Triple
T10851999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MCH Messecenter Herning |
E256167
|
entity |
| Predicate | totalSiteArea |
P58710
|
FINISHED |
| Object | over 400000 square metres |
—
|
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: over 400000 square metres | Statement: [MCH Messecenter Herning, totalSiteArea, over 400000 square metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalSiteArea Context triple: [MCH Messecenter Herning, totalSiteArea, over 400000 square metres]
-
A.
hasAreaTotal
chosen
Indicates the total surface area associated with an entity, typically measured over its entire extent.
-
B.
coveredArea
Indicates that one entity occupies or extends over a specific spatial region or surface area associated with another entity.
-
C.
roofArea
Indicates the total surface area covered by the roof of a structure.
-
D.
standardArea
Indicates that an entity has a designated or officially defined area or size that serves as a standard reference.
-
E.
acquiredLandArea
Indicates the total area of land that has been obtained or taken possession of through an acquisition.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75117b76c8190b0fb216b1428c3c7 |
completed | April 9, 2026, 7:11 a.m. |
| PD | Predicate disambiguation | batch_69d70d2b51448190bae748ed6c23edde |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.