Natural Language Processing with Python

Further Reading

Consult http://www.nltk.org/ for further materials on this chapter and on how to install the Prover9 theorem prover and Mace4 model builder. General information about these two inference tools is given by (McCune, 2008).

For more examples of semantic analysis with NLTK, please see the semantics and logic HOWTOs at http://www.nltk.org/howto. Note that there are implementations of two other approaches to scope ambiguity, namely Hole semantics as described in (Blackburn & Bos, 2005), and Glue semantics, as described in (Dalrymple et al., 1999).

There are many phenomena in natural language semantics that have not been touched on in this chapter, most notably:

1. Events, tense, and aspect

2. Semantic roles

3. Generalized quantifiers, such as most

4. Intensional constructions involving, for example, verbs such as may and believe

While (1) and (2) can be dealt with using first-order logic, (3) and (4) require different logics. These issues are covered by many of the references in the following readings.

A comprehensive overview of results and techniques in building natural language front-ends to databases can be found in (Androutsopoulos, Ritchie & Thanisch, 1995).

Any introductory book to modern logic will present propositional and first-order logic. (Hodges, 1977) is highly recommended as an entertaining and insightful text with many illustrations from natural language.

For a wide-ranging, two-volume textbook on logic that also presents contemporary material on the formal semantics of natural ...