Stefan Evert

• Area: LaCo
• Level: I
• Week: 1
• Time: 14:00 – 15:30
• Room: D1.02

News: please check the wordspace wiki for further updates & new data sets

Abstract

Distributional semantic models (DSM) – also known as “word space” or “distributional similarity” models – are based on the assumption that the meaning of a word can (at least to a certain extent) be inferred from its usage, i.e. its distribution in text.  Therefore, these models dynamically build semantic representations of words or other linguistic units in the form of high-dimensional vector spaces, based on a statistical analysis of their distribution across documents, their collocational profiles, their syntactic dependency relations, and other contextual features.  DSMs are a promising technique for solving the lexical acquisition bottleneck by unsupervised learning, and their distributed representation provides a cognitively plausible, robust and flexible architecture for the organisation and processing of semantic information.

This course aims to equip participants with the background knowledge and skills needed to build different kinds of DSM representations and apply them to a wide range of tasks. It will

• introduce the most common DSM architectures and their parameters, as well as prototypical applications;
• equip participants with a basic knowledge of the mathematical techniques needed for the implementation of DSMs, in particular those of matrix algebra;
• show how DSM vectors and distances can be applied to a wide range of practical tasks;
• convey a better understanding of the high-dimensional vector spaces based on empirical studies, visualisation techniques and mathematical arguments; and
• provide an overview of current research on DSMs, available software, evaluation tasks and future trends.

The course follows a hands-on approach, putting a strong emphasis on practical exercises with the help of a user-friendly software packages for R.  Various pre-compiled DSMs and other data sets will be made available to the course participants.  In contrast to other recent courses targeted at compositional semantics, it focuses on the underlying representations of individual words, as an essential basis not only for compositional vector operations but also for many other applications of DSMs.

The course is targeted both at participants who are new to the field and need a comprehensive overview of DSM techniques and applications, and at those who have already worked with DSMs and want to gain a deeper understanding of their parameters and mathematical underpinnings.

Slides

• Day 1: Introduction (slides, handout)
• Day 2: The parameters of a DSM (slides, handout)
• Day 3: Evaluation (slides, handout, exercise)
• Day 4: Elements of matrix algebra – preliminary version (slides, handout)
• Day 5: Practical exercises (exercise)

Note: WordPress doesn’t allow R script files, so the exercises and worked examples have been uploaded as plain text files. Please remove the extension .txt so they will be recognized by RStudio as R script files (.R).

Software & Resources

The course will include several hands-on exercises using the statistical software R together with the wordspace package. It is recommended that you bring your own laptop to the course. You might also want to pre-install the required software packages and data sets.

Step 1

Install R version 3.3.x and the RStudio GUI.

Step 2

Use the installer built into RStudio (or the standard R GUI) to install the following packages from the CRAN archive:

• sparsesvd
• iotools
• tm
• Rcpp (needed on Linux only)

Step 3

Install the wordspace package itself, which is not available from CRAN yet and will have to be installed from a local package archive.  You can download the source package as well as binaries for Windows and Mac OS X here: http://www.collocations.de/data/#tutorial

During the course, you will be asked to install a second package with additional evaluation tasks (wordspaceEval) from a password-protected Web page.

Step 4

Download one or more pre-compiled distributional models from http://www.collocations.de/data/ (both the full model and the SVD dimensions).

Some further data files will be made available during the course.

Additional References

• The Wordspace Wiki offers updated versions of the slides, examples and data sets from the ESSLLI 2018 version of the distributional semantics course

Mark Steedman

• Area: LaCo
• Level: I
• Week: 2
• Time: 14:00 – 15:30
• Room: D1.02

Abstract

The course will introduce Combinatory Categorial Grammar (CCG) as a theory
of natural language syntax and semantics for the cognitive sciences.
Because of the simplicity of its syntax-semantics interface, CCG has become
widely used in computational linguistics for semantic parsing and parser
induction for applications like question-answering. However, it is less widely
understood in theoretical linguistics and psycholinguistics. Aimed at linguists,
cognitive scientists, psychologists, and computational linguists, the course will
bring the participants to the point of being able to apply the analytic techniques
and tools of CCG in a wide range of disciplines.
To this end, we will analyze the problem of grammar from the ground up.
We will start with the requirements that child language acquisition imposes on
the theory, then develop a uniform framework for the major bounded and unbounded
constructions in English and other languages with radically different
properties, closing by considering the impact of psychological and computational
processing requirements, including acquisition, on the theory of grammar
itself.

