We present an approach to shorten Ancient Greek sentences by using morpho-syntactic information attached to each word in a sentence. This work underpins the content of our eLearning application, AncientGeek, whose unique teaching technique draws from primary Greek sources. By applying a technique that skips the clausal dependents of a main verb, we reached a well-formed rate of 89% of the sentences.
Moritz, M., Pavlek, B., Franzini, G., Crane, G., Sentence Shortening via Morpho-Syntactic Annotated Data in Historical Language Learning, <<ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE>>, 2016; (9/1): N/A-N/A. [doi:10.1145/2810040] [http://hdl.handle.net/10807/127254]
Sentence Shortening via Morpho-Syntactic Annotated Data in Historical Language Learning
Franzini, GretaPenultimo
;
2016
Abstract
We present an approach to shorten Ancient Greek sentences by using morpho-syntactic information attached to each word in a sentence. This work underpins the content of our eLearning application, AncientGeek, whose unique teaching technique draws from primary Greek sources. By applying a technique that skips the clausal dependents of a main verb, we reached a well-formed rate of 89% of the sentences.
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