Triple
T1265075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sterope |
E12581
|
entity |
| Predicate | hasMythologicalTheme |
P9595
|
FINISHED |
| Object | transformation into stars |
—
|
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: transformation into stars | Statement: [Sterope, hasMythologicalTheme, transformation into stars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMythologicalTheme Context triple: [Sterope, hasMythologicalTheme, transformation into stars]
-
A.
linkedToMythology
chosen
Indicates that something has a connection or association with a mythological tradition, figure, story, or theme.
-
B.
mythologicalRole
Indicates the specific function, duty, or status an entity holds within a mythological or legendary context.
-
C.
mythologicalEvent
Indicates an event or occurrence that takes place within mythological narratives or traditions, often involving gods, heroes, or supernatural phenomena.
-
D.
hasMythType
Indicates that an entity is associated with or classified under a particular type or category of myth.
-
E.
languageOfMyths
Indicates that the subject is the language in which the myths associated with the object are told or recorded.
- F. None of above.
Provenance (3 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4c03573a48190b5851f0a734c2d6f |
completed | March 1, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69a4bb7058e88190825b0cba5ee60b51 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:50 p.m.