eprintid: 49016 rev_number: 25 eprint_status: archive userid: 1193 dir: disk0/00/04/90/16 datestamp: 2017-05-12 03:22:31 lastmod: 2022-06-23 02:48:24 status_changed: 2017-05-12 03:22:31 type: thesis metadata_visibility: show contact_email: eprints@uny.ac.id creators_name: Rahmawati, Yesi title: A SEMANTIC ANALYSIS OF ENTAILMENT IN THE DA VINCI CODE MOVIE ispublished: pub subjects: E4 divisions: fbs_jurdik_inggris_bahasa_sastra_inggris full_text_status: restricted keywords: semantic, entailment, The Da Vinci Code movie abstract: This research is under the scope of semantics. The aims of this study are to identify the types of entailment, to describe the orders of entailment, and to explain the approaches to detect entailment uttered by the characters in The Da Vinci Code movie. This research employed descriptive qualitative method. Therefore, the data of this research were in the form of utterances performed by the characters in The Da Vinci Code movie, while the context of the data was monologues or dialogues between the characters. The source of the data was The Da Vinci Code movie and its transcript. The data were collected by selecting sentences containing entailment. The researcher conducted triangulation in order to establish the credibility of the data. The results revealed from the findings are mentioned as follows. (1) All types of entailment which are one-way entailment, two-way/mutual entailment, negative entailment, and metaphorical entailment are found in The Da Vinci Code movie. From the total 57 data, one-way entailment reaches the highest frequency because it is the simplest model of entailment, and it appears 26 times. Meanwhile, negative entailment, which appears 6 times, becomes the least one to occur. This type of entailment requires at least one negative sentence to formulate entailment, while the characters in the movie rarely perform negative sentences. (2) Each order of entailment is applied in the data sheet; they are background entailment and foreground entailment. Therefore, most of entailments found in the movie are ordered based on the foreground as it is applied 33 times, and is distributed into 28 stressing and 5 clefting. The existence of stressing and clefting supports the foreground order to acquire the highest position. (3) To detect entailment in The Da Vinci Code movie, the researcher employs contexted clause and context matching approaches. Contexted clause is employed 36 times out of 57 data, while context matching is employed in the rest of the data. The researcher tends to apply contexted clause more frequently rather than context matching since most of the entailments are interconnected in context. 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