Crowd-Sourcing A High-Quality Dataset for Metaphor Identification in Tweets

Metaphor is one of the most important elements of human communication, especially in informal settings such as social media. There have been a number of datasets created for metaphor identification, however, this task has proven difficult due to the nebulous nature of metaphoricity. In this paper, we present a crowd-sourcing approach for the creation of a dataset for metaphor identification, that is able to rapidly achieve large coverage over the different usages of metaphor in a given corpus while maintaining high accuracy. We validate this methodology by creating a set of 2,500 manually annotated tweets in English, for which we achieve inter-annotator agreement scores over 0.8, which is higher than other reported results that did not limit the task. This methodology is based on the use of an existing classifier for metaphor in order to assist in the identification and the selection of the examples for annotation, in a way that reduces the cognitive load for annotators and enables quick and accurate annotation. We selected a corpus of both general language tweets and political tweets relating to Brexit and we compare the resulting corpus on these two domains. As a result of this work, we have published the first dataset of tweets annotated for metaphors, which we believe will be invaluable for the development, training and evaluation of approaches for metaphor identification in tweets

Charge Pumping in Carbon Nanotubes

We demonstrate charge pumping in semiconducting carbon nanotubes by a traveling potential wave. From the observation of pumping in the nanotube insulating state we deduce that transport occurs by packets of charge being carried along by the wave. By tuning the potential of a side gate, transport of either electron or hole packets can be realized. Prospects for the realization of nanotube based single-electron pumps are discussed

A Quantum Dot in the Kondo Regime Coupled to Superconductors

The Kondo effect and superconductivity are both prime examples of many-body phenomena. Here we report transport measurements on a carbon nanotube quantum dot coupled to superconducting leads that show a delicate interplay between both effects. We demonstrate that the superconductivity of the leads does not destroy the Kondo correlations on the quantum dot when the Kondo temperature, which varies for different single-electron states, exceeds the superconducting gap energy

An Architecture for Data and Knowledge Acquisition for the Semantic Web: the AGROVOC Use Case

We are surrounded by ever growing volumes of unstructured and weakly-structured information, and for a human being, domain expert or not, it is nearly impossible to read, understand and categorize such information in a fair amount of time. Moreover, different user categories have different expectations: final users need easy-to-use tools and services for specific tasks, knowledge engineers require robust tools for knowledge acquisition, knowledge categorization and semantic resources development, while semantic applications developers demand for flexible frameworks for fast and easy, standardized development of complex applications. This work represents an experience report on the use of the CODA framework for rapid prototyping and deployment of knowledge acquisition systems for RDF. The system integrates independent NLP tools and custom libraries complying with UIMA standards. For our experiment a document set has been processed to populate the AGROVOC thesaurus with two new relationships

Reviewing the problem of learning non-taxonomic relationships of ontologies from text

Learning Non-Taxonomic Relationships is a sub-field of Ontology Learning that aims at automating the extraction of these relationships from text. This article discusses the problem of Learning Non-Taxonomic Relationships of ontologies and proposes a generic process for approaching it. Some techniques representing the state of the art of this field are discussed along with their advantages and limitations. Finally, a framework for Learning Non- Taxonomic Relationships being developed by the authors is briefly discussed. This framework intends to be a customizable solution to reach good effectiveness in the process of extraction of non-taxonomic relationships according to the characteristics of the corpus.This work is supported by CNPq, CAPES and FAPEMA, research funding agencies of the Brazilian government

An Introduction to Ontologies and Ontology Engineering

In the last decades, the use of ontologies in information systems has become more and more popular in various fields, such as web technologies, database integration, multi agent systems, natural language processing, etc. Artificial intelligent researchers have initially borrowed the word “ontology” from Philosophy, then the word spread in many scientific domain and ontologies are now used in several developments. The main goal of this chapter is to answer generic questions about ontologies, such as: Which are the different kinds of ontologies? What is the purpose of the use of ontologies in an application? Which methods can I use to build an ontology

Spectroscopic analysis of finite size effects around a Kondo quantum dot

We consider a simple setup in which a small quantum dot is strongly connected to a finite size box. This box can be either a metallic box or a finite size quantum wire.The formation of the Kondo screening cloud in the box strongly depends on the ratio between the Kondo temperature and the box level spacing. By weakly connecting two metallic reservoirs to the quantum dot, a detailed spectroscopic analysis can be performed. Since the transport channels and the screening channels are almost decoupled, such a setup allows an easier access to the measure of finite-size effects associated with the finite extension of the Kondo cloud.Comment: contribution to Les Houches proceeding, ``Quantum magnetism'' 200