Triple
T23662732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danaids |
E584492
|
entity |
| Predicate | haveMythologicalTheme |
P45276
|
FINISHED |
| Object | forced marriage |
—
|
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: forced marriage | Statement: [Danaids, haveMythologicalTheme, forced marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveMythologicalTheme Context triple: [Danaids, haveMythologicalTheme, forced marriage]
-
A.
hasMythologicalFeature
chosen
Indicates that an entity possesses a characteristic, attribute, or element derived from mythology or mythological beings.
-
B.
hasMythologicalDomain
Indicates that a mythological figure, deity, or entity is associated with or rules over a particular conceptual or physical domain (such as the sea, war, or the underworld).
-
C.
mythologicalCategory
Indicates that one entity is classified as belonging to the mythological type, group, or category represented by the other entity.
-
D.
mythologicalContent
Indicates that the subject contains, references, or is associated with myths, mythological narratives, or myth-based elements.
-
E.
hasMythologicalNamesake
Indicates that one entity is named after, or shares its name with, a figure or element from mythology.
- 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_69e248ffc0888190ae23c4731eb8b7ac |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4094c448190be12402422451e89 |
completed | April 29, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:50 p.m.