Triple
T1074943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walton-on-Thames |
E23814
|
entity |
| Predicate | hasRiversideAmenity |
P19053
|
FINISHED |
| Object | Walton riverside 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: Walton riverside promenade | Statement: [Walton-on-Thames, hasRiversideAmenity, Walton riverside promenade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiversideAmenity Context triple: [Walton-on-Thames, hasRiversideAmenity, Walton riverside promenade]
-
A.
hasWaterfrontArea
chosen
Indicates that an entity possesses or includes an area directly adjacent to or bordering a body of water.
-
B.
hasParkAlongBank
Indicates that a park is located adjacent to or running alongside the bank of a water body.
-
C.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
D.
hasRiverActivity
Indicates that an entity engages in, supports, or is associated with activities occurring on or along a river.
-
E.
hasNearbyLake
Indicates that one entity is located close to or in the vicinity of a lake.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92e480c81909a848b48c196a293 |
completed | March 1, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69a4b73ba8208190be7f3cef8c18689b |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.