Etiological Origin Myth Type Classifier
Keep independently annotated etiological explanation domains separate; not scientific origin evidence. Independently annotated feature columns in order: natural phenomenon origin explained, place origin explained, custom origin explained. Compatible classes are not established identities; unknown evidence retained. No automatic semantic parsing, diagnosis, authenticity or safety determination.
Description
An etiological narrative explains why a feature, place or custom has its present form.
An etiological narrative explains why a feature, place or custom has its present form.1
Independently annotated motifs can support several explanatory categories without verifying the story's literal cause. Use this tool to compare independently annotated features with the stated candidate rules.
When to use Etiological Origin Myth Type Classifier
Use this tool to compare independently annotated features with the stated candidate rules. Identify the community, narrative version, source edition and interpretation context; prepare any annotations independently.
How to use Etiological Origin Myth Type Classifier and understand its results
- Identify the community, narrative version, source edition and interpretation context; prepare any annotations independently.
- Enter observedFeatureFlags, featureKnownFlags, using the field meanings and rules below, then run the tool.
- Read result.compatibleClasses, result.witnessedClasses, result.unknownFeatureIndices. Interpret the fields using their units, signs and evidence conventions below.
- If input validation fails, correct the reported field and run again. Before applying the result, check reference scope, model assumptions and any missing evidence or placeholder values.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| observedFeatureFlags | Observed feature flags; binary 0/1 under the definitions below | list of number | Required |
| featureKnownFlags | Feature known flags; binary 1=known, 0=unknown, in the order described below | list of number | Required |
Supply binary observation and binary known flags in the fixed column order below. Rule −1 ignores a feature; rule 0 requires known absence and rule 1 requires known presence for a witnessed match. A compatible match permits unknown required features but rejects conflicting known observations. Return every compatible candidate, every fully witnessed candidate and zero-based unknown indices. All-unknown evidence can leave every candidate compatible while witnessing none; incompatible evidence may return no candidates. There is no automatic text interpretation or judgment of truth, authenticity or narrative quality.
| Zero-based column | Observed feature |
|---|---|
| 0 | natural phenomenon origin explained |
| 1 | place origin explained |
| 2 | custom origin explained |
| Candidate | natural phenomenon origin explained | place origin explained | custom origin explained |
|---|---|---|---|
| natural-origin-candidate | Known present (1) | Ignored | Ignored |
| place-origin-candidate | Ignored | Known present (1) | Ignored |
| custom-origin-candidate | Ignored | Ignored | Known present (1) |
compatible={candidate:all constraints ignored, unknown or matched}; witnessed={candidate:all nonignored constraints known and matched}; unknown={i:known_i=0} Use the exact units, boundary rules, ordering and missing-evidence conventions above.
| Output field | Meaning | Value type |
|---|---|---|
| result | Structured calculation or selected reference, with fields listed below | object |
| result.compatibleClasses | Every fixed candidate whose rules do not conflict with known features | list of string |
| result.witnessedClasses | Every fixed candidate with all nonignored constraints actually known and matched | list of string |
| result.unknownFeatureIndices | Zero-based indices of unknown feature observations | list of values |
{
"input": {
"observedFeatureFlags": [
1,
1,
1
],
"featureKnownFlags": [
1,
1,
1
]
},
"output": {
"result": {
"compatibleClasses": [
"natural-origin-candidate",
"place-origin-candidate",
"custom-origin-candidate"
],
"witnessedClasses": [
"natural-origin-candidate",
"place-origin-candidate",
"custom-origin-candidate"
],
"unknownFeatureIndices": []
}
}
}Limitations and assumptions
Features and criteria are independent annotations. Compatible candidates and retained unknown evidence do not establish an identity, interpretation, overall pass or permission.
All listed fields require explicit values. Unexpected fields, incorrect types, nonfinite numbers and sparse evidence arrays fail validation; the specific bounds and alignment requirements are stated above. Extremely large inputs or outputs can also be rejected. An input error is distinct from a successful result reporting false, no matches or missing evidence.
Alternative or Complementary methods
Use Egyptian Book of the Dead42 Negative Confessions Lookup for this related task: Negative declarations occur in versions of Egyptian Book of the Dead spell 125.
Use Dragon Type Western Eastern Feathered Serpent Classifier when its separate inputs and assumptions fit the question: Dragon and serpent narratives use different combinations of independently recorded features.
References
-
Etiological Origin Myth Type Classifier — tool.io
Similar or alternative tools
- Egyptian Book of the Dead42 Negative Confessions Lookup
Negative declarations occur in versions of Egyptian Book of the Dead spell 125.
- Dragon Type Western Eastern Feathered Serpent Classifier
Dragon and serpent narratives use different combinations of independently recorded features.