Using Verb Frames for Text Difficulty Assessment
This paper presents the first investigation on using semantic frames to assess text difficulty. Based on Mandarin VerbNet, a verbal semantic database that adopts a frame-based approach, we examine usage patterns of ten verbs in a corpus of graded Chinese texts. We identify a number of characteristics in texts at advanced grades: more frequent use of non-core frame elements; more frequent omission of some core frame elements; increased preference for noun phrases rather than clauses as verb arguments; and more frequent metaphoric usage. These characteristics can potentially be useful for automatic prediction of text readability.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Improvement of VerbNet-like resources by frame typing
Verbenet is a French lexicon developed by {``}translation{''} of its English counterpart {---} VerbNet (Kipper-Schuler, 2005){---}and treatment of the specificities of French syntax (Pradet et al., 2014; Danlos et al., 2…
Machine TranslationQuestion AnsweringStock Market PredictionTranslationDynamic Video Frame Interpolation with integrated Difficulty Pre-Assessment
Video frame interpolation(VFI) has witnessed great progress in recent years. While existing VFI models still struggle to achieve a good trade-off between accuracy and efficiency: fast models often have inferior accuracy;…
Video Frame InterpolationVerb Sense Clustering using Contextualized Word Representations for Semantic Frame Induction
Contextualized word representations have proven useful for various natural language processing tasks. However, it remains unclear to what extent these representations can cover hand-coded semantic information such as sem…
ClusteringImproving Verb Phrase Extraction from Historical Text by use of Verb Valency Frames
Enriching the ``Senso Comune'' Platform with Automatically Acquired Data
This paper reports on research activities on automatic methods for the enrichment of the Senso Comune platform. At this stage of development, we will report on two tasks, namely word sense alignment with MultiWordNet and…