Lecture Schedule and Readings

1. Read Chs. 1, 2, and 3 of the ms. for for background.   Read Ch. 4 for Lecture and Class Discussion
2. Read Ch. 5 for Lecture and Class Discussion
3. Read Ch. 6 for Lecture and Class Discussion
4. Read Ch. 7 for Lecture and Class Discussion
5. Read Ch. 11 and the appendices (or other)  for Lecture and Class Discussion

References

I’ll introduce the early chapters of the following ms. and discuss them with the class.  I’m hoping that people will at least glance at them before the relevant class.   I’m open to variation in the schedule for the last class to discuss more advanced linguistic topics, rather than the computational appendices on performance.

http://homepages.inf.ed.ac.uk/steedman/papers/ccg/esslli16.pdf

Felix Engelmann and Shravan Vasishth

• Area: LoCo
• Level: F
• Week: 1
• Time: 11:00 – 12:30
• Room: D1.02

Abstract

Sentence comprehension, a field of research within psycholinguistics, is concerned with the study of the cognitive processes that unfold when we hear or read a sentence. The focus is on developing theories and models about how sentence comprehension (parsing) works.

The last sixty years have seen significant advances in our understanding of sentence comprehension processes. However, the vast majority of this work is experiment-based, with theory-development being largely limited to paper-pencil models. Although we have learnt a great deal from such informal reasoning about cognitive processes, ultimately the only way to test a theory is to implement it as a computational model. This is a standard approach in research on cognition in artificial intelligence, computer science, and mathematical psychology. Indeed, history has shown that the development of different computational cognitive architectures and mathematical models of cognition has had a huge impact in advancing our understanding of cognitive processes.
This is because computational and mathematical models force the scientist to make detailed commitments, which can then be tested empirically.

The present course brings together these two cultures: informally developed theories of sentence comprehension, and computational/mathematical models of cognition. We develop a series of accounts of sentence comprehension within a specific cognitive architecture that has been developed for modeling general cognitive processes, the ACT-R architecture (version 6.0).

ACT-R is a good choice because it is a mature architecture that has been widely used in artificial intelligence, human-computer interaction, psychology, and psycholinguistics to study cognitive processes.

Some of the issues that have been addressed empirically in sentence comprehension research are: (a) the influence of individual differences in capacity on parsing, (b) the role of parsing strategy, including task-dependent underspecification, (c) the role of probabilistic expectations, (d) the interaction between grammatical knowledge and parsing, (e) the interaction between the eye-movement control system and sentence comprehension, and (f) how impaired processing might arise (e.g., in aphasia). We address all of these topics by presenting computational models of representative phenomena using the ACT-R framework. The source code for the model is already freely available on github:

1. The ACT-R Parser extended with eye-movement control
2. The ACT-R Parsing Module
3. ACT-R simulation of retrieval process
4. Simple Memory
   Retrieval Model for sentence processing based on ACT-R, originally
   developed by R. Lewis and W. Badecker. With some extensions.

Further information:

course website

Frank Drewes

• Area: LaCo
• Level: F
• Week: 1
• Time: 09:00 – 10:30
• Room: C2.06

Abstract

Graphs are becoming a widely used fundamental data structure in practical natural language processing (NLP). Classic feature structures can be seen as rooted, directed, edge- and leaf-labeled graphs, dependency parsing produces graphs rather than trees, and recent work in deep semantic annotation organizes logical meanings into directed graph structures. Efforts currently being made will yield large amounts of linguistic data annotated with such representations, to support the development of NLP algorithms and systems based on the manipulation of graphs. Fortunately, there exists a well-developed theory of graph transformation whose subject is the manipulation of graphs.

A good understanding of the theory of graph transformation will therefore become an asset for the next generation of researchers working in NLP. This course offers an introduction to this, with emphasis on aspects that are of interest for NLP. In particular, this includes context-free graph grammars. The course will start off by a general introduction to graph transformation, being a Turing-complete model of computation which is based on local replacements in graphs. After that, most of the time will be spent on context-free graph grammars, their parsing problem, and their relation to monadic second-order logic. Finally, an introduction to term graph rewriting will be given.

