SHADE: Semantic Hypernym Annotator for Domain-specific Entities -- DnD Domain Use Case
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Abstract (arXiv)
Manual data annotation is an important NLP task but one that takes considerable amount of resources and effort. In spite of the costs, labeling and categorizing entities is essential for NLP tasks such as semantic evaluation. Even though annotation can be done by non-experts in most cases, due to the fact that this requires human labor, the process is costly. Another major challenge encountered in data annotation is maintaining the annotation consistency. Annotation efforts are typically carried out by teams of multiple annotators. The annotations need to maintain the consistency in relation to both the domain truth and annotation format while reducing human errors. Annotating a specialized domain that deviates significantly from the general domain, such as fantasy literature, will see a lot of human error and annotator disagreement. So it is vital that proper guidelines and error reduction mechanisms are enforced. One such way to enforce these constraints is using a specialized application. Such an app can ensure that the notations are consistent, and the labels can be pre-defined or restricted reducing the room for errors. In this paper, we present SHADE, an annotation software that can be used to annotate entities in the high fantasy literature domain. Specifically in Dungeons and Dragons lore extracted from the Forgotten Realms Fandom Wiki.
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References · 6
- 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
- 2020Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingcited by 1,009
- 2021SciXGen: A Scientific Paper Dataset for Context-Aware Text Generationcited by 22
- 2018Legal Document Retrieval using Document Vector Embeddings and Deep Learningcited by 13
- 2017Synergistic Union of Word2Vec and Lexicon for Domain Specific Semantic Similaritycited by 8
- 2022Synthesis and Evaluation of a Domain-specific Large Data Set for Dungeons & Dragonscited by 5
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