parameter in addition to input data for native environment support. Environment operators may be added to the database compiler, which perform one or more of accessing and modifying the environment. Environment operators may include a return-environment operator, a map-with-environment operator and a compose-with-environment operator.

Abstract: An entity grammar that specifies a computer conversational agent may be received. User utterances are interpreted based on the entity grammar and prompts for the conversational agent to pose are determined based on the entity grammar. An outcome of the dialog is built by storing words in the user utterances and the prompts that match tokens in the entity grammar. The entity grammar specifies both a dialog flow and data structure of the outcome.

Abstract: An entity grammar that specifies a computer conversational agent may be received. User utterances are interpreted based on the entity grammar and prompts for the conversational agent to pose are determined based on the entity grammar. An outcome of the dialog is built by storing words in the user utterances and the prompts that match tokens in the entity grammar. The entity grammar specifies both a dialog flow and data structure of the outcome.

Abstract: Automatic generation of a chat bot from an API specification to carry out a dialogue with a user and invoke an API call described in the API specification. Based on input API specification, a conversational bot specification representing a dialog flow is constructed. A natural language expression is received and transformed into instructions based on the conversational bot specification. Based on the instructions, a natural language prompt to the user and executable computer code for invoking the API call may be generated.

Abstract: A computer-implemented conversational agent engages in a natural language conversation with a user, interpreting the natural language conversation by parsing and tokenizing utterances in the natural language conversation. Based on interpreting, a set of utterances in the natural language conversation to be recorded as a macro is determined. The macro is stored in a database with an associated macro identifier. Replaying of the macro executes a function specified in the set of utterances.

Abstract: A computer natural language conversational agent authors an event-processing rule by carrying out a dialog in natural language with a user. A data model that customizes a dialog and building of the event-processing rule is received. A partial tree data structure is constructed based on a rule's grammar, and specialized based on tokens extracted from the data model. An utterance is received from a user and interpreted according to the grammar as specialized to the data model. Based on the interpreting of the utterance, the grammar, the data model, and context of interactions with the user, a natural language prompt is determined for the computer natural language conversational agent to output to the user. The partial tree data structure is filled based on the natural language prompt and the utterance from the user. The event-processing rule is generated based on the partial tree data structure filled during the dialog.

Abstract: A computer-implemented conversational agent engages in a natural language conversation with a user, interpreting the natural language conversation by parsing and tokenizing utterances in the natural language conversation. Based on interpreting, a set of utterances in the natural language conversation to be recorded as a macro is determined. The macro is stored in a database with an associated macro identifier. Replaying of the macro executes a function specified in the set of utterances.

Abstract: A computer natural language conversational agent authors an event-processing rule by carrying out a dialog in natural language with a user. A data model that customizes a dialog and building of the event-processing rule is received. A partial tree data structure is constructed based on a rule's grammar, and specialized based on tokens extracted from the data model. An utterance is received from a user and interpreted according to the grammar as specialized to the data model. Based on the interpreting of the utterance, the grammar, the data model, and context of interactions with the user, a natural language prompt is determined for the computer natural language conversational agent to output to the user. The partial tree data structure is filled based on the natural language prompt and the utterance from the user. The event-processing rule is generated based on the partial tree data structure filled during the dialog.

Abstract: Automatic generation of a chat bot from an API specification to carry out a dialogue with a user and invoke an API call described in the API specification. Based on input API specification, a conversational bot specification representing a dialog flow is constructed. A natural language expression is received and transformed into instructions based on the conversational bot specification. Based on the instructions, a natural language prompt to the user and executable computer code for invoking the API call may be generated.

Abstract: Automatic generation of a chat bot from an API specification to carry out a dialog with a user and invoke an API call described in the API specification. Based on input API specification, a conversational bot specification representing a dialog flow is constructed. A natural language expression is received and transformed into instructions based on the conversational bot specification. Based on the instructions, a natural language prompt to the user and executable computer code for invoking the API call may be generated.

Abstract: A computer-implemented conversational agent engages in a natural language conversation with a user, interpreting the natural language conversation by parsing and tokenizing utterances in the natural language conversation. Based on interpreting, a set of utterances in the natural language conversation to be recorded as a macro is determined. The macro is stored in a database with an associated macro identifier. Replaying of the macro executes a function specified in the set of utterances.

Abstract: Automatic generation of a chat bot from an API specification to carry out a dialogue with a user and invoke an API call described in the API specification. Based on input API specification, a conversational bot specification representing a dialog flow is constructed. A natural language expression is received and transformed into instructions based on the conversational bot specification. Based on the instructions, a natural language prompt to the user and executable computer code for invoking the API call may be generated.

Abstract: Running a global production rule on data distributed over a plurality of machines may comprise receiving a local production rule that can run on each of the plurality of machines to jointly accomplish a global computation specified by the global production rule. The local production rule may be deployed to each of the plurality of machines, each of which stores a portion of the data and runs an instance of a rules engine that can run the local production rule. The plurality of machines are enabled to communicate intermediate data produced by the instance of the rules engine running the local production rule on said each of the machines. Coordinating between the plurality of machines is enabled to synchronize one or more local computations performed locally according to the local production rule on said each machine.

Abstract: A computer natural language conversational agent authors an event-processing rule by carrying out a dialog in natural language with a user. A data model that customizes a dialog and building of the event-processing rule is received. A partial tree data structure is constructed based on a rule's grammar, and specialized based on tokens extracted from the data model. An utterance is received from a user and interpreted according to the grammar as specialized to the data model. Based on the interpreting of the utterance, the grammar, the data model, and context of interactions with the user, a natural language prompt is determined for the computer natural language conversational agent to output to the user. The partial tree data structure is filled based on the natural language prompt and the utterance from the user. The event-processing rule is generated based on the partial tree data structure filled during the dialog.

Abstract: An entity grammar that specifies a computer conversational agent may be received. User utterances are interpreted based on the entity grammar and prompts for the conversational agent to pose are determined based on the entity grammar. An outcome of the dialog is built by storing words in the user utterances and the prompts that match tokens in the entity grammar. The entity grammar specifies both a dialog flow and data structure of the outcome.

Abstract: Database compiler with environment support may be provided. Database operators in a database compiler may be extended to include environment as an input parameter in addition to input data for native environment support. Environment operators may be added to the database compiler, which perform one or more of accessing and modifying the environment. Environment operators may include a return-environment operator, a map-with-environment operator and a compose-with-environment operator.

Abstract: Running a global production rule on data distributed over a plurality of machines may comprise receiving a local production rule that can run on each of the plurality of machines to jointly accomplish a global computation specified by the global production rule. The local production rule may be deployed to each of the plurality of machines, each of which stores a portion of the data and runs an instance of a rules engine that can run the local production rule. The plurality of machines are enabled to communicate intermediate data produced by the instance of the rules engine running the local production rule on said each of the machines. Coordinating between the plurality of machines is enabled to synchronize one or more local computations performed locally according to the local production rule on said each machine.