Search Results for author: Marco Rospocher

Found 6 papers, 1 papers with code

A formalisation of BPMN in Description Logics

no code implementations22 Sep 2021 Chiara Ghidini, Marco Rospocher, Luciano Serafini

In this paper we present a textual description, in terms of Description Logics, of the BPMN Ontology, which provides a clear semantic formalisation of the structural components of the Business Process Modelling Notation (BPMN), based on the latest stable BPMN specifications from OMG [BPMN Version 1. 1 -- January 2008].

GRaSP: Grounded Representation and Source Perspective

1 code implementation RANLP 2017 Antske Fokkens, Piek Vossen, Marco Rospocher, Rinke Hoekstra, Willem Robert van Hage

When people or organizations provide information, they make choices regarding what information they include and how they present it.

On Coreferring Text-extracted Event Descriptions with the aid of Ontological Reasoning

no code implementations1 Dec 2016 Stefano Borgo, Loris Bozzato, Alessio Palmero Aprosio, Marco Rospocher, Luciano Serafini

Systems for automatic extraction of semantic information about events from large textual resources are now available: these tools are capable to generate RDF datasets about text extracted events and this knowledge can be used to reason over the recognized events.

Using Recurrent Neural Network for Learning Expressive Ontologies

no code implementations14 Jul 2016 Giulio Petrucci, Chiara Ghidini, Marco Rospocher

Recently, Neural Networks have been proven extremely effective in many natural language processing tasks such as sentiment analysis, question answering, or machine translation.

Machine Translation Question Answering +2

The Event and Implied Situation Ontology (ESO): Application and Evaluation

no code implementations LREC 2016 Roxane Segers, Marco Rospocher, Piek Vossen, Egoitz Laparra, German Rigau, Anne-Lyse Minard

This paper presents the Event and Implied Situation Ontology (ESO), a manually constructed resource which formalizes the pre and post situations of events and the roles of the entities affected by an event.

PreMOn: a Lemon Extension for Exposing Predicate Models as Linked Data

no code implementations LREC 2016 Francesco Corcoglioniti, Marco Rospocher, Alessio Palmero Aprosio, Sara Tonelli

We introduce PreMOn (predicate model for ontologies), a linguistic resource for exposing predicate models (PropBank, NomBank, VerbNet, and FrameNet) and mappings between them (e. g, SemLink) as Linked Open Data.

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