Triple
T10734792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maera |
E253165
|
entity |
| Predicate | isMythologicalFigureType |
P95710
|
FINISHED |
| Object | mortal or minor divinity (uncertain) |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: mortal or minor divinity (uncertain) | Statement: [Maera, isMythologicalFigureType, mortal or minor divinity (uncertain)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMythologicalFigureType Context triple: [Maera, isMythologicalFigureType, mortal or minor divinity (uncertain)]
-
A.
hasMythicalFigure
Indicates that one entity is associated with, features, or includes a particular mythical or legendary figure.
-
B.
hasMythologicalFeature
Indicates that an entity possesses a characteristic, attribute, or element derived from mythology or mythological beings.
-
C.
hasMythType
Indicates that an entity is associated with or classified under a particular type or category of myth.
-
D.
hasMythologicalNamesake
Indicates that one entity is named after, or shares its name with, a figure or element from mythology.
-
E.
mythologicalFigureFeatured
Indicates that a mythological figure is prominently depicted, referenced, or plays a significant role within a given work, context, or medium.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71021cccc8190ba2d3bbd7d50e2a7 |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f309a44881908e49e3ba478c35b4 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:14 p.m.