Slides

Lecture 1: Graph Transformation
Lecture 2: Context-Free Graph Grammars
Lecture 3: Parsing for Context-Free Graph Grammars
Lecture 4: Let’s Get Logical
Lecture 5: Further Topics, Implementations, and Literature

Additional References

Drewes, Habel, Kreowski. Hyperedge replacement graph grammars. In Handbook of Graph Grammars and Computing by Graph Transformation. Vol. 1: Foundations, chapter 2, pages 95–162. World Scientific, 1997.

Hana Filip and Peter Sutton

• Area: LaLo
• Level: A
• Week: 1
• Time: 09:00 – 10:30
• Room: C3.06

Abstract

Slides

Day 1

• Lecture 1: Introduction to mereology and countability in the nominal domain

Day 2

• Lecture 2: Chierchia (2010) and Rothstein (2010)

Day 3

• Lecture 3.1: Landman (2011)
• Lecture 3.2: Sutton and Filip (2016)

Day 4

• Lecture 4: Introduction to mereology and countability in the verbal domain

Day 5

• Lecture 5: Quantization puzzles and Maximization

Primary Readings

If you cannot access the primary readings from the links below, please contact Peter Sutton

• Email: peter (dot) r (dot) sutton (at-sign) icloud (dot) com

Day 1

• Champollion, Lucas, and Manfred Krifka (in press). Mereology. In: P. Dekker and M. Aloni (eds), Cambridge Handbook of Semantics. Cambridge University Press
  • Draft (Lingbuzz)

Day 2

• Rothstein, Susan (2010). Counting and the mass/count distinction. Journal of Semantics, 27(3):343–397.
  • (PDF)
• Chierchia, Genaro (2010). Mass Nouns, Vagueness and Semantic Variation. Synthese, 174:99–149.
  • (PDF)

Day 3

• Landman, Fred (2011), Count Nouns – Mass Nouns – Neat Nouns – Mess Nouns, The Baltic International Yearbook of Cognition, 6:1–67.
  • (PDF)
• Sutton, Peter and Hana Filip (2016), Mass/Count Variation, a Mereological, Two-Dimensional Semantics.
  • Draft

Day 4

• Krifka, Manfred (1989). Nominal Reference, Temporal Constitution and Quantification in Event Semantics. In: Renate Bartsch and J. F. A. K. van Benthem and P. van Emde Boas (eds.) Semantics and Contextual Expression, pp. 75–115, Foris Publications.
  • Philpapers

Day 5

• Filip, Hana (2008). “Events and Maximalization.” Theoretical and Crosslinguistic Approaches to the Semantics of Aspect, edited by Susan Rothstein. Amsterdam: John Benjamins. Pp.217-256.
  • pdf

Glyn Morrill and Oriol Valentin

• Area: LaLo
• Level: A
• Week: 1
• Time: 09:00 – 10:30
• Room: D1.01

Abstract

The displacement calculus is a sublinear intuitionistic logic extending the Lambek calculus with a logic of holes, contexts, and plugging. The extension is conservative, free of structural rules, and continues to enjoy Cut-elimination and its corollaries the subformula property, the finite reading property and decidability. In this course we present displacement calculus and explain as case studies medial relativisation (overt movement) and quantifier scoping (covert movement). We provide technical analyses of Cut-elimination, models, and generative power, and we aim to draw come conclusions on the logical, linguistic and computational state of the art of categorial grammar making comparisons with Lambda Grammar, Hybrid Type Logical Grammar, and Lambek-Grishin Calculus.

Slides

Additional References

Paula Menéndez-Benito

• Area: LaLo
• Level: A
• Week: 1
• Time: 11:00 – 12:30
• Room: C3.06

Abstract

Modal indefinites are existential items that convey modal inferences. Across languages, modal indefinites express two types of modal meanings (Haspelmath, 1997). Epistemic indefinites give us information about the epistemic state of the speaker. For instance, the use of Spanish algún in (1) signals that the speaker does not know which doctor María  married (see Alonso-Ovalle and Menéndez-Benito 2015 for a recent overview of epistemic indefinites). Random choice indefinites indicate that an agent made an indiscriminate choice (Kim and Kaufmann, 2007; Choi, 2007; Choi and Romero, 2008; Rivero, 2011a,b; Alonso-Ovalle and Menéndez-Benito, 2013; Chierchia, 2013; Fălăuș 2014). For example, the Spanish sentence in (2), with the random choice indefinite uno cualquiera, compares what Juan actually did (e.g., buying book a) with other alternative, non- actual, actions that he could have undertaken (e.g., buying book b, buying book c) and says that all those actions count as the same for Juan.

