Triple
T2033508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Möhne Dam |
E44569
|
entity |
| Predicate | reservoirSurfaceArea |
P35437
|
FINISHED |
| Object | approximately 10.4 square kilometres |
—
|
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: approximately 10.4 square kilometres | Statement: [Möhne Dam, reservoirSurfaceArea, approximately 10.4 square kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reservoirSurfaceArea Context triple: [Möhne Dam, reservoirSurfaceArea, approximately 10.4 square kilometres]
-
A.
lakeArea
Indicates the surface area measurement of a lake.
-
B.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
C.
reservoir
Indicates that one entity serves as a storage or containment source (often for a resource) that can supply or affect another entity.
-
D.
areaWater
Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
-
E.
drainageAreaApprox
Indicates that one entity has an approximate drainage area measured or characterized by the other entity.
- 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_69a889144f2481909932f0746a93023d |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb93255248190bd47a54a7b3c7447 |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb7a8125881909c0cb58b777c1faa |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb90ec7948190bbfb0329e9e67cca |
completed | March 7, 2026, 5:35 a.m. |
Created at: March 4, 2026, 7:39 p.m.