A Neural Approach to Discourse Relation Signal Detection

Previous data-driven work investigating the types and distributions of discourse relation signals, including discourse markers such as 'however' or phrases such as 'as a result' has focused on the relative frequencies of signal words within and outside text from each discourse relation. Such approaches do not allow us to quantify the signaling strength of individual instances of a signal on a scale (e.g. more or less discourse-relevant instances of 'and'), to assess the distribution of ambiguity for signals, or to identify words that hinder discourse relation identification in context ('anti-signals' or 'distractors'). In this paper we present a data-driven approach to signal detection using a distantly supervised neural network and develop a metric, Δs (or 'delta-softmax'), to quantify signaling strength. Ranging between -1 and 1 and relying on recent advances in contextualized words embeddings, the metric represents each word's positive or negative contribution to the identifiability of a relation in specific instances in context. Based on an English corpus annotated for discourse relations using Rhetorical Structure Theory and signal type annotations anchored to specific tokens, our analysis examines the reliability of the metric, the places where it overlaps with and differs from human judgments, and the implications for identifying features that neural models may need in order to perform better on automatic discourse relation classification

Signaling of Causal Relations in Spanish: Variety, Functionality, and Specificity

While some recent studies on Spanish have shown that some causal discourse markers specialize in expressing certain types of causal relations, others have revealed that causal relations may be signaled by a variety of linguistic devices. Given that we were interested not only in specificity and variety, but also in the (poly) functionality of signals, our objective in the present study was threefold. First, to identify the variety of markers used to signal causal relations in Spanish. Second, to describe the (poly) functionality of those causal markers. Third, to determine whether there exists a relationship of specificity between markers and particular types of causal relations. We analyzed a corpus of 2,514 causal coherence relations previously annotated. 40 different linguistic devices used to signal causal relations were identified. These devices were grouped into two main classes: Discourse Markers and Cue Phrases. Regarding the (poly) functionality of the markers, we found that 8 of the most frequent markers were used to signal different relations. Regarding specificity, it was observed that various conjunctions and conjunctive adverbs specialize in signaling specific relations

The timing of prominence information during the resolution of German personal and demonstrative pronouns

German personal and demonstrative pronouns have distinct preferences in their interpretation; personal pronouns are more flexible in their interpretation but tend to resolve to a prominent antecedent, while demonstratives have a strong preference for a non-prominent antecedent. However, less is known about how prominence information is used during the process of resolution, particularly in the light of two- stage processing models which assume that reference will normally be to the most accessible candidate. We conducted three experiments investigating how prominence information is used during the resolution of gender-disambiguated personal and demonstrative pronouns in German. While the demonstrative pronoun required additional processing compared to the personal pronoun, prominence information did not affect resolution in shallow conditions. It did, however, affect resolution under deep processing conditions. We conclude that prominence information is not ruled out by the presence of stronger resolution cues such as gender. However, the deployment of prominence information in the evaluation of candidate antecedents is under strategic control

From Discursive Practice to Logic? Remarks on Logical Expressivism

This paper investigates Robert Brandom's programme of logical expressivism and in the processattempts to clarify his use of the term practice, by means of a comparison with the works of sociologistand anthropologist Pierre Bourdieu. The key claim of logical expressivisim is the ideathat logical terms serve to make explicit the inferential relations between statements which alreadyhold implicitly in a discursive practice that lacks such terms in its vocabulary. Along with this, itis claimed that the formal validity of an argument is derivative on so-called material inference, inthat an inference is taken to be logically valid only if it is a materially good inference and cannotbe made into a bad inference by substituting nonlogical for nonlogical vocabulary in its premisesand conclusion. We note that no systematic account of logical validity employing this substitutionalmethod has been offered to date; rather, proposals by e.g. Lance and Kremer, Piwek, Kibbleand Brandom himself have followed the more conventional path of developing a formally definedsystem which is informally associated with natural language examples. We suggest a number of refinementsto Brandom’s account of conditionals and of validity, supported by analysis of linguisticexamples including material from the SNLI and MultiNLI corpora and a review of relevant literature.The analysis suggests that Brandom’s expressivist programme faces formidable challengesonce exposed to a wide range of linguistic data, and may not in fact be realisable owing to thepervasive context-dependence of linguistic expressions, including 'logical' vocabulary. A furtherclaim of this paper is that a purely assertional practice may not provide an adequate basis for conditionalreasoning, but that a more promising route is provided by the introduction of imperatives,as in so-called "pseudo-imperatives" such as "Get individuals to invest their time and the fundingwill follow". We conclude the resulting dialogical analysis of conditional reasoning is faithful toBrandom's Sellarsian intuition of linguistic practice as a game of giving and asking for reasons, andconjecture that language is best analysed not as a system of rules but as a Wittgensteinian repertoireof evolving micro-practices

Comparing discourse structures between purely linguistic and situated messages in an annotated corpus

This paper describes a corpus of situated multiparty chats developed for the STAC project (Strategic Conversation, ERC grant n. 269427). and annotated for discourse structure in the style of Segmented Discourse Representation Theory (SDRT; Asher & Lascarides,2003).  The STAC corpus is not only a rich source of data on strategic conversation, but also the first corpus that we are aware of that provides discourse structures for multiparty dialogues situated within a virtual environment.  The corpus was annotated in two stages: we initially annotated the chat moves only, but later decided to annotate interactions between the chat moves and non-linguistic events from the virtual environment. This two-step procedure  has allowed us quantify various ways in which adding information from the nonlinguistic context affects dialogue structure.  In this paper, we  look at how annotations based only on linguistic information were preserved once the nonlinguistic context was factored in.  We explain that while the preservation of relation instances is relatively high when we move from one corpus to the other, there is little preservation of higher order structures  that capture ``the main point" of a dialogue and distinguish it from peripheral information