The goal of this course is to provide a critical overview of representative research on modal indefinites, addressing questions such as: How do the modal contents expressed by indefinites differ from those attested in the verbal domain? How do modal indefinites interact with other modal elements and why? What is the source of the modal effect? This course will allow students to get acquainted with two current research programs: the development of an explanatory semantic typology of indefinite phrases and the investigation of modality across categories.

Prerequisites

The target audience for this course are graduate students who have taken at least one introductory course in formal semantics at the graduate (M.A. or Ph.D.) level.

Tentative Outline

Day 1. Introduction. Modal indefinites: descriptive overview and research questions. Some parameters of variation. Types of modal content. Epistemic indefinites: degrees of ignorance, type of evidence, interaction with non-epistemic modals, interaction with plurality. Random choice indefinites and modal selectivity.

Day 2. Epistemic indefinites 1. The source of the modal effect. Assessment of the implicature analysis (Alonso-Ovalle and Menéndez-Benito, 2008, 2010; Fălăuș ̧, 2014; Chierchia, 2013).

Day 3. Epistemic indefinites 2. The source of the modal effect: assessment of a pragmatic ap- proach based on conceptual covers. (Aloni and Port, 2013). Exploring new empirical generalizations: epistemic indefinites and evidential constraints (Alonso-Ovalle and Menéndez- Benito, 2013a).

Day 4. Random choice indefinites 1. Type of modality. Assessing the counterfactual approach (Choi, 2007; Choi and Romero, 2008).

Day 5. Random Choice Indefinites 2. Modal Selectivity. Assessing the decision-based approach (Alonso-Ovalle and Menéndez-Benito, 2013b). Taking stock.

Slides

Lecture 1
Lecture 2
Lecture 3
Lecture 4
Lecture 5

Overviews and Monographs

Alonso-Ovalle Luis and Paula Menéndez-Benito  (2015). Epistemic Indefinites. Exploring Modality Beyond the Verbal Domain. Oxford University Press

Alonso-Ovalle Luis and Paula Menéndez-Benito (2013c). Two Views on Epistemic Indefinites. Language and Linguistics Compass, 17(2):105–122

Alonso-Ovalle Luis and Paula Menéndez-Benito  (to appear). Free Choice Items and Modal Indefinites. In Lisa Matthewson, Cécile Meier, Hotze Rullmann, and Thomas Ede Zimmermann (eds.), Companion to Semantics. Wiley

Chierchia, Gennaro (2013). Logic in Grammar. Polarity, Free Choice and Intervention. Oxford: Oxford University Press

Daisuke Bekki and Koji Mineshima

• Area: LaLo
• Level: A
• Week: 1
• Time: 14:00 – 15:30
• Room: D1.03

Abstract

This course is intended to provide an introduction to natural language semantics based on dependent type theory (Martin-Löf 1984; Coquand and Huet 1988).  This discipline, which originated in Sundholm (1986) and Ranta (1994), has been paid much attention recently and extended in various ways (see Cooper 2005 and Luo 2012). From among these extensions, we plan to introduce the compositional framework Dependent Type Semantics (DTS; Bekki 2014), together with its empirical predictions on linguistic phenomena and its conceptual implications for the theory of meaning.

History and Motivation

This course introduces Dependent Type Semantics (DTS), a framework of natural language semantics via dependent type theory.

In the late 1980s, against the backdrop of the rapid development of mainstream discourse semantics such as Discourse Representation Theory (DRT), File Change Semantics, and Dynamic Predicate Logic, Martin-Löf and Sundholm noticed that dependent type theory, which is an extension of simply typed lambda calculus, may provide a solution to the discrepancy between syntactic structures and semantic representations (SRs) of donkey sentences (or, more generally, discourse anaphora). (1b) is an SR of the sentence (1a) given in Sundholm(1986), while (1c) is a first-order translation of (1a).

