Zero and Few-shot Semantic Parsing with Ambiguous Inputs

1 code implementation • 1 Jun 2023 • Elias Stengel-Eskin, Kyle Rawlins, Benjamin Van Durme

We attempt to address this shortcoming by introducing AmP, a framework, dataset, and challenge for translating ambiguous natural language to formal representations like logic and code.

Semantic Parsing

LOME: Large Ontology Multilingual Extraction

no code implementations • EACL 2021 • Patrick Xia, Guanghui Qin, Siddharth Vashishtha, Yunmo Chen, Tongfei Chen, Chandler May, Craig Harman, Kyle Rawlins, Aaron Steven White, Benjamin Van Durme

We present LOME, a system for performing multilingual information extraction.

coreference-resolution Entity Typing +4

Frequency, Acceptability, and Selection: A case study of clause-embedding

no code implementations • 8 Apr 2020 • Aaron Steven White, Kyle Rawlins

We investigate the relationship between the frequency with which verbs are found in particular subcategorization frames and the acceptability of those verbs in those frames, focusing in particular on subordinate clause-taking verbs, such as "think", "want", and "tell".

Multi-Sentence Argument Linking

no code implementations • ACL 2020 • Seth Ebner, Patrick Xia, Ryan Culkin, Kyle Rawlins, Benjamin Van Durme

We present a novel document-level model for finding argument spans that fill an event's roles, connecting related ideas in sentence-level semantic role labeling and coreference resolution.

coreference-resolution Semantic Role Labeling +2

The Universal Decompositional Semantics Dataset and Decomp Toolkit

1 code implementation • LREC 2020 • Aaron Steven White, Elias Stengel-Eskin, Siddharth Vashishtha, Venkata Govindarajan, Dee Ann Reisinger, Tim Vieira, Keisuke Sakaguchi, Sheng Zhang, Francis Ferraro, Rachel Rudinger, Kyle Rawlins, Benjamin Van Durme

We present the Universal Decompositional Semantics (UDS) dataset (v1. 0), which is bundled with the Decomp toolkit (v0. 1).

Predicting the Argumenthood of English Prepositional Phrases

no code implementations • 20 Sep 2018 • Najoung Kim, Kyle Rawlins, Benjamin Van Durme, Paul Smolensky

Distinguishing between arguments and adjuncts of a verb is a longstanding, nontrivial problem.

Semantic Role Labeling Sentence +1

Lexicosyntactic Inference in Neural Models

no code implementations • EMNLP 2018 • Aaron Steven White, Rachel Rudinger, Kyle Rawlins, Benjamin Van Durme

We use this dataset, which we make publicly available, to probe the behavior of current state-of-the-art neural systems, showing that these systems make certain systematic errors that are clearly visible through the lens of factuality prediction.

The Semantic Proto-Role Linking Model

no code implementations • EACL 2017 • Aaron Steven White, Kyle Rawlins, Benjamin Van Durme

We propose the semantic proto-role linking model, which jointly induces both predicate-specific semantic roles and predicate-general semantic proto-roles based on semantic proto-role property likelihood judgments.

Semantic Role Labeling

Universal Decompositional Semantics on Universal Dependencies

1 code implementation • EMNLP 2016 • Aaron Steven White, Drew Reisinger, Keisuke Sakaguchi, Tim Vieira, Sheng Zhang, Rachel Rudinger, Kyle Rawlins, Benjamin Van Durme

Computational linking theory

no code implementations • 8 Oct 2016 • Aaron Steven White, Drew Reisinger, Rachel Rudinger, Kyle Rawlins, Benjamin Van Durme

A linking theory explains how verbs' semantic arguments are mapped to their syntactic arguments---the inverse of the Semantic Role Labeling task from the shallow semantic parsing literature.

Semantic Parsing Semantic Role Labeling

Semantic Proto-Roles

no code implementations • TACL 2015 • Drew Reisinger, Rachel Rudinger, Francis Ferraro, Craig Harman, Kyle Rawlins, Benjamin Van Durme

We present the first large-scale, corpus based verification of Dowty{'}s seminal theory of proto-roles.

Semantic Role Labeling