The Use of Perspective Markers and Connectives in Expressing Subjectivity: Evidence from Collocational Analyses

This study explores how subjectivity is expressed in coherence relations, by means of a distinctive collocational analysis on two Chinese causal connectives: the specific subjective kejian ‘so’, used in subjective argument-claim relations, and the underspecified suoyi ‘so’, which can be used in both subjective argument-claim and objective cause-consequence relations. On the basis of both Horn’s pragmatic Relation and Quality principles and the Uniform Information Density Theory, we hypothesized that the presence of other linguistic elements expressing subjectivity in a discourse segment should be related the degree of subjectivity encoded by the connective. In line with this hypothesis, the association scores showed that suoyi is more frequently combined with perspective markers expressing epistemic stance: cognition verbs and modal verbs. Kejian, which already expresses epistemic stance, co-occurred more often with perspective markers related to attitudinal stance, such as markers of expectedness and importance. The paper also pays attention to similarities and differences in collocation patterns across contexts and genres

How compatible are our discourse annotation frameworks? Insights from mapping RST-DT and PDTB annotations

Discourse-annotated corpora are an important resource for the community, but they are often annotated according to different frameworks. This makes joint usage of the annotations difficult, preventing researchers from searching the corpora in a unified way, or using all annotated data jointly to train computational systems. Several theoretical proposals have recently been made for mapping the relational labels of different frameworks to each other, but these proposals have so far not been validated against existing annotations. The two largest discourse relation annotated resources, the Penn Discourse Treebank and the Rhetorical Structure Theory Discourse Treebank, have however been annotated on the same texts, allowing for a direct comparison of the annotation layers. We propose a method for automatically aligning the discourse segments, and then evaluate existing mapping proposals by comparing the empirically observed against the proposed mappings. Our analysis highlights the influence of segmentation on subsequent discourse relation labelling, and shows that while agreement between frameworks is reasonable for explicit relations, agreement on implicit relations is low. We identify several sources of systematic discrepancies between the two annotation schemes and discuss consequences for future annotation and for usage of the existing resources

Reinforcement adaptation of an attention-based neural natural language generator for spoken dialogue systems

Following some recent propositions to handle natural language generation in spoken dialogue systems with long short-term memory recurrent neural network models~\citep{Wen2016a} we first investigate a variant thereof with the objective of a better integration of the attention subnetwork. Then our next objective is to propose and evaluate a framework to adapt the NLG module online through direct interactions with the users. When doing so the basic way is to ask the user to utter an alternative sentence to express a particular dialogue act. But then the system has to decide between using an automatic transcription or to ask for a manual transcription. To do so a reinforcement learning approach based on an adversarial bandit scheme is retained. We show that by defining appropriately the rewards as a linear combination of expected payoffs and costs of acquiring the new data provided by the user, a system design can balance between improving the system's performance towards a better match with the user's preferences and the burden associated with it. Then the actual benefits of this system is assessed with a human evaluation, showing that the addition of more diverse utterances allows to produce sentences more satisfying for the user

A Narrative Sentence Planner and Structurer for Domain Independent, Parameterizable Storytelling

Storytelling is an integral part of daily life and a key part of how we share information and connect with others. The ability to use Natural Language Generation (NLG) to produce stories that are tailored and adapted to the individual reader could have large impact in many different applications. However, one reason that this has not become a reality to date is the NLG story gap, a disconnect between the plan-type representations that story generation engines produce, and the linguistic representations needed by NLG engines. Here we describe Fabula Tales, a storytelling system supporting both story generation and NLG. With manual annotation of texts from existing stories using an intuitive user interface, Fabula Tales automatically extracts the underlying story representation and its accompanying syntactically grounded representation. Narratological and sentence planning parameters are applied to these structures to generate different versions of the story. We show how our storytelling system can alter the story at the sentence level, as well as the discourse level. We also show that our approach can be applied to different kinds of stories by testing our approach on both Aesop’s Fables and first-person blogs posted on social media. The content and genre of such stories varies widely, supporting our claim that our approach is general and domain independent. We then conduct several user studies to evaluate the generated story variations and show that Fabula Tales’ automatically produced variations are perceived as more immediate, interesting, and correct, and are preferred to a baseline generation system that does not use narrative parameters

Visual attention-capture cue in depicted scenes fails to modulate online sentence processing

Everyday communication is enriched by the visual environment that listeners concomitantly link to the linguistic input. If and when visual cues are integrated into the mental meaning representation of the communicative setting, is still unclear. In our earlier findings, the integration of linguistic cues (i.e., topic-hood of a discourse referent) reduced discourse updating costs of the mental representation as indicated by reduced sentence-initial processing costs of the non-canonical word order in German. In the present study we tried to replicate our earlier findings by replacing the linguistic cue by a visual attention-capture cue presented below the threshold of perception in order to direct participant’s attention to a depicted referent. While this type of cue has previously been shown to modulate word order preferences in sentence production, we found no effects on sentence comprehension. We discuss possible theory-based reasons for the null effect of the implicit visual cue as well as methodological caveats and issues that should be considered in future research on multimodal meaning integration