(1)
a. Every farmer who owns a donkey beats it.
b. (Πu: (Σx:farmer(x))(Σy: donkey(y))own(x,y)) beat(π1(u),π1(π2(u)))
c. ∀x(farmer(x) → ∀y(donkey(y) ∧ own(x,y)) → beat(x,y))

In dependent type theory, an SR of a declarative sentence is a type, which is a collection of proofs. A type (Πx:A)B (dependent function type) is a generalization of implication/function types A → B and universal types (∀x:A)B, while a type (Σx:A)B (dependent product type) is a generalization of conjunction/product types A ⨉ B and existential types (∃x:A)B. We observe that the structure of the SR (1b) parallels that of (1a), in the sense that the universal and the existential quantifications are respectively translated to Π and Σ, unlike (1c) where an indefinite a donkey is translated to the universal quantifier and the syntactic structure of (1a) is lost.

While the accessible anaphoric links are well represented, the inaccessible anaphora such as (2), listed in Karttunen (1976), are simply not representable with dependent types as Ranta (1994) argued. This is because universal quantification, implication, and negation are represented by Π-types that are data types of functions, from which the intended antecedents cannot be picked up. This is an explanation purely based on the structures of proofs, which is fundamentally different from that of DRT and other dynamic semantics.

(2)
a. Everybody bought a carⁱ. *It_i stinks.
b. If John bought a carⁱ, it_i must be a Porsche. *It_i stinks.
c. John didn’t buy a carⁱ. *It_i stinks.

This explanatory advantage launched a discipline of discourse semantics based on the dependent type theory: Ahn and Kolb (1990) proposed a translation algorithm from discourse representation structures to SRs in terms of dependent type theory. Perez (1995) proposed an integration of dependent type theory and Montagovian categorial grammar, and tried to provide a compositional setting (which has not been entirely successful, as discussed in Bekki (2014)). Then, the seminal work of Ranta (1994)—a compilation of this discipline in the mid-1990s—covers a broad range of linguistic phenomena including the anaphora inaccessibility mentioned above, descriptions, tense, and modality.

However, Ranta’s work is formulated as a theory of sentence generation, which needs to be reformulated if one is to adopt it as a semantic component of a modern formal syntactic theory. This problem further involves how to formulate a problem of anaphora resolution and presupposition binding/accommodation as achieved in van der Sandt (1992), Geurts (1999), and Bos (2003) within the DRT framework.

Interestingly, the pursuit of this problem led to works such as Krause (1995), Krahmer and Piwek (1999), Mineshima (2008) and Bekki (2014) attaining a paradigm called “anaphora resolution as proof construction,” which unified analyses of anaphora resolution and presupposition binding/accommodation, and analyses of sentential entailments. Moreover, within the framework of DTS in Bekki (2014), presupposition projections are simply calculated by type checking/inference algorithm of dependent type theory (Bekki and Sato 2015).

Course Plan

The content of this course is highly relevant to the ESSLLI2014 course by Chatzikyriakidis and Luo, titled “Formal Semantics in Modern Type Theories: Theory and Implementation.” However, our course may be of interest to both those who attended it and those who did not, for the following two reasons.

First, our course will focus more on the aspect of DTS as a semantic component of formal grammars. We will present a fully compositional version of DTS, which will meet the demands of researchers studying formal syntax who are looking for a discourse semantics that is a purely type-theoretical.

Second, we will start our course with an introduction to dependent type theory. There seems to be a relatively high barrier to entry for formal linguists seeking to learn semantic theories based on dependent type theory, since one is required to be familiar with proof theory and type theory, especially Martin-Löf type theory, which has a proof-theoretic semantics (see Dummett 1975, Dummett 1976, Prawitz 1980). The notion of proof-theoretic semantics is fundamentally different from that of model-theoretic semantics in which every representation is understood in terms of its semantic value (e.g., dependent type theory does not make use of concepts such as an assignment function, on which the analysis of accessibility in DRT is based). Our aim is to remove any such barrier, by introducing the fundamental notions of proof-theoretic semantics, comparing them with the corresponding notions in model-theoretic semantics.

Given that the empirical coverage of DTS is getting broader, we will discuss, among other things, representations of generalized quantifiers in Sundholm (1989), Fox and Lappin (2005), Tanaka et al. (2013), and Tanaka (2014); modality and factivity discussed in Ranta (1994), Tanaka (2014), and Tanaka et al. (2015); the phenomena of coercion discussed in Luo (2010,2011,2012a,2012b) and Asher and Luo (2012); a unified analysis of conventional implicatures and presuppositions in Bekki and McCready(2014).

