activity
20172026
most citedA Transition-Based Directed Acyclic Graph Parser for UCCA

99 citations · 138 across the 19 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

cs.CL2020

Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics

Daniel Hershcovich, Nathan Schneider, Dotan Dvir +3

Building robust natural language understanding systems will require a clear characterization of whether and how various linguistic meaning representations complement each other. To…

cs.CL2020

HUJI-KU at MRP~2020: Two Transition-based Neural Parsers

Ofir Arviv, Ruixiang Cui, Daniel Hershcovich

This paper describes the HUJI-KU system submission to the shared task on Cross-Framework Meaning Representation Parsing (MRP) at the 2020 Conference for Computational Language Lear…

cs.CL2020

Joint Semantic Analysis with Document-Level Cross-Task Coherence Rewards

Rahul Aralikatte, Mostafa Abdou, Heather Lent +2

Coreference resolution and semantic role labeling are NLP tasks that capture different aspects of semantics, indicating respectively, which expressions refer to the same entity, an…

cs.CL2020

Køpsala: Transition-Based Graph Parsing via Efficient Training and Effective Encoding

Daniel Hershcovich, Miryam de Lhoneux, Artur Kulmizev +2

We present Køpsala, the Copenhagen-Uppsala system for the Enhanced Universal Dependencies Shared Task at IWPT 2020. Our system is a pipeline consisting of off-the-shelf models for…

cs.CL2020★ 6 cited

Refining Implicit Argument Annotation for UCCA

Ruixiang Cui, Daniel Hershcovich

Predicate-argument structure analysis is a central component in meaning representations of text. The fact that some arguments are not explicitly mentioned in a sentence gives rise…

cs.CL2020

Lexical Semantic Recognition

Nelson F. Liu, Daniel Hershcovich, Michael Kranzlein +1

In lexical semantics, full-sentence segmentation and segment labeling of various phenomena are generally treated separately, despite their interdependence. We hypothesize that a un…