In contrast to large text corpora, knowledge graphs (KG) provide dense a...
We present NorBench: a streamlined suite of NLP tasks and probes for
eva...
This paper explores the task of identifying the overall sentiment expres...
We investigate in this paper how distributions of occupations with respe...
While modern masked language models (LMs) are trained on ever larger cor...
We present a qualitative analysis of the (potentially erroneous) outputs...
This paper demonstrates how a graph-based semantic parser can be applied...
Structured sentiment analysis attempts to extract full opinion tuples fr...
We present the ongoing NorLM initiative to support the creation and use ...
Fine-grained sentiment analysis attempts to extract sentiment holders,
t...
Documents are composed of smaller pieces - paragraphs, sentences, and to...
We here introduce NoReCfine, a dataset for fine-grained sentiment analys...
This paper presents NorNE, a manually annotated corpus of named entities...
We extend the well-known word analogy task to a one-to-X formulation,
in...
Sentiment analysis is directly affected by compositional phenomena in
la...
Neural methods for SA have led to quantitative improvements over previou...
This paper extends the task of probing sentence representations for
ling...
In this paper, we empirically evaluate the utility of transfer and multi...
Recent years have witnessed a surge of publications aimed at tracing tem...
This paper presents the Norwegian Review Corpus (NoReC), created for tra...
This paper deals with using word embedding models to trace the temporal
...
This paper studies how word embeddings trained on the British National C...