We also plan to compare DTS with other proof-theoretic semantics of natural language, such as the ones proposed in Francez (2010a,2010b) and Luo (2012). The relation between DTS and theories of tropes such as in Moltmann (2007) may interest philosophers.

Course Outline

Day 1 : From Natural Deduction to Dependent Type Theory

• Proof-theoretic semantics and model-theoretic semantics
• Natural deduction
• Curry-Howard Correspondence
• Dependent types (Π-type and Σ-type)

Slide: Course outline
Slide: From natural deduction to dependent type theory

Day 2 : Dependent Type Semantics (Part I): Anaphora

• Introducing the basic framework of DTS
• Anaphora resolution in DTS
• Bound variable anaphora, Donkey anaphora, E-type anaphora, Syllogistic anaphora, Accessibility

Slide: Dependent Type Semantics (DTS)

Day 3 : Dependent Type Semantics (Part II): Presupposition

• Presupposition resolution via type-checking
• A proof-theoretic account of presupposition projection
• Applications: bridging, factive presupposition, Binding problem

Slide: Presuppositions

Day 4 : Dependent Type Semantics (Part III): More types

• The interpretation of common nouns: types or predicates?
• Natural number and finite types
• Guest Lecture 1 (Ribeka Tanaka): Generalized quantifiers in Dependent Type Semantics

Slide: Common Nouns: types or predicates?
Slide: More dependent types
Slide: Generalized Quantifier in Dependent Type Semantics (by Ribeka Tanaka)

Day 5 : Computational and philosophical aspects of Dependent Type Semantics

• Guest Lecture 2 (Pascual Martínez-Goméz): Computational semantics and recognizing textual entailment
• Presupposition accommodation
• A proof-theoretic turn in natural language semantics: Beyond context change potential

Slide: Introduction
Slide: Computational semantics and recognizing textual entailment
Slide: Proof-theoretic turn

Appendix

A formal presentation of dependent type theory

Selected References

Theoretical Background

Coquand, T. and G. Huet. (1988) “The Calculus of Constructions”, Information and Computation 76(2-3), pp.95–120.

Martin-Löf, P. (1984) Intuitionistic Type Theory, Vol. 17. Naples, Italy: Bibliopolis. Sambin, Giovanni (ed.).

Sundholm, G. (1986) “Proof theory and meaning”, In: D. Gabbay and F. Guenthner (eds.): Handbook of Philosophical Logic, Vol. III. Reidel, Kluwer, pp.471–506.

Dependent Type Semantics

Bekki, D. (2014) “Representing Anaphora with Dependent Types”, In the Proceedings of N. Asher and S. V. Soloviev (eds.): Logical Aspects of Computational Linguistics (8th international conference, LACL2014, Toulouse, France, June 2014 Proceedings), LNCS 8535. Toulouse, pp.14–29, Springer, Heiderburg.

Bekki, D. and E. McCready. (2014) “CI via DTS”, In the Proceedings of LENLS11. Tokyo, pp.110–123.

Bekki, D. and M. Sato. (2015) “Calculating Projections via Type Checking”, In the Proceedings of TYpe Theory and LExical Semantics (TYTLES), ESSLLI2015 workshop. Barcelona, Spain.

Tanaka, R. (2014) “A Proof-Theoretic Approach to Generalized Quantifiers in Dependent Type Semantics”, In the Proceedings of R. de Haan (ed.): the ESSLLI 2014 Student Session, 26th European Summer School in Logic, Language and Information. Tübingen, Germany, pp.140–151.

Tanaka, R., K. Mineshima, and D. Bekki. (2014) “Resolving Modal Anaphora in Dependent Type Semantics”, In the Proceedings of the Eleventh International Workshop on Logic and Engineering of Natural Language Semantics (LENLS11), JSAI International Symposia on AI 2014. Tokyo, pp.43–56.

Tanaka, R., K. Mineshima, and D. Bekki. (2015) “Factivity and Presupposition in Dependent Type Semantics”, In the Proceedings of TYpe Theory and LExical Semantics (TYTLES), ESSLLI2015 workshop.

Anaphora and Presupposition

Bos, J. (2003) “Implementing the Binding and Accommodation Theory for Anaphora Resolution and Presupposition Projection”, Computational Linguistics 29(2), pp.179– 210.

