Triple
T8980567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Wyre |
E214512
|
entity |
| Predicate | hasMonitoringStation |
P59133
|
FINISHED |
| Object | St Michael's on Wyre gauging station |
—
|
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: St Michael's on Wyre gauging station | Statement: [River Wyre, hasMonitoringStation, St Michael's on Wyre gauging station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMonitoringStation Context triple: [River Wyre, hasMonitoringStation, St Michael's on Wyre gauging station]
-
A.
hasGagingStation
chosen
Indicates that one entity is equipped with, or associated with, a gaging station used to measure and monitor conditions such as water level or flow.
-
B.
hasStationNear
Indicates that one entity has a station located in close proximity to another entity.
-
C.
hasMeteorologicalStation
Indicates that one entity possesses, hosts, or is equipped with a meteorological station used for observing and recording weather-related data.
-
D.
hasStationManager
Indicates that an entity has another entity serving as its station manager.
-
E.
hasFocalStations
Indicates that an entity is associated with one or more primary or central stations that serve as its main points of focus or operation.
- 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_69ca839ea8b88190922c6a326ffcc0d3 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc67a615b081909b88e761be879802 |
completed | April 1, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed9a2d48190ad11381078e823b7 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:03 p.m.