Building a Corpus of Indefinite Uses Annotated with Fine-grained Semantic Functions
Natural languages possess a wealth of indefinite forms that typically differ in distribution and interpretation. Although formal semanticists have strived to develop precise meaning representations for different indefinite functions, to date there has hardly been any corpus work on the topic. In this paper, we present the results of a small corpus study where English indefinite forms any' and some' were labelled with fine-grained semantic functions well-motivated by typological studies. We developed annotation guidelines that could be used by non-expert annotators and calculated inter-annotator agreement amongst several coders. The results show that the annotation task is hard, with agreement scores ranging from 52{\%} to 62{\%} depending on the number of functions considered, but also that each of the independent annotations is in accordance with theoretical predictions regarding the possible distributions of indefinite functions. The resulting annotated corpus is available upon request and can be accessed through a searchable online database.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Building a Biomedical Full-Text Part-of-Speech Corpus Semi-Automatically
This paper presents a method for semi-automatically building a corpus of full-text English-language biomedical articles annotated with part-of-speech tags. The outcomes are a semi-automatic procedure to create a large si…
ArticlesTAGBuilding a Bilingual Vietnamese-French Named Entity Annotated Corpus through Cross-Linguistic Projection
The creation of high-quality named entity annotated resources is time-consuming and an expensive process. Most of the gold standard corpora are available for English but not for less-resourced languages such as Vietnames…
Automatic Error Detection concerning the Definite and Indefinite Conjugation in the HunLearner Corpus
In this paper we present the results of automatic error detection, concerning the definite and indefinite conjugation in the extended version of the HunLearner corpus, the learners corpus of the Hungarian language. We p…
Semi-automatically Annotated Learner Corpus for Russian
We present ReLCo— the Revita Learner Corpus—a new semi-automatically annotated learner corpus for Russian. The corpus was collected while several thousand L2 learners were performing exercises using the Revita language-l…
Grammatical Error CorrectionGrammatical Error DetectionBuilding a Manually Annotated Hungarian Coreference Corpus: Workflow and Tools
This paper presents the complete workflow of building a manually annotated Hungarian corpus, KorKor, with particular reference to anaphora and coreference annotation. All linguistic annotation layers were corrected manua…