Search Results for author:
Found 34 papers, 11 papers with code
Unifying the Treatment of Preposition-Determiner Contractions in German Universal Dependencies Treebanks
HDT-UD, the largest German UD treebank by a large margin, as well as the German-LIT treebank, currently do not analyze preposition-determiner contractions such as zum (= zu dem, “to the”) as multi-word tokens, which is inconsistent both with UD guidelines as well as other German UD corpora (GSD and PUD).
A Corpus Study of Creating Rule-Based Enhanced Universal Dependencies for German
In this paper, we present a first attempt at enriching German Universal Dependencies (UD) treebanks with enhanced dependencies.
ClusterDataSplit: Exploring Challenging Clustering-Based Data Splits for Model Performance Evaluation
This paper adds to the ongoing discussion in the natural language processing community on how to choose a good development set.
RobertNLP at the IWPT 2021 Shared Task: Simple Enhanced UD Parsing for 17 Languages
This paper presents our multilingual dependency parsing system as used in the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies.
Applying Occam’s Razor to Transformer-Based Dependency Parsing: What Works, What Doesn’t, and What is Really Necessary
We find that the choice of pre-trained embeddings has by far the greatest impact on parser performance and identify XLM-R as a robust choice across the languages in our study.
A Crash Course on Ethics for Natural Language Processing
It is generally agreed upon in the natural language processing (NLP) community that ethics should be integrated into any curriculum.
AnnoCTR: A Dataset for Detecting and Linking Entities, Tactics, and Techniques in Cyber Threat Reports
In our few-shot scenario, we find that for identifying the MITRE ATT&CK concepts that are mentioned explicitly or implicitly in a text, concept descriptions from MITRE ATT&CK are an effective source for training data augmentation.
BoschAI @ Causal News Corpus 2023: Robust Cause-Effect Span Extraction using Multi-Layer Sequence Tagging and Data Augmentation
Understanding causality is a core aspect of intelligence.
BoschAI @ PLABA 2023: Leveraging Edit Operations in End-to-End Neural Sentence Simplification
We furthermore show that the hyperparameter $\lambda$ in token-level loss weights can be used to control the edit distance and the simplicity level (FKGL).
MuLMS: A Multi-Layer Annotated Text Corpus for Information Extraction in the Materials Science Domain
Keeping track of all relevant recent publications and experimental results for a research area is a challenging task.
MuLMS-AZ: An Argumentative Zoning Dataset for the Materials Science Domain
We present and release a new dataset of 50 manually annotated research articles.
MIST: a Large-Scale Annotated Resource and Neural Models for Functions of Modal Verbs in English Scientific Text
Modal verbs (e. g., "can", "should", or "must") occur highly frequently in scientific articles.
A Survey of Methods for Addressing Class Imbalance in Deep-Learning Based Natural Language Processing
With this survey, the first overview on class imbalance in deep-learning based NLP, we provide guidance for NLP researchers and practitioners dealing with imbalanced data.
A Kind Introduction to Lexical and Grammatical Aspect, with a Survey of Computational Approaches
This includes whether a situation is described as a state or as an event, whether the situation is finished or ongoing, and whether it is viewed as a whole or with a focus on a particular phase.
Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations
To close the gap, we organized the BioCreative LitCovid track to call for a community effort to tackle automated topic annotation for COVID-19 literature.
Negation-Instance Based Evaluation of End-to-End Negation Resolution
In this paper, we revisit the task of negation resolution, which includes the subtasks of cue detection (e. g. "not", "never") and scope resolution.
Coordinate Constructions in English Enhanced Universal Dependencies: Analysis and Computational Modeling
In this paper, we address the representation of coordinate constructions in Enhanced Universal Dependencies (UD), where relevant dependency links are propagated from conjunction heads to other conjuncts.
Applying Occam's Razor to Transformer-Based Dependency Parsing: What Works, What Doesn't, and What is Really Necessary
We find that the choice of pre-trained embeddings has by far the greatest impact on parser performance and identify XLM-R as a robust choice across the languages in our study.
RobertNLP at the IWPT 2020 Shared Task: Surprisingly Simple Enhanced UD Parsing for English
This paper presents our system at the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies.
The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain
With this paper, we publish our annotation guidelines, as well as our SOFC-Exp corpus consisting of 45 open-access scholarly articles annotated by domain experts.
Classification of telicity using cross-linguistic annotation projection
In English, this classification task is difficult, as telicity is a covert linguistic category.
LQVSumm: A Corpus of Linguistic Quality Violations in Multi-Document Summarization
We present LQVSumm, a corpus of about 2000 automatically created extractive multi-document summaries from the TAC 2011 shared task on Guided Summarization, which we annotated with several types of linguistic quality violations.
Coherent Multi-Sentence Video Description with Variable Level of Detail
Humans can easily describe what they see in a coherent way and at varying level of detail.
Suffix Trees as Language Models
Suffix trees are data structures that can be used to index a corpus.
