Course pages 2013–14

# Syntax and Semantics of Natural Language

**Principal lecturers:** Prof Ted Briscoe, Dr Stephen Clark**Taken by:** MPhil ACS, Part III**Code:** L107**Hours:** 16**Prerequisites:** L100 Introduction to Natural Language Processing and R07 Introductory Logic for students who have not taken a course in logic before.

## Aims

This module provides an introduction to the formal syntax and semantics of natural language, in particular Montague-style compositional semantics using a Categorial Grammar model of syntax. Half of the module will focus on the theory of syntax, followed by an example of how recent advances in parsing technology allow such a theory to be implemented in practice, operating on naturally occurring text. The other half of the module focuses on truth-conditional compositional semantics of sentences, computational implementation of this approach, and probabilistic inference for semantic interpretation.

## Syllabus

- Introduction to (Combinatory) Categorial Grammar (CCG). [1 lecture]
- English syntax in the CCG framework. [3 lectures]
- Introduction to statistical parsing. [1 lecture]
- Constructing a wide-coverage CCG English grammar. [1 lecture]
- Wide-coverage robust statistical parsing with CCG. [2 lectures]
- Introduction to natural language semantics. [1 lecture]
- Montague semantics; compositional semantics, typed lambda calculus, quantification, intensionality. [3 lectures]
- Robust, wide-coverage implementation and underspecification. [2 lectures]
- Probabilistic inference and semantic interpretation. [2 lectures]

All lectures will be given by Professor Briscoe or Dr Clark.

## Objectives

On completion of this module, students should:

- understand how the syntax of natural language sentences can be modelled using a type-driven (Combinatory) Categorial Grammar;
- understand how a wide-coverage grammar of English can be constructed;
- have studied one approach to statistical parsing in detail;
- understand how the meaning of natural language sentences can be modelled using a logical, model-theoretic approach;
- understand how the meaning of natural language sentences can be constructed using Frege's principle of compositionality;
- understand how this approach to meaning can be combined with probabilistic inference;
- gain an appreciation of how syntactic and semantic theory can be implemented in practice.

## Assessment

- Four ticked take-home tests or short practicals. Each ticked test is worth 5% of the final assessment for the course. Tests will be due in one week after assignment and ticked (with feedback) by Professor Briscoe and Dr Clark.
- One final take-home exam covering all the material taken at beginning of Easter Term. Final take-home exam will contribute 80% to the final assessment. Questions set and marked by Professor Briscoe and Dr Clark.

## Recommended reading

Steedman, M. (with Baldridge, J.) (forthcoming). Combinatory
categorial grammar. To appear in *Non-transformational syntax*
(eds. Borsley, R. & Borjars, K.). Available
here.

Clark, S. & Curran, J.R. (2007). Wide-coverage efficient
statistical parsing with CCG and log-linear models.
In *Computational linguistics*, 33(4),
pp.493-552. Available here.

Cann, R. (1993). *Formal semantics*. Cambridge University
Press. (Google Books, UL, etc.)

Bos, J. & Blackburn, P. (2004). *Working with discourse representation
theory.*
Available here.

Bos, J., Clark, S., Curran, J.R. & Hockenmaier, J. (2004).
Wide-coverage semantic representations from a CCG parser. In
*Proceedings of COLING-04*, pp.1240-1246, Geneva, Switzerland.
Available here.

Bos, J. (2008). Wide-coverage semantic analysis with Boxer.
*2nd Conference on semantics in text
processing*. Available here.

Garrette, D., Erk, K. & Mooney, R. (2011). Integrating logical
representations with probabilistic information using Markov logic.
*International workshop on computational semantics*. Available
here.