Triple
T26685662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hovedøya Abbey |
E672736
|
entity |
| Predicate | hasRuinsOn |
P163458
|
FINISHED |
| Object | Hovedøya |
—
|
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: Hovedøya | Statement: [Hovedøya Abbey, hasRuinsOn, Hovedøya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuinsOn Context triple: [Hovedøya Abbey, hasRuinsOn, Hovedøya]
-
A.
cityRuinsOf
Indicates that a city is located on or associated with the ruins of another, earlier city.
-
B.
hasArchaeologicalSiteIn
Indicates that an entity possesses, contains, or is associated with an archaeological site located within a specified place or region.
-
C.
hasArchaeologicalSitesFrom
Indicates that an entity contains or is associated with archaeological sites dating from a specified time period or era.
-
D.
hasNumberOfChurchRuins
Indicates the quantity of church ruins associated with a given entity.
-
E.
hasRomanRemains
Indicates that the subject contains or is the location of physical remains or archaeological evidence from the Roman period.
- 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_69eecda2066c8190a344218afa5e89c1 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f638d11c988190af7fd4572b08e038 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f63709e4848190b5cf322e06b23fb6 |
completed | May 2, 2026, 5:40 p.m. |
| PDg | Predicate description generation | batch_69f638344b148190bf0414ef7c5f1f38 |
completed | May 2, 2026, 5:45 p.m. |
Created at: April 27, 2026, 3:22 a.m.