Search Results for author: Austin Blodgett

Found 11 papers, 6 papers with code

The Search for Agreement on Logical Fallacy Annotation of an Infodemic

no code implementations LREC 2022 Claire Bonial, Austin Blodgett, Taylor Hudson, Stephanie M. Lukin, Jeffrey Micher, Douglas Summers-Stay, Peter Sutor, Clare Voss

We evaluate an annotation schema for labeling logical fallacy types, originally developed for a crowd-sourcing annotation paradigm, now using an annotation paradigm of two trained linguist annotators.

Logical Fallacies

Xposition: An Online Multilingual Database of Adpositional Semantics

no code implementations LREC 2022 Luke Gessler, Nathan Schneider, Joseph C. Ledford, Austin Blodgett

We present Xposition, an online platform for documenting adpositional semantics across languages in terms of supersenses (Schneider et al., 2018).

DocAMR: Multi-Sentence AMR Representation and Evaluation

1 code implementation NAACL 2022 Tahira Naseem, Austin Blodgett, Sadhana Kumaravel, Tim O'Gorman, Young-suk Lee, Jeffrey Flanigan, Ramón Fernandez Astudillo, Radu Florian, Salim Roukos, Nathan Schneider

Despite extensive research on parsing of English sentences into Abstraction Meaning Representation (AMR) graphs, which are compared to gold graphs via the Smatch metric, full-document parsing into a unified graph representation lacks well-defined representation and evaluation.

coreference-resolution Coreference Resolution

Probabilistic, Structure-Aware Algorithms for Improved Variety, Accuracy, and Coverage of AMR Alignments

1 code implementation ACL 2021 Austin Blodgett, Nathan Schneider

We present algorithms for aligning components of Abstract Meaning Representation (AMR) graphs to spans in English sentences.

AMR Parsing

A Corpus of Adpositional Supersenses for Mandarin Chinese

no code implementations LREC 2020 Siyao Peng, Yang Liu, YIlun Zhu, Austin Blodgett, Yushi Zhao, Nathan Schneider

Adpositions are frequent markers of semantic relations, but they are highly ambiguous and vary significantly from language to language.


An Improved Approach for Semantic Graph Composition with CCG

no code implementations WS 2019 Austin Blodgett, Nathan Schneider

We define new semantics for the CCG combinators that is better suited to deriving AMR graphs.

AMR Parsing

Adpositional Supersenses for Mandarin Chinese

no code implementations6 Dec 2018 YIlun Zhu, Yang Liu, Siyao Peng, Austin Blodgett, Yushi Zhao, Nathan Schneider

This study adapts Semantic Network of Adposition and Case Supersenses (SNACS) annotation to Mandarin Chinese and demonstrates that the same supersense categories are appropriate for Chinese adposition semantics.

Machine Translation Translation

Comprehensive Supersense Disambiguation of English Prepositions and Possessives

1 code implementation ACL 2018 Nathan Schneider, Jena D. Hwang, Vivek Srikumar, Jakob Prange, Austin Blodgett, Sarah R. Moeller, Aviram Stern, Adi Bitan, Omri Abend

Semantic relations are often signaled with prepositional or possessive marking--but extreme polysemy bedevils their analysis and automatic interpretation.

Adposition and Case Supersenses v2.6: Guidelines for English

4 code implementations7 Apr 2017 Nathan Schneider, Jena D. Hwang, Vivek Srikumar, Archna Bhatia, Na-Rae Han, Tim O'Gorman, Sarah R. Moeller, Omri Abend, Adi Shalev, Austin Blodgett, Jakob Prange

This document offers a detailed linguistic description of SNACS (Semantic Network of Adposition and Case Supersenses; Schneider et al., 2018), an inventory of 52 semantic labels ("supersenses") that characterize the use of adpositions and case markers at a somewhat coarse level of granularity, as demonstrated in the STREUSLE corpus (https://github. com/nert-nlp/streusle/ ; version 4. 5 tracks guidelines version 2. 6).

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