Triple
T10557553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thompson’s Lane, Cambridge |
E249126
|
entity |
| Predicate | hasProximityToWater |
P49291
|
FINISHED |
| Object | close to River Cam |
—
|
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: close to River Cam | Statement: [Thompson’s Lane, Cambridge, hasProximityToWater, close to River Cam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProximityToWater Context triple: [Thompson’s Lane, Cambridge, hasProximityToWater, close to River Cam]
-
A.
hasNearbyWater
chosen
Indicates that one entity is located close to a body of water associated with or relevant to another entity.
-
B.
hasNearbyWaterInfrastructure
Indicates that a location or entity is situated close to water-related infrastructure such as pipes, treatment facilities, or distribution systems.
-
C.
hasNearbyWatersUsedBy
Indicates that a body of water located near an entity is utilized or accessed by another specified entity.
-
D.
hasSurroundingWaters
Indicates that one entity is bordered or encircled by bodies of water associated with another entity.
-
E.
hasEstuaryNear
Indicates that the estuary of a water body is located in close proximity to a specified place or feature.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5271521a4819086d96e1f183ab07a |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:35 p.m.