Triple
T1049240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rossendale borough |
E22655
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Waterfoot |
E51939
|
NE 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: Waterfoot | Statement: [Rossendale borough, contains, Waterfoot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waterfoot Context triple: [Rossendale borough, contains, Waterfoot]
-
A.
Waterfoot
chosen
Waterfoot is a small town in the Rossendale Valley of Lancashire, England, known historically for its textile industry and scenic Pennine surroundings.
-
B.
Lightwater
Lightwater is a village and civil parish in the English county of Surrey, known for its residential character and proximity to heathland and countryside.
-
C.
Dighty Water
Dighty Water is a small river in Angus, Scotland, that flows through the Monifieth and Dundee area before entering the Firth of Tay.
-
D.
Waterman
Waterman is a historic luxury pen and writing instruments brand known for its high-quality fountain pens and elegant design.
-
E.
Bluewater
Bluewater is a large out-of-town shopping and leisure centre located in Kent, England.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b2c6208190b6fdf3e93b1b1d04 |
completed | March 1, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bcd3a4481908f7d9f13e3697fa9 |
completed | March 7, 2026, 2:53 p.m. |
Created at: March 1, 2026, 7:42 p.m.