Discourse Parsing

We introduce two probabilistic models that can be used to identify elementary discourse units and build sentence-level discourse parse trees. The models use syntactic and lexical features. A discourse parsing …...

1 In this paper, we describe how the LIDAS System (Linguistic Discourse Analysis Sys- tem), a discourse parser built as an implemen- tation of the Unified Linguistic Discourse Model (U-LDM) …...

Processing discourse connectives is im- portant for tasks such as discourse parsing and generation. For these tasks, it is use- ful to know which connectives can signal the same coherence …...

This paper presents a first-order logic learn- ing approach to determine rhetorical relations between discourse segments. Beyond lin- guistic cues and lexical information, our ap- proach exploits compositional semantics and …...

This paper presents a novel approach to document-based discourse analysis by performing a global A* search over the space of possible structures while optimizing a global criterion over the set …...

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 …...

Text-level discourse parsing remains a challenge. The current state-of-the-art overall accuracy in relation assignment is 55.73%, achieved by Joty et al. (2013). However, their model has a high order of …...

AbstractIn this paper we propose a method of reducing the search space of a discourse parsing process, while keeping unaffected its capacity to generate cohesive and coherent tree structures. The …...

Text-level discourse parsing remains a challenge: most approaches employ fea- tures that fail to capture the intentional, se- mantic, and syntactic aspects that govern discourse coherence. In this paper, we …...

Text-level discourse parsing is notoriously difficult, as distinctions between discourse relations require subtle semantic judg- ments that are not easily captured using standard features. In this paper, we present a …...

Previous researches on Text-level discourse parsing mainly made use of constituency structure to parse the whole document into one discourse tree. In this paper, we present the limitations of constituency …...

Recursive neural models, which use syn- tactic parse trees to recursively generate representations bottom-up, are a popular architecture. However there have not been rigorous evaluations showing for exactly which tasks …...

RST-style document-level discourse parsing remains a difficult task and efficient deep learning models on this task have rarely been presented. In this paper, we propose an attention-based hierarchical neural network …...

AbstractWe experiment with different ways of training LSTM networks to predict RST discourse trees. The main challenge for RST discourse parsing is the limited amounts of training data. We combat …...

AbstractDiscourse parsing is a popular technique widely used in text understanding, sentiment analysis and other NLP tasks. However, for most discourse parsers, the performance varies significantly across different discourse relations. …...

AbstractDiscourse parsing is a challenging task in NLP and plays a crucial role in discourse analysis. To enable discourse analysis for Hindi, Hindi Discourse Relations Bank was created on a …...

AbstractInferring implicit discourse relations in natural language text is the most difficult subtask in discourse parsing. Many neural network models have been proposed to tackle this problem. However, the comparison …...

AbstractDiscourse segmentation is the first step in building discourse parsers. Most work on discourse segmentation does not scale to real-world discourse parsing across languages, for two reasons: (i) models rely …...

AbstractIn order to determine argument structure in text, one must understand how individual components of the overall argument are linked. This work presents the first neural network-based approach to link …...

AbstractDiscourse parsing has long been treated as a stand-alone problem independent from constituency or dependency parsing. Most attempts at this problem rely on annotated text segmentations (Elementary Discourse Units, EDUs) …...

Although discourse parsing is an important and fundamental task in natural language processing, few languages have corpora anno- tated with discourse relations and if any, they are small in size. …...

AbstractDiscourse structure tree construction is the fundamental task of discourse parsing and most previous work focused on English. Due to the cultural and linguistic differences, existing successful methods on English …...

AbstractThe lack of large and diverse discourse treebanks hinders the application of data-driven approaches, such as deep-learning, to RST-style discourse parsing. In this work, we present a novel scalable methodology …...

AbstractRST-based discourse parsing is an important NLP task with numerous downstream applications, such as summarization, machine translation and opinion mining. In this paper, we demonstrate a simple, yet highly accurate …...

AbstractWe introduce a generic seq2seq parsing framework that casts constituency parsing problems (syntactic and discourse parsing) into a series of conditional splitting decisions. Our parsing model estimates the conditional probability …...

AbstractAtomic clauses are fundamental text units for understanding complex sentences. Identifying the atomic sentences within complex sentences is important for applications such as summarization, argument mining, discourse analysis, discourse parsing, …...

Multi-party dialogue machine reading compre- hension (MRC) raises an even more challeng- ing understanding goal on dialogue with more than two involved speakers, compared with the traditional plain passage style …...

AbstractDiscourse parsing on multi-party dialogues is an important but difficult task in dialogue systems and conversational analysis. It is believed that speaker interactions are helpful for this task. However, most …...

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 …...

AbstractRecent advances in discourse parsing performance create the impression that, as in other NLP tasks, performance for high-resource languages such as English is finally becoming reliable. In this paper we …...