[Seminar] Prof. Sabine Schulte im Walde 🗓

Event Date: Tuesday, 8 October, 2019

Location: 12:00-14:00, Sala Colonne, Pal. Venera

Speaker: Prof. Sabine Schulte im Walde (IMS, University of Stuttgart)

Title: Distributional Semantic Spaces and Classification Models of Abstractness and Figurative Language

Abstract: Distributional models assume that the contexts of a linguistic unit (such as a word, a multi-word expression, a phrase, a sentence, etc.) provide information about the meaning of the linguistic unit (Harris, 1954; Firth, 1957). They have been widely applied in data-intensive lexical semantics (among other areas), and proven successful in diverse research issues, such as the representation and disambiguation of word senses; selectional preference modelling; the compositionality
of compounds and phrases, or as a general framework across semantic tasks.
In this talk, I will present ongoing work that explores distributional models and multi-modal extensions for abstractness as well as for figurative meanings of German particle verbs (PVs) in context. In the first part of the talk, I will introduce classifiers for (non-)literal PV sentences, which heavily rely on distributional and abstractness/concreteness information. Furthermore, I will demonstrate the interaction between affective information and analogies in PV meaning shifts. In the second part of the talk, I will zoom into contextual characteristics of the underlying abstractness information, and the interplay between abstractness and figurative language.

Sabine Schulte im Walde is an associate professor at the Institute for Natural Language Processing at the University of Stuttgart in Germany. She performed her Master studies at the Universities of Stuttgart and Edinburgh and received a PhD in Computational Linguistics in 2003 from the University of Stuttgart and the Venia Legendi (habilitation) from Saarland University in 2009. From 2003-2004 she worked for the lexicographer Duden in Mannheim, Germany, and from 2011-2016 she was a Heisenberg Fellow. Her research applies data-intensive, statistical methods to linguistic questions, with a focus on the syntax-semantics interface and lexical-semantic phenomena. As a main challenge she considers the linguistic and cognitive plausibility of the approaches with respect to the tasks. The topics of her research include the automatic induction of semantic classifications and semantic relations; compositionality and meaning shifts of multi-word expressions; synchronic and diachronic ambiguity and figurative language usage; and the evaluation of corpus-based semantic knowledge.