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Found 22 papers, 10 papers with code
Tencent submission for WMT20 Quality Estimation Shared Task
This paper presents Tencent’s submission to the WMT20 Quality Estimation (QE) Shared Task: Sentence-Level Post-editing Effort for English-Chinese in Task 2.
SPLICE: A Singleton-Enhanced PipeLIne for Coreference REsolution
We then propose a two-step neural mention and coreference resolution system, named SPLICE, and compare its performance to the end-to-end approach in two scenarios: the OntoNotes test set and the out-of-domain (OOD) OntoGUM corpus.
eRST: A Signaled Graph Theory of Discourse Relations and Organization
In this article we present Enhanced Rhetorical Structure Theory (eRST), a new theoretical framework for computational discourse analysis, based on an expansion of Rhetorical Structure Theory (RST).
Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal Data
Named Entity Recognition (NER) is a fundamental task to extract key information from texts, but annotated resources are scarce for dialects.
MaiBaam: A Multi-Dialectal Bavarian Universal Dependency Treebank
Despite the success of the Universal Dependencies (UD) project exemplified by its impressive language breadth, there is still a lack in `within-language breadth': most treebanks focus on standard languages.
MaiBaam Annotation Guidelines
This document provides the annotation guidelines for MaiBaam, a Bavarian corpus annotated with part-of-speech (POS) tags and syntactic dependencies.
VariErr NLI: Separating Annotation Error from Human Label Variation
To fill this gap, we introduce a systematic methodology and a new dataset, VariErr (variation versus error), focusing on the NLI task in English.
EEVEE: An Easy Annotation Tool for Natural Language Processing
Annotation tools are the starting point for creating Natural Language Processing (NLP) datasets.
Different Tastes of Entities: Investigating Human Label Variation in Named Entity Annotations
Named Entity Recognition (NER) is a key information extraction task with a long-standing tradition.
Incorporating Singletons and Mention-based Features in Coreference Resolution via Multi-task Learning for Better Generalization
Previous attempts to incorporate a mention detection step into end-to-end neural coreference resolution for English have been hampered by the lack of singleton mention span data as well as other entity information.
Ranked #1 on
Coreference Resolution
on OntoGUM
GENTLE: A Genre-Diverse Multilayer Challenge Set for English NLP and Linguistic Evaluation
We evaluate state-of-the-art NLP systems on GENTLE and find severe degradation for at least some genres in their performance on all tasks, which indicates GENTLE's utility as an evaluation dataset for NLP systems.
GCDT: A Chinese RST Treebank for Multigenre and Multilingual Discourse Parsing
A lack of large-scale human-annotated data has hampered the hierarchical discourse parsing of Chinese.
Chinese Discourse Annotation Reference Manual
This document provides extensive guidelines and examples for Rhetorical Structure Theory (RST) annotation in Mandarin Chinese.
PASTRIE: A Corpus of Prepositions Annotated with Supersense Tags in Reddit International English
We present the Prepositions Annotated with Supersense Tags in Reddit International English ("PASTRIE") corpus, a new dataset containing manually annotated preposition supersenses of English data from presumed speakers of four L1s: English, French, German, and Spanish.
DisCoDisCo at the DISRPT2021 Shared Task: A System for Discourse Segmentation, Classification, and Connective Detection
This paper describes our submission to the DISRPT2021 Shared Task on Discourse Unit Segmentation, Connective Detection, and Relation Classification.
AMALGUM -- A Free, Balanced, Multilayer English Web Corpus
We present a freely available, genre-balanced English web corpus totaling 4M tokens and featuring a large number of high-quality automatic annotation layers, including dependency trees, non-named entity annotations, coreference resolution, and discourse trees in Rhetorical Structure Theory.
A Corpus of Adpositional Supersenses for Mandarin Chinese
Adpositions are frequent markers of semantic relations, but they are highly ambiguous and vary significantly from language to language.
Modeling Long-Range Context for Concurrent Dialogue Acts Recognition
Previous work on DA recognition either assumes one DA per utterance or fails to realize the sequential nature of dialogues.
All Roads Lead to UD: Converting Stanford and Penn Parses to English Universal Dependencies with Multilayer Annotations
We describe and evaluate different approaches to the conversion of gold standard corpus data from Stanford Typed Dependencies (SD) and Penn-style constituent trees to the latest English Universal Dependencies representation (UD 2. 2).
GumDrop at the DISRPT2019 Shared Task: A Model Stacking Approach to Discourse Unit Segmentation and Connective Detection
In this paper we present GumDrop, Georgetown University's entry at the DISRPT 2019 Shared Task on automatic discourse unit segmentation and connective detection.
Adpositional Supersenses for Mandarin Chinese
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.
