Ontology of folktales in the Greater Mekong Subregion
Bibliographic record
Abstract
The goal of this research is to use the digital humanities research concept in the folktales study in the Greater Mekong Subregion (GMS). This paper presents the second phase of the research, focusing on developing ontologies of folktales in the GMS. The ontology development comprised two processes: (1) ontology design and development and (2) ontology documentation. In both processes, domain knowledge and ontology of folktales were collected, captured, revised, and evaluated by experts in the field of folktale studies, literary studies, Asian studies, and ontology development. The outcome of this research is domain ontologies for folktales in the GMS. Approximately, 74 concepts of folktales in the GMS have been defined and classified into classes and subclasses, including some necessary scope notes and relationships of the topics. This developed ontology will be useful for the development of a semantic digital library of GMS folktales in the next steps of this research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".