A general framework for the annotation of causality based on FrameNet

International audienceWe present here a general set of semantic frames to annotate causal expressions, with a rich lexicon in French and an annotated corpus of about 4000 instances of causal lexical items with their corresponding semantic frames. The aim of our project is to have both the largest possible coverage of causal phenomena in French, across all parts of speech, and have it linked to a general semantic framework such as FN, to benefit in particular from the relations between other semantic frames, e.g., temporal ones or intentional ones, and the underlying upper lexical ontology that enables some forms of reasoning. This is part of the larger ASFALDA French FrameNet project, which focuses on a few different notional domains which are interesting in their own right (Djemaa et al., 2016), including cognitive positions and communication frames. In the process of building the French lexicon and preparing the annotation of the corpus, we had to remodel some of the frames proposed in FN based on English data, with hopefully more precise frame definitions to facilitate human annotation. This includes semantic clarifications of frames and frame elements, redundancy elimination, and added coverage. The result is arguably a significant improvement of the treatment of causality in FN itself

The Dots and the Line. How to Visualize the Argumentative Structure of an Essay

The contribution aims to create a visualization of the argumentative structure of several essays to compare them from their "graphical" characteristics. We, therefore, intend to combine a literary criticism approach with Data Visualization. The case study on which the contribution focuses is the nonfiction production of Italian author Italo Calvino

Connective-Lex: A Web-Based Multilingual Lexical Resource for Connectives

In this paper, we present a tangible outcome of the TextLink network: a joint online database project displaying and linking existing and newly-created lexicons of discourse connectives in multiple languages. We discuss the definition and demarcation of the class of connectives that should be included in such a resource, and present the syntactic, semantic/pragmatic, and lexicographic information we collected. Further, the technical implementation of the database and the search functionality are presented. We discuss how the multilingual integration of several connective lexicons provides added value for linguistic researchers and other users interested in connectives, by allowing crosslinguistic comparison and a direct linking between discourse relational devices in different languages. Finally, we provide pointers for possible future extensions both in breadth (i.e., by adding lexicons for additional languages) and depth (by extending the information provided for each connective item and by strengthening the crosslinguistic links).Nous présentons dans cet article un résultat tangible du réseau TextLink : un projet conjoint de base de données en ligne, qui montre et relie des lexiques, aussi bien existants que créés récemment, de connecteurs discursifs dans plusieurs langues. Nous commençons par considérer la définition et la délimitation de la classe des connecteurs qui devraient être inclus dans une telle ressource, et nous présentons l’information syntaxique, sémantico-pragmatique et lexicographique que nous avons recueillie. D’autre part, l’implémentation technique de cette base de données et les fonctionnalités de recherche qu’elle permet sont aussi décrites. Nous discutons de quelle manière l’intégration multilingue de plusieurs lexiques de connecteurs apporte une valeur ajoutée aux chercheurs en linguistique et aux autres utilisateurs qui s’intéressent aux connecteurs, en permettant de comparer plusieurs langues et de relier directement les connecteurs dans différentes langues. Pour finir, nous donnons des indications quant à une possible extension future en termes d’ampleur (par exemple, en ajoutant des lexiques pour de nouvelles langues) et de profondeur (en augmentant l’information qui est donnée pour chaque connecteur et en renforçant les liens entre lexiques)

Developing a French FrameNet: Methodology and First results

International audienceThe Asfalda project aims to develop a French corpus with frame-based semantic annotations and automatic tools for shallow semantic analysis. We present the first part of the project: focusing on a set of notional domains, we delimited a subset of English frames, adapted them to French data when necessary, and developed the corresponding French lexicon. We believe that working domain by domain helped us to enforce the coherence of the resulting resource, and also has the advantage that, though the number of frames is limited (around a hundred), we obtain full coverage within a given domain

Proceedings

Proceedings of the Workshop on Annotation and Exploitation of Parallel Corpora AEPC 2010. Editors: Lars Ahrenberg, Jörg Tiedemann and Martin Volk. NEALT Proceedings Series, Vol. 10 (2010), 98 pages. © 2010 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/15893

Identifying Causal Relations in Legal Documents with Dependency Syntactic Analysis

This article describes a method for enriching a dependency-based parser with causal connectors. Our specific objective is to identify causal relationships between elementary discourse units in Spanish legal texts. For this purpose, the approach we follow is to search for specific discourse connectives which are taken as causal dependencies relating an effect event (head) with a verbal or nominal cause (dependent). As a result, we turn a specific syntactic parser into a discourse parser aimed at recognizing causal structures

Towards a pragmatic category of conditionals

© 2016 Elsevier B.V. In this paper, we present the benefits of regarding conditionality as a pragmatic phenomenon as compared with approaches based on the syntactic category of a conditional sentence. We propose a pragmatic category of conditionality and justify it using theoretical arguments supported with examples from our database collected from the International Corpus of English-GB. Next, we demonstrate how conditional utterances that pertain to a variety of syntactic constructions can be represented in Default Semantics, a contextualist, truth-conditional approach to utterance meaning. We identify six types of such constructions, using the dimensions of (i) primary vs. secondary meaning (PM/SM index) and (ii) meaning conveyed through sentence structure vs. meaning conveyed at the level of merger representation (WS/σ index). It is concluded that in view of the diversity of constructions through which conditional thoughts are expressed, conditionality is best regarded as a pragmatic (and as such conceptual) category. Finally, we comment on the status of this claim as a potential semantic/pragmatic universal.This is the author accepted manuscript. The final version is available from Elsevier via https://doi.org/10.1016/j.pragma.2016.04.01

Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration\u27s Adverse Event Reporting System Narratives

BACKGROUND: The Food and Drug Administration\u27s (FDA) Adverse Event Reporting System (FAERS) is a repository of spontaneously-reported adverse drug events (ADEs) for FDA-approved prescription drugs. FAERS reports include both structured reports and unstructured narratives. The narratives often include essential information for evaluation of the severity, causality, and description of ADEs that are not present in the structured data. The timely identification of unknown toxicities of prescription drugs is an important, unsolved problem. OBJECTIVE: The objective of this study was to develop an annotated corpus of FAERS narratives and biomedical named entity tagger to automatically identify ADE related information in the FAERS narratives. METHODS: We developed an annotation guideline and annotate medication information and adverse event related entities on 122 FAERS narratives comprising approximately 23,000 word tokens. A named entity tagger using supervised machine learning approaches was built for detecting medication information and adverse event entities using various categories of features. RESULTS: The annotated corpus had an agreement of over .9 Cohen\u27s kappa for medication and adverse event entities. The best performing tagger achieves an overall performance of 0.73 F1 score for detection of medication, adverse event and other named entities. C ONCLUSIONS: In this study, we developed an annotated corpus of FAERS narratives and machine learning based models for automatically extracting medication and adverse event information from the FAERS narratives. Our study is an important step towards enriching the FAERS data for postmarketing pharmacovigilance