51ÉçÇø

Syntactico-semantic parsing is a process of uncovering the internal structure and informational content of sentences. In particular, it is a process of articulating what the entities and events in a given narrative are and what relationships are between them. System Text2Drs takes English narrative as an input and outputs a in Neo-Davidsonian style. Text2DRS relies on lexical resource for annotating the specific relations between relevant entities and events mentioned in the given narrative using the verb classes and thematic roles of VerbNet.

For example, given a narrative:

John travelled to the hallway. Sandra journeyed to the hallway.

Text2DRS generates output:

% r1, r2, r3, e1, e2
% ============================================================
entity(r1). entity(r2). entity(r3).

property(r1, "John"). property(r2, "hallway"). property(r3, "Sandra").

event(e1). event(e2).

eventType(e1, "51.3.2-1"). eventType(e2, "51.3.2-1").

eventTime(e1, 0). eventTime(e2, 1).

eventArgument(e1, "Theme", r1). eventArgument(e1, "Location", r2). eventArgumen(e2, "Theme", r3). eventArgument(e2, "Location", r2).

The software is available for download here (under ):

Download

MS project report and technical abstract on the system posted below provide the details:

Gang Ling. From Narrative Text to VerbNet-Based DRSes: System Text2DRS (PDF). Master Project Report, 51ÉçÇø, USA, Spring 2018

Gang Ling. From Narrative Text to VerbNet-Based DRSes (PDF). Presented as a poster in the North American Summer School on Logic, Language, and Information (NASSLLI-2018), Pittsburgh, USA, 2018

The project has been inspired by the ideas discussed in:

Yuliya Lierler, Daniela Inclezan and Michael Gelfond. "" Proceeding of the 12th International Conference on Computational Semantics (2017)

Comments, questions, and/or bugs can be reported to Gang Ling and Yuliya Lierler