B1706 - Semantics (1) (LM)

Learning outcomes

The course is an introduction to the study of meaning in language, and how meaning is encoded in constructions belonging to different structural levels (morphology, syntax, discourse). The course focuses on the following aspects: lexical semantics; grammatical semantics; meaning representation; meaning, cognition and categorization; meaning and variation. Students will become familiar with the main theoretical models within the field, as well as with research methods and tools (including computational ones) for the collection and analysis of linguistic data, from both an intra-linguistic and a cross-linguistic perspective.

Course contents

Everything we do linguistically is aimed at creating messages, and therefore meanings that can be conveyed in some form.

This course is an introduction to the study of meaning in natural language and to the ways in which meaning is "packaged" in linguistic constructions that belongs to different structural levels (morphology, syntax, discourse).

The following general questions will be tackled:

• What is meaning? What is the difference between denotation and connotation, sense and reference, meaning and encyclopedic knowledge?
• Where is meaning? Which are the linguistic units that bear meaning? What is the difference between lexical semantics and grammatical semantics?
• What kinds of semantic relations do we have?
  
• How do we represent meaning? Which are the main relevant theoretical models? And how can we account for non-literal expressions?
  
• What is the relation between meaning and cognition, between language and thought? How does categorization work?
  

Afterwards, we will focus on three topics:

1. the competition between different forms to express the same function, at both morphological and syntactic-discursive levels;
2. evaluative semantics, especially approximation and prototypicality, at both morphological and syntactic-discursive levels;
3. verb semantics: classes of verbs, semantics-syntax interaction, aspectual marking and the emergence of non-canonical values in verbal series.

In the last part of the course (valid only for the 9CFU, 45h Semantics exam) some computational methods and resources for investingating meaning will be introduced. In particular, the basics of corpus linguistics will be provided, in order to collect and analyze naturally occurring data, and the method of Distributional Semantics will be introduced, to qualitatively and quantitatively explore unstructured data.

NOTA BENE – This is an advanced course in linguistics. A basic knowledge of general linguistics is required. Students who have no prior knowledge of the field are strongly advised to study an introductory linguistics textbook before the classes start (e.g. Graffi & Scalise 2013 or Berruto & Cerruti 2011).

Readings/Bibliography

Textbook

• Riemer, Nick. 2010. Introducing semantics. Cambridge: Cambridge University Press [except chapters 4 and 6].

Articles

• Aronoff, Mark. 2016. Competition and the lexicon. In Annibale Elia, Claudio Iacobini & Miriam Voghera (eds), Livelli di analisi e fenomeni di interfaccia, 39–52. Roma: Bulzoni.
• De Wit, Astrid & Frank Brisard. 2020. Aspect beyond time. Journal of Linguistics 56. 459–477.
• Grandi, Nicola. 2017. Intensification processes in Italian: A survey. In Maria Napoli e Miriam Ravetto (eds),Exploring Intensification. Synchronic, diachronic and cross-linguistic perspectives, 55–77. Amsterdam: Benjamins.
• Masini, Francesca, Muriel Norde & Kristel Van Goethem. 2023. Approximation in morphology: A state of the art. Zeitschrift für Wortbildung / Journal of Word Formation 7(1). 1–26.

Further readings on specific topics may be given during classes. All materials used during the course (slides, articles, etc.) are part of the readings for the oral exam for students who attend classes.

Further readings for students who do not attend classes (in addition to the textbook and the articles)

• Three chapters from: Dirk Geeraerts & Hubert Cuyckens (eds), The Oxford Handbook of Cognitive Linguistics, Oxford:Oxford University Press.

Teaching methods

All topics will be discussed with reference to data from different languages. Some IT tools for the collection and analysis of relevant linguistic data will be employed and illustrated.
In addition to traditional lectures, students will be involved in lab/group activities.

Assessment methods

The final oral exam aims at assessing the theoretical notions acquired by the students during the course, as well as their ability to tackle with specific questions and to analyze concrete cases of linguistic analysis. The oral exam consists of three questions, each of which focuses on one of the program topics.

For students who attend classes, the teacher will also take into account their work during classes (seminars and lab/group activities) in determining the final grade. Students who don't attend classes should instead study the extra readings listed in the bibliography. All students are kindly requested to inform the teacher about their attending classes or not at the beginning of the course.

As for the assessment, the ability of the students to give clearly expressed, correct and complete answers will be considered. Besides, clarity and argumentative rigor will be evaluated. Those students who demonstrate to have a global and harmonious knowledge of the subject and its specific language/terminology, to communicate ideas in a proper and clear way and to have acquired adequate analysis skills will get high grades. A partial knowledge of the subject and its specific language/terminology, an overall fair but not perfect way of communicating, and less refined analysis skills imply average grades. A limited knowledge of the subject and its specific language/terminology and poor communication and analysis skills imply low grades. Those students who prove to have an inadequate and/or insufficient knowledge of the subject (in both its theoretical and applied parts) and its specific language/terminology will fail the exam.

Teaching tools

PowerPoint presentations and/or printed handouts will support the lectures. Computational tools and web resources for data analysis will also be displayed through a projector.

All materials will be published on the Virtuale platform every week and are part of the readings for the oral exam for students who attend classes.

Office hours

See the website of Francesca Masini