Using dialogue corpora to extend information extraction patterns for natural language understanding of dialogue

This work was funded by the Companions project (www.companions-project.org) sponsored by the European Commission as part of the Information Society Technologies (IST) programme under EC grant number IST-FP6-034434.This paper examines how Natural Language Process (NLP) resources and online dialogue corpora can be used to extend coverage of Information Extraction (IE) templates in a Spoken Dialogue system. IE templates are used as part of a Natural Language Understanding module for identifying meaning in a user utterance. The use of NLP tools in Dialogue systems is a difficult task given spoken dialogue is often not well-formed and 2) there is a serious lack of dialogue data. In spite of that, we have devised a method for extending IE patterns using standard NLP tools and available dialogue corpora found on the web. In this paper, we explain our method which includes using a set of NLP modules developed using GATE (a General Architecture for Text Engineering), as well as a general purpose editing tool that we built to facilitate the IE rule creation process. Lastly, we present directions for future work in this area.peer-reviewe

Joint Modeling of Content and Discourse Relations in Dialogues

We present a joint modeling approach to identify salient discussion points in spoken meetings as well as to label the discourse relations between speaker turns. A variation of our model is also discussed when discourse relations are treated as latent variables. Experimental results on two popular meeting corpora show that our joint model can outperform state-of-the-art approaches for both phrase-based content selection and discourse relation prediction tasks. We also evaluate our model on predicting the consistency among team members' understanding of their group decisions. Classifiers trained with features constructed from our model achieve significant better predictive performance than the state-of-the-art.Comment: Accepted by ACL 2017. 11 page

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Design of a Controlled Language for Critical Infrastructures Protection

We describe a project for the construction of controlled language for critical infrastructures protection (CIP). This project originates from the need to coordinate and categorize the communications on CIP at the European level. These communications can be physically represented by official documents, reports on incidents, informal communications and plain e-mail. We explore the application of traditional library science tools for the construction of controlled languages in order to achieve our goal. Our starting point is an analogous work done during the sixties in the field of nuclear science known as the Euratom Thesaurus.JRC.G.6-Security technology assessmen

Systemic-functional linguistics and computation : New directions, new challenges

Peer reviewe

Dialogue-Based Relation Extraction

We present the first human-annotated dialogue-based relation extraction (RE) dataset DialogRE, aiming to support the prediction of relation(s) between two arguments that appear in a dialogue. We further offer DialogRE as a platform for studying cross-sentence RE as most facts span multiple sentences. We argue that speaker-related information plays a critical role in the proposed task, based on an analysis of similarities and differences between dialogue-based and traditional RE tasks. Considering the timeliness of communication in a dialogue, we design a new metric to evaluate the performance of RE methods in a conversational setting and investigate the performance of several representative RE methods on DialogRE. Experimental results demonstrate that a speaker-aware extension on the best-performing model leads to gains in both the standard and conversational evaluation settings. DialogRE is available at https://dataset.org/dialogre/.Comment: To appear in ACL 202