Triple
T24286628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tachibana River in Himuka |
E605687
|
entity |
| Predicate | mythologicalRealmContrastedWith |
P155699
|
FINISHED |
| Object | Yomi |
—
|
NE NERFINISHED |
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: Yomi | Statement: [Tachibana River in Himuka, mythologicalRealmContrastedWith, Yomi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mythologicalRealmContrastedWith Context triple: [Tachibana River in Himuka, mythologicalRealmContrastedWith, Yomi]
-
A.
mythologicalCategory
Indicates that one entity is classified as belonging to the mythological type, group, or category represented by the other entity.
-
B.
mythologicalSetting
Indicates that an entity is set within, associated with, or takes place in a mythological or legendary context.
-
C.
mythologicalContent
Indicates that the subject contains, references, or is associated with myths, mythological narratives, or myth-based elements.
-
D.
expandsMythologyOf
Indicates that one entity broadens, enriches, or adds new elements to the mythological background or lore associated with another entity.
-
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. 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f56cdc08190a1e06f67dffd4769 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 18, 2026, 12:08 a.m.