This article surveys the use of empirical, machine-learning methods for a particular natural
language-understanding task-information extraction. The author presents a generic …

The growing availability of online textual sources and the potential number of applications of
knowledge acquisition from textual data has lead to an increase in Information Extraction …

This paper presents recent work using the CHILL parser acquisition system to automate the
construction of a natural-language interface for database queries. CHILL treats parser …

A program that makes an existing website look like a database is called a wrapper. Wrapper
learning is the problem of learning website wrappers from examples. We present a wrapper …

This paper describes an experimental comparison of seven different learning algorithms on
the problem of learning to disambiguate the meaning of a word from context. The algorithms …

FOIL is a first-order learning system that uses information in a collection of relations to
construct theories expressed in a dialect of Prolog. This paper provides an overview of the …

In recent years, there has been a resurgence in research on empirical methods in natural
language processing. These methods employ learning techniques to automatically extract …

To understand diverse natural language commands, virtual assistants today are trained with
numerous labor-intensive, manually annotated sentences. This paper presents a …

Text categorization is the task of classifying text into one of several prede ned categories. In
this paper we will evaluate the e ectiveness of several ILP methods for text categorization …

This paper presents a method for inducing logic programs from examples that learns a new
class of concepts called first-order decision lists, defined as ordered lists of clauses each …