Triple
T5890743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garding |
E130980
|
entity |
| Predicate | hasLandAreaRange |
P67295
|
FINISHED |
| Object | between 10 and 20 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: between 10 and 20 square kilometres | Statement: [Garding, hasLandAreaRange, between 10 and 20 square kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandAreaRange Context triple: [Garding, hasLandAreaRange, between 10 and 20 square kilometres]
-
A.
hasLandAreaSquareKilometers
Indicates that an entity possesses a land area measured in square kilometers.
-
B.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
C.
meanSurfaceArea_km2
Indicates the average surface area of an entity measured in square kilometers.
-
D.
landAreaSquareMiles
Indicates the size of a geographic area measured in square miles.
-
E.
areaTotalSquareKilometers
Indicates the total size of something measured in square kilometers.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03fe07b7081909f8577ec3a9a1a8d |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0334bdc308190ad0d7199ab975588 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03fdf954c8190ae97a5c9ce40bdfa |
completed | March 22, 2026, 7:15 p.m. |
Created at: March 22, 2026, 3:58 p.m.