Triple
T24156256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoeksche Waard |
E598686
|
entity |
| Predicate | hasAreaUnitSquareKilometresApprox |
P13670
|
FINISHED |
| Object | over 300 |
—
|
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 300 | Statement: [Hoeksche Waard, hasAreaUnitSquareKilometresApprox, over 300]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAreaUnitSquareKilometresApprox Context triple: [Hoeksche Waard, hasAreaUnitSquareKilometresApprox, over 300]
-
A.
areaApproxKm2
chosen
Indicates that one entity has an approximate area, measured in square kilometers, given by the other entity.
-
B.
hasLandAreaSquareKilometers
Indicates that an entity possesses a land area measured in square kilometers.
-
C.
areaTotalSquareKilometers
Indicates the total size of something measured in square kilometers.
-
D.
areaApproximateSquareMiles
Indicates that the related entity has an area approximately equal to the specified number of square miles.
-
E.
areaUnit
Indicates the unit of measurement used to express an area value in a given context.
- 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_69e288cb0a3081909ef221744f274384 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e0e4fc9c8190bafabb4f08a2db45 |
completed | April 29, 2026, 10:43 a.m. |
| PD | Predicate disambiguation | batch_69f176585f3481909beb907de252cd98 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:31 p.m.