| dc.contributor.author | Kathleen Swee, Neo Tan | |
| dc.contributor.author | Tong, Ming Lim | |
| dc.contributor.author | Chi, Wee Tan | |
| dc.contributor.author | Wei, Wei Chew | |
| dc.date.accessioned | 2024-02-27T06:43:55Z | |
| dc.date.available | 2024-02-27T06:43:55Z | |
| dc.date.issued | 2022 | |
| dc.identifier.citation | The Journal of the Institution of Engineers, Malaysia, Special Ed., 2022, pages 95-100. | en_US |
| dc.identifier.issn | 0126-513x | |
| dc.identifier.uri | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/80145 | |
| dc.description | Link to publisher’s home pages at https://www.myiem.org.my/ | en_US |
| dc.description.abstract | Light verb constructions (LVC) are complex predicates that are present in many languages. They belong to the Multiword Expression (MWE) category known as verbal MWEs and has the canonical form of verb+noun. Examples of LVCs include give help, make decisions, and take walks. LVC identification is essential for many natural processing (NLP) applications such as machine translation, sentiment analysis, and information extraction. However, the task of LVC identification is challenging due to its characteristics such as variability, discontinuity, and ambiguity. This paper presents a review of recent work, discusses the gaps that still exist, and proposes some future work that may contribute significant progress in LVC identification. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | The Institution of Engineers, Malaysia (IEM) | en_US |
| dc.subject.other | Light verb constructions | en_US |
| dc.subject.other | Multiword expressions | en_US |
| dc.subject.other | Computational linguistics | en_US |
| dc.subject.other | Natural language processing | en_US |
| dc.title | Automatic identification of light verb constructions: a review | en_US |
| dc.type | Article | en_US |
| dc.identifier.url | https://www.myiem.org.my/ | |
| dc.contributor.url | tansn@tarc.edu.my | en_US |
