Triple
T16483465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutz, Cologne |
E400378
|
entity |
| Predicate | hasRiverBankUse |
P85477
|
FINISHED |
| Object | recreational promenade |
—
|
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: recreational promenade | Statement: [Deutz, Cologne, hasRiverBankUse, recreational promenade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverBankUse Context triple: [Deutz, Cologne, hasRiverBankUse, recreational promenade]
-
A.
hasRiverUse
Indicates that one entity makes use of a river associated with another entity, such as for transport, irrigation, recreation, or other purposes.
-
B.
hasWaterfrontUse
Indicates that an entity is used, designated, or suitable for activities or purposes directly related to a waterfront or shoreline area.
-
C.
hasParkAlongBank
Indicates that a park is located adjacent to or running alongside the bank of a water body.
-
D.
hasRiverBankSettlement
Indicates that a settlement is located on or directly adjacent to the bank of a river.
-
E.
hasRiverbanksUse
chosen
Indicates how the riverbanks of a river or watercourse are used or managed (e.g., for agriculture, recreation, conservation, or infrastructure).
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e0420ac81908f9a3548ddb3b1ff |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:13 a.m.