Annotated Datasets
Related Papers
Automatically Identifying Implicit Arguments to Improve Argument Linking and Coherence Modeling
Implicit arguments are a discourse-level phe- nomenon that has not been extensively stud- ied in semantic processing. One reason for this lies in the scarce amount of annotated data sets …...
Supervised Morphological Segmentation in a Low-Resource Learning Setting using Conditional Random Fields
We discuss data-driven morphological segmentation, in which word forms are segmented into morphs, the surface forms of morphemes. Our focus is on a low- resource learning setting, in which only …...
A comparison of Named-Entity Disambiguation and Word Sense Disambiguation
AbstractNamed Entity Disambiguation (NED) is the task of linking a named-entity mention to an instance in a knowledge-base, typically Wikipedia-derived resources like DBpedia. This task is closely related to word-sense …...
Government Domain Named Entity Recognition for South African Languages
AbstractThis paper describes the named entity language resources developed as part of a development project for the South African languages. The development efforts focused on creating protocols and annotated data …...
A Novel Challenge Set for Hebrew Morphological Disambiguation and Diacritics Restoration
AbstractOne of the primary tasks of morphological parsers is the disambiguation of homographs. Particularly difficult are cases of unbalanced ambiguity, where one of the possible analyses is far more frequent …...
Lin: Unsupervised Extraction of Tasks from Textual Communication
AbstractCommitments and requests are a hallmark of collaborative communication, especially in team settings. Identifying specific tasks being committed to or request from emails and chat messages can enable important downstream …...
Offensive Video Detection: Dataset and Baseline Results
AbstractWeb-users produce and publish high volumes of data of various types, such as text, images, and videos. The platforms try to restrain their users from publishing offensive content to keep …...
Understanding Pre-trained BERT for Aspect-based Sentiment Analysis
AbstractThis paper analyzes the pre-trained hidden representations learned from reviews on BERT for tasks in aspect-based sentiment analysis (ABSA). Our work is motivated by the recent progress in BERT-based language …...
Evaluating Scholarly Impact: Towards Content-Aware Bibliometrics
AbstractQuantitatively measuring the impact-related aspects of scientific, engineering, and technological (SET) innovations is a fundamental problem with broad applications. Traditional citation-based measures for assessing the impact of innovations and related …...
BERTifying Sinhala - A Comprehensive Analysis of Pre-trained Language Models for Sinhala Text Classification
AbstractThis research provides the first comprehensive analysis of the performance of pre-trained language models for Sinhala text classification. We test on a set of different Sinhala text classification tasks and …...
PropBank Comes of Age—Larger, Smarter, and more Diverse
AbstractThis paper describes the evolution of the PropBank approach to semantic role labeling over the last two decades. During this time the PropBank frame files have been expanded to include …...
Systematic Analysis of Image Schemas in Natural Language through Explainable Multilingual Neural Language Processing
AbstractIn embodied cognition, physical experiences are believed to shape abstract cognition, such as natural language and reasoning. Image schemas were introduced as spatio-temporal cognitive building blocks that capture these recurring …...