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Found 15 papers, 9 papers with code
Subcategorizing Adverbials in Universal Conceptual Cognitive Annotation
Universal Conceptual Cognitive Annotation (UCCA) is a semantic annotation scheme that organizes texts into coarse predicate-argument structure, offering broad coverage of semantic phenomena.
Empirical Sufficiency Lower Bounds for Language Modeling with Locally-Bootstrapped Semantic Structures
In this work we build upon negative results from an attempt at language modeling with predicted semantic structure, in order to establish empirical lower bounds on what could have made the attempt successful.
Reanalyzing L2 Preposition Learning with Bayesian Mixed Effects and a Pretrained Language Model
We use both Bayesian and neural models to dissect a data set of Chinese learners' pre- and post-interventional responses to two tests measuring their understanding of English prepositions.
Linguistic Frameworks Go Toe-to-Toe at Neuro-Symbolic Language Modeling
We examine the extent to which, in principle, linguistic graph representations can complement and improve neural language modeling.
UCCA's Foundational Layer: Annotation Guidelines v2.1
This is the annotation manual for Universal Conceptual Cognitive Annotation (UCCA; Abend and Rappoport, 2013), specifically the Foundational Layer.
Supertagging the Long Tail with Tree-Structured Decoding of Complex Categories
Our best tagger is capable of recovering a sizeable fraction of the long-tail supertags and even generates CCG categories that have never been seen in training, while approximating the prior state of the art in overall tag accuracy with fewer parameters.
Cross-lingual Semantic Representation for NLP with UCCA
This is an introductory tutorial to UCCA (Universal Conceptual Cognitive Annotation), a cross-linguistically applicable framework for semantic representation, with corpora annotated in English, German and French, and ongoing annotation in Russian and Hebrew.
Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics
Building robust natural language understanding systems will require a clear characterization of whether and how various linguistic meaning representations complement each other.
Made for Each Other: Broad-coverage Semantic Structures Meet Preposition Supersenses
Universal Conceptual Cognitive Annotation (UCCA; Abend and Rappoport, 2013) is a typologically-informed, broad-coverage semantic annotation scheme that describes coarse-grained predicate-argument structure but currently lacks semantic roles.
Semantically Constrained Multilayer Annotation: The Case of Coreference
We propose a coreference annotation scheme as a layer on top of the Universal Conceptual Cognitive Annotation foundational layer, treating units in predicate-argument structure as a basis for entity and event mentions.
Comprehensive Supersense Disambiguation of English Prepositions and Possessives
Semantic relations are often signaled with prepositional or possessive marking--but extreme polysemy bedevils their analysis and automatic interpretation.
Ranked #4 on
Natural Language Understanding
on STREUSLE
(Role F1 (Preps) metric)
Adposition and Case Supersenses v2.6: Guidelines for English
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).
A Corpus of Literal and Idiomatic Uses of German Infinitive-Verb Compounds
We present an annotation study on a representative dataset of literal and idiomatic uses of German infinitive-verb compounds in newspaper and journal texts.