Geurts, B. (1999) Presuppositions and pronouns. Elsevier, Oxford.

van der Sandt, R. (1992) “Presupposition projection as anaphora resolution”, Journal of Semantics 9, pp.333–377.

Dependent Types and Proof-Theoretic Semantics of Natural Language

Cooper, R. (2005) “Austinian truth, attitudes and type theory”, Research on Language and Computation 3, pp.333–362.

Francez, N. and R. Dyckhoff. (2010) “Proof-theoretic semantics for a natural language fragment”, Linguistics and Philosophy 33(6), pp.447–477.

Luo, Z. (2012a) “Common Nouns as Types”, In: D. B ́echet and A. Dikovsky (eds.): Logical Aspects of Computational Linguistics, 7th International Conference, LACL2012, Nantes, France, July 2012 Proceedings. Springer, pp.173–185.

Luo, Z. (2012b) “Formal Semantics in Modern Type Theories with Coercive Subtyping”, Linguistics and Philosophy 35(6).

Mineshima, K. (2008) “A presuppositional analysis of definite descriptions in proof theory”, In: K. Satoh, A. Inokuchi, K. Nagao, and T. Kawamura (eds.): New Frontiers in Artificial Intelligence: JSAI 2007 Conference and Workshops, Revised Selected Papers, Lecture Notes in Computer Science Vol. 4914. Springer-Verlag, pp.214–227.

Ranta, A. (1994) Type-Theoretical Grammar. Oxford University Press.

Paul Egré and Benjamin Spector

• Area: LaLo
• Level: I
• Week: 1
• Time: 14:00 – 15:30
• Room: D1.01

Abstract

The goal of this course is to show how certain types of trivalent logics that can be used to model natural language phenomena -­‐focussing on presuppositions, vagueness,and plural semantics.

• We will start with a presentation and comparison of the Strong
  Kleene semantics and the supervaluationist framework for
  propositional logic, viewed as theories of vagueness in natural
  languages. We will also present the`Strict, Tolerant, Classical’
  framework of Cobreros et al. and its application to vagueness.
• We will then move to presuppositions and present the Middle Kleene
  approach to presupposition projection for a propositional fragment.
• We will show how some of these systems can be extended to
  languages that include generalized quantifiers.
• We will address recent attempts to provide a uniform multivalent
  semantics that can deal simultaneously with presupposition and
  vagueness.
• We will discuss a recent application of Strong Kleene semantics to
  the semantics and pragmatics of plural expressions.

 

Recommended textbooks

If you are encountering three-valued logics for the first time, we recommend the following textbooks as excellent introductions:

JC. Beall and Bas van Fraassen, Possibilities and Paradox, OUP, 2003.

Graham Priest, An introduction to non-classical logics, 2nd edition, OUP, 2008.

 

Outline of the course

—

Session #1: Introduction & Overview of Trivalent Logics

• General problem: the projection of vagueness and the projection of presupposition
• Supervaluations, Strong Kleene, Weak Kleene and their duals.
• Applications to vagueness

Slides Day #1: pdf

NB. This overview really is meant as an overview, it may seem fairly abstract and technical, so do not worry if you don’t get everything at once, we will revisit some of the main semantics in a different guise on Day 2. If you missed Session 1, you can get a complete fresh start in Session 2 !

—

Session #2: Presupposition (and vagueness) projection

• The problem
• Strong Kleene
• Middle Kleene
• Accommodation
• Incremental supervaluationism

Handout Day #2: pdf

—

Session #3: Presupposition projection in quantified contexts

• Extending Strong Kleene and Middle Kleene to a language with generalized quantifiers

Handout Day #3: pdf

—

Session #4: Strict Tolerant semantics

• Borderline contradictions
• Three-valued ST
• Gaps vs. Gluts
• Local ST

Slides Day #4: pdf

—

Session #5: Plurals and Homogeneity, integrating vagueness and presupposition

• Homogeneity vs. Vagueness
• Time-permitting: integrating vagueness and presupposition in a single multivalent semantics.

Slides/Handouts Day #5:

Integrating vagueness and presupposition, Plurals, homogeneity and non-maximality

Selected References

Vagueness and Trivalence

Alxatib, S. and Pelletier, F. J. (2011). The psychology of vagueness: Borderline cases and contradictions. Mind & Language, 26(3):287–326.

