Determining the Type and Weight of Clauses of Relational Process in Google Translate Persian into English by Translation Evaluation Model of HAR from Halliday's SFG

Authors

Abstract

Lexico-grammar errors in 10 clauses of relational process, translated by Google Translate Persian into English, are analyzed from SFG using the HAR pattern designed by the authors. Since the ratio of the unmarked identified-identifier clauses to marked identified-identifier clauses and the ratio of unmarked carrier-attribute clauses to marked carrier-attribute clauses in Ph.D. thesis was 4 to 1, here 4 unmarked and 1 marked identified-identifier clauses and 4 unmarked and 1 marked carrier-attribute clauses have been deliberately selected to be investigated. HAR error codes of 2, 3, 4, and 6 which are considered as more serious errors due to having more direct relationship to textual and experimental metafunctions were less than other error codes, meaning these two metafunctions are considerably taken into account by Google Translate in relational process.

Author Biographies

Zeinolabedin Rahmani

Ph.D., Department of Linguistics, Tarbiat Modares University, Tehran, Iran

Ferdows Aghagolzadeh

Professor, Department of Linguistics, Tarbiat Modares University, Tehran, Iran

Aliyeh Kord Zaferanlou Kambouzia

Associate Prefessor, Department of Linguistics, Tarbiat Modares University, Tehran, Iran

Arsalan Golfam

Associate Prefessor, Department of Linguistics, Tarbiat Modares University, Tehran, Iran

Published

2017-09-16

How to Cite

Rahmani, Z., Aghagolzadeh, F., Kord Zaferanlou Kambouzia, A., & Golfam, A. (2017). Determining the Type and Weight of Clauses of Relational Process in Google Translate Persian into English by Translation Evaluation Model of HAR from Halliday’s SFG. Iranian Journal of Translation Studies, 15(58). Retrieved from https://journal.translationstudies.ir/ts/article/view/436

Issue

Vol. 15 No. 58 (2017)

Section

Academic Research Paper

License

Copyright Licensee: Iranian Journal of Translation Studies. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0 license).