Пеннский дискурсивный банк

The annotations of the Penn Discourse Treebank (PDTB) include (1) discourse connectives and their arguments, and (2) attribution of each argument of each con- nective and of the relation it …...

AbstractIn this paper, we make a qualitative and quantitative analysis of discourse relations within the LUNA conversational spoken dialog corpus. In particular, we first describe the Penn Discourse Treebank (PDTB) …...

The annotations of explicit and implicit discourse connectives in the Penn Discourse Treebank make it possible to investigate on a large scale how different types of discourse relations are expressed. …...

We present a classification model that predicts the presence or omission of a lexical connec- tive between two clauses, based upon linguis- tic features of the clauses and the type …...

Discourse parsing is a challenging task and plays a critical role in discourse anal- ysis. In this paper, we focus on label- ing full argument spans of discourse con- nectives …...

Previous work by Lin et al. (2011) demonstrated the effectiveness of using discourse relations for evaluating text coherence. However, their work was based on discourse relations annotated in accordance with …...

Word pairs, which are one of the most eas- ily accessible features between two text segments, have been proven to be very useful for detecting the discourse relations held between …...

AbstractLearning effective representations of sentences is one of the core missions of natural language understanding. Existing models either train on a vast amount of text, or require costly, manually curated …...

AbstractWe tackle implicit discourse relation recognition. Both self-attention and interactive-attention mechanisms have been applied for attention-aware representation learning, which improves the current discourse analysis models. To take advantages of the …...

AbstractIn this paper, we report on our experiments towards the creation of a corpus for coherence evaluation. Most corpora for textual coherence evaluation are composed of randomly shuffled sentences that …...

AbstractImplicit discourse relation recognition is a challenging task due to the lack of connectives as strong linguistic clues. Previous methods primarily encode two arguments separately or extract the specific interaction …...

AbstractWe tackle implicit discourse relation classification, a task of automatically determining semantic relationships between arguments. The attention-worthy words in arguments are crucial clues for classifying the discourse relations. Attention mechanisms …...

AbstractRepresenting, and reasoning over, long narratives requires models that can deal with complex event structures connected through multiple relationship types. This paper suggests to represent this type of information as …...

AbstractDiscourse parsing has proven to be useful for a number of NLP tasks that require complex reasoning. However, over a decade since the advent of the Penn Discourse Treebank, predicting …...

AbstractThe task of shallow discourse parsing in the Penn Discourse Treebank (PDTB) framework has traditionally been restricted to identifying those relations that are signaled by a discourse connective (“explicit”) and …...

AbstractIn this paper, we investigate the relationship between the use of discourse relations and the CEFR-level of argumentative English learner essays. Using both the Rhetorical Structure Theory (RST) and the …...