Alxatib, S., Pagin, P., and Sauerland, U. (2013). Acceptable contradictions: Pragmatics or semantics? a reply to Cobreros et al. Journal of philosophical logic, 42(4):619–634.

Cobreros, P., Egré, P., Ripley, D., and van Rooij, R. (2012). Tolerant, classical, strict. Journal of Philosophical Logic, 41(2):347–385.

Cobreros, P., Egré, P., Ripley, D., and van Rooij, D. (2015a). Vagueness, truth and permissive consequence. In D. Achouriotti, H. Galinon, J. M., editor, Unifying the Philosophy of Truth, pages 409–430. Springer.

Cobreros, P., Egré, P., Ripley, D., and van Rooij, R. (2015b). Pragmatic interpretations of vague expressions: strongest meaning and nonmonotonic consequence. Journal of Philosophical Logic, 44(4):375–393.

Egré P. and Zehr J. (2016). Are Gaps preferred to Gluts? A closer look at borderline contradictions. Manuscript, under review.

Ripley, D. (2011). Contradictions at the border. In Nouwen, R., Schmitz, H.-C., and van Rooij, R., editors, Vagueness in Communication.

Ripley, D. (2013). Sorting out the sorites. In Tanaka, K., Berto, F., and Mares, E., Eds, Paraconsistency: Logic and Applications, pages 329–3. Springer.

Serchuk, P., Hargreaves, I., and Zach, R. (2011). Vagueness, logic and use: Four experimental studies on vagueness. Mind & Language, 26(5):540–573.

Zehr, J. (2014). Vagueness, Presupposition and Truth-Value Judgments. PHD Thesis, ENS, Paris.

Presupposition, Homogeneity and Trivalence

Beaver, D. and E. Krahmer (2001). A partial account of presupposition projection. Journal of Logic, Language and Information 10,147–182.

George, B. R. (2008). A new predictive theory of presupposition projection. In Proceedings of SALT, Volume 18, pp. 358–375.

Kriz, M., forthcoming. Homogeneity, Non-maximality, and ‘all’. Journal of Semantics.

Kriz, M. and B. Spector. Maximality, homogeneity and alternatives. Ms.

Križ, M. and E. Chemla. (2014) Two methods to find truth-value gaps and their application to the projection problem of homogeneity. Natural Language Semantics : 1944.

Löbner,S.(2000).Polarity in natural language predication, quantification and negation in particular and characterizing sentences. Linguistics and Philosophy 23(3), 213–308.

Peters, S. (1979). A truth-conditional formulation of Karttunen’s account of presupposition. Synthese 40(2), 301–316.

Spector,B (2015). Multivalent semantics for vagueness and presupposition. Topoi, doi: 10.1007/s1124590149929291

Zehr, J. (2013). ST5: a 5-valued logic for truth-value judgments involving vagueness and presuppositions. In M. Colinet, S. Katrenko, and R. K. Rendsvig (Eds.), Pristine Perspectives on Logic, Language and Computation, Volume 8607, pp. 247–265. ESSLLI 2012-2013.

Judith Degen

• Area: LaLo
• Level: I
• Week: 1
• Time: 11:00 – 11:30
• Room: C2.01

Click here to visit the course website. 

Abstract

Traditionally, the primary source of data in pragmatics has been researchers’ intuitions about utterance meanings. However, the small numbers of introspective judgments about examples, hand-selected by researchers who themselves provide these judgments, introduces bias into the phenomena under investigation. The recently emerging use of experimental methods for probing linguistically untrained language users’ interpretations has ameliorated the bias introduced by small numbers of judgments. It cannot, however, remove item bias: researchers artificially construct the stimuli used in experiments. Fortunately, studying corpora of naturally occurring language can reduce item bias. Corpora provide naturally occurring utterances that can be used in tandem with platforms like Mechanical Turk to provide large-scale crowd-sourced interpretations of these utterances, thereby allowing for constructing large databases of different types of meanings (e.g., implicatures) in context.

In order to not only introduce course participants to the use of corpora of naturally occurring language for research in semantics/pragmatics but also equip you with practical skills for conducting your own research in this area, the course will contain a substantial hands-on component. We will use tools for searching syntactically parsed corpora (tgrep2, TDTlite) as well as tools for analyzing and visualizing data (R, in particular the lme4 and ggplot2 packages).