Courses' slots:
Week two 9:00 - 10:30
Language and Logic introductory course:
Topics in the Semantics of Interrogative Clauses.
Teachers
Abstract: The purpose of the class is to present in a systematic way some of the most influential lines of investigations pertaining to the semantics of questions. We will start by presenting two related types of theories, namely theories based on "sets of answers" (Hamblin 1973, Karttunen 1977), on the one hand, and theories based on "partition semantics", on the other hand (Gronendijk & Stockhof 1982, 1984), and discuss their strengths and weaknesses. This will lead us to an extensive discussion of embedded interrogatives (including topics such as weak and strong exhaustivity in relation to NPI licensing, the distinction between de dicto and de re readings, extensional vs. intensional question embedding predicates, quantificational variability). We will provide a compositional account of the meaning of wh-questions, which will allow us to address more specific topics such as identity questions, functional and pair-list readings of wh-questions, alternative questions.
Language and Computation advanced course:
Psycho-computational issues in Morphology Learning and Processing.
Teacher
- Vito Pirrelli ()
By providing a comprehensive overview of current machine-learning, psycholinguistic and theoretical linguistic literature on the topic, the course is intended to answer the following questions. How are words singled out of their embedding input stream? How are they processed and eventually understood in working memory? Are morphologically complex words stored in long-term memory as a whole or are they rather composed "on-line" in working memory from sub-lexical constituents? Do formal regularity and morpho-semantic transparency play any role in this? Does word-level knowledge require parallel development of form and meaning representations, or do the latter develop independently at a different pace to interact only at later stages? To what extent does past knowledge affect on-line word processing? What principles govern this knowledge? Are they morphology-specific or are they rather based on brain memory structures generically devoted to the ordered activation of items in time? Do they capture local, syntagmatic relations among sub-lexical co-occurring constituents, or also enforce more global paradigmatic constraints over classes of such constituents in complementary distribution?
Language and Logic foundational course:
Meaning Composition: Empricial Problems and Formal Solutions.
Teacher
Abstract:
This course provides an overview two of the main empirical
problems that have emerged in the development of models for
meaning composition in natural language, the tradeoffs that are
involved in solving these problems, and some of the different
techniques that have been proposed as solutions. The goal is
twofold: to make students with logic backgrounds aware of the
reasons why the composition of natural language meanings is not
a trivial problem (even though at some levels it might seem that
way), and to familiarize students with linguistics backgrounds
with some of the main alternative techniques for meaning
composition, their similarities and differences, and their pros
and cons. The course will presuppose only a minimal familiarity
with basic grammatical concepts and predicate logic.
An elegant theory of meaning composition for natural language
might be expected to meet the following desiderata, among
others:
-It should respect independently-motivated results of research
on morphology, syntax, and the lexicon.
- It should be grounded in an independently motivated theory of
what lexical meanings are like.
- It should avoid idiosyncratic composition rules to the extent
possible.
- It should be expressible in a sound and computationally
tractable logic.
However, natural language data sometimes make a maximally
elegant theory difficult. Perhaps the best-studied problem for
the meaning composition in this respect has been
quantification. In this course, we will focus on two additional
problems which have driven various kinds of alternative meaning
composition strategies: bare nominals and incorporation on the
one hand, and so-called "intersective"
vs. "nonintersective" modification, on the other. We will
develop a sense of the general nature of the problems these
phenomena pose, as well as a global vision of the issues the
proposed solutions raise.
The plan for the course is the following:
Day 1: The basics: Classic "rule-to-rule"
vs. "shake-and-bake" approaches to
composition. [Discussion of work by Bach, Carpenter, Dowty,
Klein & Sag, Montague, and others]
Days 2-3: The empirical problem: Bare nominals and
incorporation. The solutions: type shifting, the separation of
syntactic and semantic saturation, Discourse Representation
Theory-based alternatives. [Discussion of work by Chung &
Ladusaw, Dayal, de Hoop, Espinal & McNally, Farkas & de Swart,
Kamp, Partee, Van Geenhoven, and others]
Days 4-5: The empirical problem: Intersective
vs. nonintersective modification. The solutions: type coercion,
enriched lexical representations, ad-hoc composition
rules. [Discussion of work by Asher, Larson, McNally, Montague,
Pustejovsky, and others]
Language and Computation introductory course:
Standard XML query languages for natural language processing.
Teacher
Course material: u_schaefer_xml_query.pdf
Abstract:This course will introduce three standard XML query languages that have been designed by the World Wide Web Consortium (W3C), XPath, XSLT and XQuery. Although various query languages have been proposed and developed for accessing annotated corpora, they are often tailored to specific formats and phenomena. This course will focus on the standard query languages for which multiple and very efficient implementations exist that run on almost any platform. Applications and examples are presented not only for corpus access, but also other NLP-related tasks such as accessing RDF ontologies and integrating NLP component output. Finally, the course will also briefly show the frameworks that are used to embed the query languages in popular programming languages.
Logic and Computation advanced course:
Ontologies: Structuring, Modularity, and Heterogeneity.
Teachers
- Stefano Borgo ()
- Oliver Kutz ()
The design of formal ontologies is an interdisciplinary area of
research that draws on logic, philosophy, cognitive science,
linguistics, as well as computer science, with major
applications in the Semantic Web. As the scope and relevance of
ontologies grows, both for supporting Semantic Web applications
and for knowledge-rich processing in general, the issue of
re-using/importing developed ontological components takes on an
ever more critical role. The current solutions being pursued
within OWL-oriented Semantic Web approaches have some severe
limitations in this respect. For the next generation of
ontology-based systems, it will be essential to move beyond
this.
To achieve this, we present major methodologies and techniques
to correctly construct, modify, and relate ontologies -
understood in a broad sense as logical theories formulated in
various formal languages - with an emphasis on heterogeneity,
structuring and modularity, as well as foundations of ontology
design. As illustrative examples, we will discuss prominent
ontologies from the spatial, philosophical and linguistic
domains. These will be analysed and structured using the Common
Algebraic Specification Language (CASL), and shown 'at
work' employing the tool HeTS, offering (heterogeneous)
reasoning support for structured ontologies and providing
powerful new mechanisms for reusing ontological components or
modules. A Live-CD for hands-on experimentation with HeTS will
be distributed to all participants.
Logic and Computation foundational course:
Logics of Rational Agency.
Teacher
- Eric Pacuit ()
Course material: lori-notes.pdf
Abstract:
Thinking about rational agents interacting over time is at the
center of many research communities represented at ESSLLI. This
course will introduce the main research themes and conceptual
issues surrounding rational agency. The primary objective is to
understand the complex phenomena that arise when rational
agents interact and how to incorporate these phenomena into
formal models. Studying rational agents involves many different
aspects including (but not limited to) action, knowledge,
belief, desires, and revision. This course covers all these
ingredients toward the goal of understanding how these things
work together. Specific topics that will be introduced during
the course include 1. logics of knowledge and belief,
2. information dynamics and belief revision, 3. logics of
preference and preference change, 4. logics of motivational
mental attitudes, and 5. logics of individual and collective
action and 6. group phenomena and issues of social choice. In
fact, not all parts of this story have been developed within
one single discipline. The course will also bring together
several research programs: from philosophy, computer science,
logic, and game theory, and try to see their various
contributions in one coherent manner.
http://ai.stanford.edu/~epacuit/classes/esslli/log-ratagency.html