Fine-grained discourse structures in continuation semantics

International audienceIn this work, we are interested in the computation of logical representations of discourse. We argue that all discourse connectives are anaphors obeying different sets of constraints and show how this view allows one to account for the semantically parenthetical use of attitude verbs and verbs of report (e.g., think, say) and for sequences of conjunctions (A CONJ 1 B CONJ 2 C). We implement this proposal in event semantics using de Groote (2006)’s dynamic framework

Testing SDRT's Right Frontier

The Right Frontier Constraint (RFC), as a constraint on the attachment of new constituents to an existing discourse structure, has important implications for the interpretation of anaphoric elements in discourse and for Machine Learning (ML) approaches to learning discourse structures. In this paper we provide strong empirical support for SDRT's version of RFC. The analysis of about 100 doubly annotated documents by five different naive annotators shows that SDRT's RFC is respected about 95% of the time. The qualitative analysis of presumed violations that we have performed shows that they are either click-errors or structural misconceptions

The BURCHAK corpus: a Challenge Data Set for Interactive Learning of Visually Grounded Word Meanings

We motivate and describe a new freely available human-human dialogue dataset for interactive learning of visually grounded word meanings through ostensive definition by a tutor to a learner. The data has been collected using a novel, character-by-character variant of the DiET chat tool (Healey et al., 2003; Mills and Healey, submitted) with a novel task, where a Learner needs to learn invented visual attribute words (such as " burchak " for square) from a tutor. As such, the text-based interactions closely resemble face-to-face conversation and thus contain many of the linguistic phenomena encountered in natural, spontaneous dialogue. These include self-and other-correction, mid-sentence continuations, interruptions, overlaps, fillers, and hedges. We also present a generic n-gram framework for building user (i.e. tutor) simulations from this type of incremental data, which is freely available to researchers. We show that the simulations produce outputs that are similar to the original data (e.g. 78% turn match similarity). Finally, we train and evaluate a Reinforcement Learning dialogue control agent for learning visually grounded word meanings, trained from the BURCHAK corpus. The learned policy shows comparable performance to a rule-based system built previously.Comment: 10 pages, THE 6TH WORKSHOP ON VISION AND LANGUAGE (VL'17

Evaluating Scoped Meaning Representations

Semantic parsing offers many opportunities to improve natural language understanding. We present a semantically annotated parallel corpus for English, German, Italian, and Dutch where sentences are aligned with scoped meaning representations in order to capture the semantics of negation, modals, quantification, and presupposition triggers. The semantic formalism is based on Discourse Representation Theory, but concepts are represented by WordNet synsets and thematic roles by VerbNet relations. Translating scoped meaning representations to sets of clauses enables us to compare them for the purpose of semantic parser evaluation and checking translations. This is done by computing precision and recall on matching clauses, in a similar way as is done for Abstract Meaning Representations. We show that our matching tool for evaluating scoped meaning representations is both accurate and efficient. Applying this matching tool to three baseline semantic parsers yields F-scores between 43% and 54%. A pilot study is performed to automatically find changes in meaning by comparing meaning representations of translations. This comparison turns out to be an additional way of (i) finding annotation mistakes and (ii) finding instances where our semantic analysis needs to be improved.Comment: Camera-ready for LREC 201

On the limits of the Davidsonian approach : the case of copula sentences

Since Donald Davidson’s seminal work “The Logical Form of Action Sentences” (1967) event arguments have become an integral component of virtually every semantic theory. Over the past years Davidson´s proposal has been continuously extended such that nowadays event(uality) arguments are generally associated not only with action verbs but with predicates of all sorts. The reasons for such an extension are seldom explicitly justified. Most problematical in this respect is the case of stative expressions. By taking a closer look at copula sentences the present study assesses the legitimacy of stretching the Davidsonian notion of events and discusses its consequences. A careful application of some standard eventuality diagnostics (perception reports, combination with locative modifiers and manner adverbials) as well as some new diagnostics (behavior of certain degree adverbials) reveals that copular expressions do not behave as expected under a Davidsonian perspective: they fail all eventuality tests, regardless of whether they represent stage-level or individual-level predicates. In this respect, copular expressions pattern with stative verbs like know, hate, and resemble, which in turn differ sharply from state verbs like stand, sit, and sleep. The latter pass all of the eventuality tests and therefore qualify as true “Davidsonian state” expressions. On the basis of these empirical observations and taking up ideas of Kim (1969, 1976) and Asher (1993, 2000), an alternative account of copular expressions (and stative verbs) is provided, according to which the copula introduces a referential argument for a temporally bound property exemplification (= “Kimian state”). Considerations on some logical properties, viz. closure conditions and the latent infinite regress of eventualities, suggest that supplementing Davidsonian eventualities with Kimian states may yield not only a more adequate analysis of copula sentences but also a better understanding of eventualities in general

This research topic of yours – is it a research topic at all? Using comparative interactional data for a fine-grained reanalysis of traditional concepts

This paper demonstrates how bottom-up research on interactional data offers the opportunity of disentangling presumably basic linguistic notions into smaller primitives. Using parallel case studies on interrogatives and left dislocations from two unrelated languages (Modern Hebrew and Anal Naga), the paper shows how avoiding restrictive definitions and recurrently expanding the set of examples results in a revision of concepts, taken for granted at the beginning of the study. The findings emphasise the need for channelling corpus-based research into an interactionally-informed examination of the metalanguage employed for the analysis. They illustrate how studying a research topic and questioning the validity of the concepts that underlie it are part of the same process

Unsupervised extraction of semantic relations using discourse cues

International audienceThis paper presents a knowledge base containing triples involving pairs of verbs associated with semantic or discourse relations. The relations in these triples are marked by discourse connectors between two adjacent instances of the verbs in the triple in the large French corpus, frWaC. We detail several measures that evaluate the relevance of the triples and the strength of their association. We use manual annotations to evaluate our method, and also study the coverage of our resource with respect to the discourse annotated corpus Annodis. Our positive results show the potential impact of our resource for discourse analysis tasks as well as other semantically oriented tasks like temporal and causal information extractio

Towards interoperable discourse annotation: discourse features in the Ontologies of Linguistic Annotation

This paper describes the extension of the Ontologies of Linguistic Annotation (OLiA) with respect to discourse features. The OLiA ontologies provide a a terminology repository that can be employed to facilitate the conceptual (semantic) interoperability of annotations of discourse phenomena as found in the most important corpora available to the community, including OntoNotes, the RST Discourse Treebank and the Penn Discourse Treebank. Along with selected schemes for information structure and coreference, discourse relations are discussed with special emphasis on the Penn Discourse Treebank and the RST Discourse Treebank. For an example contained in the intersection of both corpora, I show how ontologies can be employed to generalize over divergent annotation schemes