Computational semantics in the Natural Language Toolkit

NLTK, the Natural Language Toolkit, is an open source project whose goals include providing students with software and language resources that will help them to learn basic NLP. Until now, the program modules in NLTK have covered such topics as tagging, chunking, and parsing, but have not incorporated any aspect of semantic interpretation. This paper describes recent work on building a new semantics package for NLTK. This currently allows semantic representations to be built compositionally as a part of sentence parsing, and for the representations to be evaluated by a model checker. We present the main components of this work, and consider comparisons between the Python implementation and the Prolog approach developed by Blackburn and Bos (2005).

Genie: A Generator of Natural Language Semantic Parsers for Virtual Assistant Commands

To understand diverse natural language commands, virtual assistants today are trained with numerous labor-intensive, manually annotated sentences. This paper presents a methodology and the Genie toolkit that can handle new compound commands with significantly less manual effort. We advocate formalizing the capability of virtual assistants with a Virtual Assistant Programming Language (VAPL) and using a neural semantic parser to translate natural language into VAPL code. Genie needs only a small realistic set of input sentences for validating the neural model. Developers write templates to synthesize data; Genie uses crowdsourced paraphrases and data augmentation, along with the synthesized data, to train a semantic parser. We also propose design principles that make VAPL languages amenable to natural language translation. We apply these principles to revise ThingTalk, the language used by the Almond virtual assistant. We use Genie to build the first semantic parser that can support compound virtual assistants commands with unquoted free-form parameters. Genie achieves a 62% accuracy on realistic user inputs. We demonstrate Genie's generality by showing a 19% and 31% improvement over the previous state of the art on a music skill, aggregate functions, and access control.Comment: To appear in PLDI 201

Proceedings of International Workshop "Global Computing: Programming Environments, Languages, Security and Analysis of Systems"

According to the IST/ FET proactive initiative on GLOBAL COMPUTING, the goal is to obtain techniques (models, frameworks, methods, algorithms) for constructing systems that are flexible, dependable, secure, robust and efficient. The dominant concerns are not those of representing and manipulating data efficiently but rather those of handling the co-ordination and interaction, security, reliability, robustness, failure modes, and control of risk of the entities in the system and the overall design, description and performance of the system itself. Completely different paradigms of computer science may have to be developed to tackle these issues effectively. The research should concentrate on systems having the following characteristics: • The systems are composed of autonomous computational entities where activity is not centrally controlled, either because global control is impossible or impractical, or because the entities are created or controlled by different owners. • The computational entities are mobile, due to the movement of the physical platforms or by movement of the entity from one platform to another. • The configuration varies over time. For instance, the system is open to the introduction of new computational entities and likewise their deletion. The behaviour of the entities may vary over time. • The systems operate with incomplete information about the environment. For instance, information becomes rapidly out of date and mobility requires information about the environment to be discovered. The ultimate goal of the research action is to provide a solid scientific foundation for the design of such systems, and to lay the groundwork for achieving effective principles for building and analysing such systems. This workshop covers the aspects related to languages and programming environments as well as analysis of systems and resources involving 9 projects (AGILE , DART, DEGAS , MIKADO, MRG, MYTHS, PEPITO, PROFUNDIS, SECURE) out of the 13 founded under the initiative. After an year from the start of the projects, the goal of the workshop is to fix the state of the art on the topics covered by the two clusters related to programming environments and analysis of systems as well as to devise strategies and new ideas to profitably continue the research effort towards the overall objective of the initiative. We acknowledge the Dipartimento di Informatica and Tlc of the University of Trento, the Comune di Rovereto, the project DEGAS for partially funding the event and the Events and Meetings Office of the University of Trento for the valuable collaboration