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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Barreiro, A. & Batista, F. (2016). Machine translation of non-contiguous multiword units. In Workshop on Discontinuous Structures in Natural Language Processing (DiscoNLP 2016). (pp. 22-30). San Diego, California, USA: Association for Computational Linguistics.
Exportar Referência (IEEE) 
A. Barreiro and F. M. Batista,  "Machine translation of non-contiguous multiword units", in Workshop on Discontinuous Structures in Natural Language Processing (DiscoNLP 2016), San Diego, California, USA, Association for Computational Linguistics, 2016, pp. 22-30
Exportar BibTeX 
@inproceedings{barreiro2016_1766238839216,
	author = "Barreiro, A. and Batista, F.",
	title = "Machine translation of non-contiguous multiword units",
	booktitle = "Workshop on Discontinuous Structures in Natural Language Processing (DiscoNLP 2016)",
	year = "2016",
	editor = "",
	volume = "",
	number = "",
	series = "",
	pages = "22-30",
	publisher = "Association for Computational Linguistics",
	address = "San Diego, California, USA",
	organization = "Association for Computational Linguistics",
	url = "http://www.proceedings.com/30815.html"
}
Exportar RIS 
TY  - CPAPER
TI  - Machine translation of non-contiguous multiword units
T2  - Workshop on Discontinuous Structures in Natural Language Processing (DiscoNLP 2016)
AU  - Barreiro, A.
AU  - Batista, F.
PY  - 2016
SP  - 22-30
CY  - San Diego, California, USA
UR  - http://www.proceedings.com/30815.html
AB  - Non-adjacent linguistic phenomena such as non-contiguous multiwords and other phrasal units containing insertions, i.e., words that are not part of the unit, are difficult to process and remain a problem for NLP applications. Non-contiguous multiword units are common across languages and constitute some of the most important challenges to high quality machine translation. This paper presents an empirical analysis of non-contiguous multiwords, and highlights our use of the Logos Model and the Semtab function to deploy semantic knowledge to align non-contiguous multiword units with the goal to translate these units with high fidelity. The phrase level manual alignments illustrated in the paper were produced with the CLUE-Aligner, a Cross-Language Unit Elicitation alignment tool.
ER  -