Triple
T23641211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madoc ab Owain Gwynedd |
E583898
|
entity |
| Predicate | regionOfMythReception |
P109542
|
FINISHED |
| Object | Wales |
—
|
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: Wales | Statement: [Madoc ab Owain Gwynedd, regionOfMythReception, Wales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOfMythReception Context triple: [Madoc ab Owain Gwynedd, regionOfMythReception, Wales]
-
A.
languageOfMyths
Indicates that the subject is the language in which the myths associated with the object are told or recorded.
-
B.
culturalRegionOfLore
chosen
Indicates that a particular cultural region is the primary setting, origin, or contextual background for a given body of lore or tradition.
-
C.
subsequentMythology
Indicates that one mythology develops later than, or is derived from, another mythology in time or tradition.
-
D.
mythologicalCategory
Indicates that one entity is classified as belonging to the mythological type, group, or category represented by the other entity.
-
E.
expandsMythologyOf
Indicates that one entity broadens, enriches, or adds new elements to the mythological background or lore associated with another entity.
- 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_69e248fe1c2c8190ac914d2442ff3d26 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b28152108190972ac680cba986d7 |
completed | April 29, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:48 p.m.