Implicit Discourse Relation Classification
6 papers with code • 0 benchmarks • 2 datasets
Parsing a text into a set of discourse relations between two adjacent or non-adjacent discourse units in the absence of explicit connectives, such as 'but' or 'however', and classifying those relations. (Source: Adapted from https://www.cs.brandeis.edu/~clp/conll15st/intro.html)
Benchmarks
These leaderboards are used to track progress in Implicit Discourse Relation Classification
DISRPT2021
Latest papers with no code
Prompting Implicit Discourse Relation Annotation
Pre-trained large language models, such as ChatGPT, archive outstanding performance in various reasoning tasks without supervised training and were found to have outperformed crowdsourcing workers.
A Side-by-side Comparison of Transformers for English Implicit Discourse Relation Classification
Though discourse parsing can help multiple NLP fields, there has been no wide language model search done on implicit discourse relation classification.
Pre-trained Sentence Embeddings for Implicit Discourse Relation Classification
Implicit discourse relations bind smaller linguistic units into coherent texts.
Entity Enhancement for Implicit Discourse Relation Classification in the Biomedical Domain
Implicit discourse relation classification is a challenging task, in particular when the text domain is different from the standard Penn Discourse Treebank (PDTB; Prasad et al., 2008) training corpus domain (Wall Street Journal in 1990s).
Let's be explicit about that: Distant supervision for implicit discourse relation classification via connective prediction
We sidestep the lack of data through explicitation of implicit relations to reduce the task to two sub-problems: language modeling and explicit discourse relation classification, a much easier problem.
Using a Penalty-based Loss Re-estimation Method to Improve Implicit Discourse Relation Classification
We tackle implicit discourse relation classification, a task of automatically determining semantic relationships between arguments.
Implicit Discourse Relation Classification: We Need to Talk about Evaluation
Implicit relation classification on Penn Discourse TreeBank (PDTB) 2. 0 is a common benchmark task for evaluating the understanding of discourse relations.
Adapting BERT to Implicit Discourse Relation Classification with a Focus on Discourse Connectives
BERT, a neural network-based language model pre-trained on large corpora, is a breakthrough in natural language processing, significantly outperforming previous state-of-the-art models in numerous tasks.
Unsupervised Adversarial Domain Adaptation for Implicit Discourse Relation Classification
Implicit discourse relations are not only more challenging to classify, but also to annotate, than their explicit counterparts.
Next Sentence Prediction helps Implicit Discourse Relation Classification within and across Domains
Implicit discourse relation classification is one of the most difficult tasks in discourse parsing.
