Getting More Out Of Syntax with PropS

Understand

Semantic NLP applications often rely on dependency trees to recognize major elements of the proposition structure of sentences.

• Yet, while much semantic structure is indeed expressed by syntax, many phenomena are not easily read out of dependency trees, often leading to further ad-hoc heuristic post-processing or to information loss.
• To directly address the needs of semantic applications, we present PropS -- an output representation designed to explicitly and uniformly express much of the proposition structure which is implied from syntax, and an associated tool for extracting it from dependency trees.