Triple
T35287306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Stavanger |
E1019120
|
entity |
| Predicate | hasApproximateNumberOfBuildings |
P11484
|
FINISHED |
| Object | about 170 wooden houses |
—
|
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: about 170 wooden houses | Statement: [Old Stavanger, hasApproximateNumberOfBuildings, about 170 wooden houses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfBuildings Context triple: [Old Stavanger, hasApproximateNumberOfBuildings, about 170 wooden houses]
-
A.
numberOfBuildings
chosen
Indicates the total count of buildings associated with a given entity or within a specified context.
-
B.
hasMultipleBuildings
Indicates that an entity possesses, controls, or is associated with more than one distinct building.
-
C.
floorCountOfSurroundingBuildings
Indicates the number of floors in the buildings that are located around or near a given reference building or area.
-
D.
hasStrataCountApprox
Indicates that an entity has an approximate or estimated number of strata (layers), rather than an exact count.
-
E.
hasBaseBuildingFloors
Indicates that something (such as a building or structure) has a specified number of floors in its base or main part.
- 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_69f76de6d39c8190bb11342e4b91ff2b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
Created at: May 3, 2026, 4:03 p.m.