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Latin: A Linguistic Introduction

By Renato Oniga and Norma Shifano

Applies the principles of contemporary linguistics to the study of Latin and provides clear explanations of grammatical rules alongside diagrams to illustrate complex structures.


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The Ancient Language, and the Dialect of Cornwall, with an Enlarged Glossary of Cornish Provincial Words

By Frederick W.P. Jago

Containing around 3,700 dialect words from both Cornish and English,, this glossary was published in 1882 by Frederick W. P. Jago (1817–92) in an effort to describe and preserve the dialect as it too declined and it is an invaluable record of a disappearing dialect and way of life.


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Linguistic Bibliography for the Year 2013

The Linguistic Bibliography is by far the most comprehensive bibliographic reference work in the field. This volume contains up-to-date and extensive indexes of names, languages, and subjects.


Academic Paper


Title: Generating example contexts to help children learn word meaning
Author: Liu Liu
Institution: Google Pittsburgh
Author: Jack Mostow
Institution: Carnegie Mellon University
Author: Gregory S. Aist
Email: click here to access email
Homepage: http://www.gregoryaist.com
Linguistic Field: Computational Linguistics
Abstract: This article addresses the problem of generating good example contexts to help children learn vocabulary. We describe VEGEMATIC, a system that constructs such contexts by concatenating overlapping five-grams from Google's N-gram corpus. We propose and operationalize a set of constraints to identify good contexts. VEGEMATIC uses these constraints to filter, cluster, score, and select example contexts. An evaluation experiment compared the resulting contexts against human-authored example contexts (e.g., from children's dictionaries and children's stories). Based on rating by an expert blind to source, their average quality was comparable to story sentences, though not as good as dictionary examples. A second experiment measured the percentage of generated contexts rated by lay judges as acceptable, and how long it took to rate them. They accepted only 28% of the examples, but averaged only 27 seconds to find the first acceptable example for each target word. This result suggests that hand-vetting VEGEMATIC's output may supply example contexts faster than creating them manually.

CUP at LINGUIST

This article appears in Natural Language Engineering Vol. 19, Issue 2, which you can read on Cambridge's site or on LINGUIST .



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