Sentence Shortening via Morpho-Syntactic Annotated Data in Historical Language Learning

Maria Moritz; Barbara Pavlek; Greta Franzini; Gregory Crane

doi:10.1145/2810040

Sentence Shortening via Morpho-Syntactic Annotated Data in Historical Language Learning

Maria Moritz
, Barbara Pavlek
, Greta Franzini
, Gregory Crane

Università Cattolica del Sacro Cuore

University of Göttingen
University of Zagreb
Leipzig University

Risultato della ricerca: Contributo in rivista › Articolo

2 Citazioni (Scopus)

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.

Lingua originale	Inglese
pagine (da-a)	N/A-N/A
Numero di pagine	9
Rivista	Journal on Computing and Cultural Heritage
DOI	https://doi.org/10.1145/2810040
Stato di pubblicazione	Pubblicato - 2016

Keywords

Primary source text
dependent
morpho-syntactic annotation
part of speech tags

Accesso al documento

10.1145/2810040

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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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KW - part of speech tags

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KW - dependent

KW - morpho-syntactic annotation

KW - part of speech tags

UR - http://hdl.handle.net/10807/127254

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Sentence Shortening via Morpho-Syntactic Annotated Data in Historical Language Learning

Abstract

Keywords

Accesso al documento

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