Triple
T8095593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baguley tram stop |
E188975
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Baguley |
E35768
|
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: Baguley | Statement: [Baguley tram stop, locatedIn, Baguley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baguley Context triple: [Baguley tram stop, locatedIn, Baguley]
-
A.
Baguley
chosen
Baguley is a suburban area in Wythenshawe, south Manchester, England, known primarily as a residential district with local transport links and amenities.
-
B.
Boddam
Boddam is a coastal fishing village in Aberdeenshire, Scotland, known for its historic lighthouse and rugged North Sea shoreline.
-
C.
Bilbrook
Bilbrook is a village in Staffordshire, England, known as the place where geneticist Reginald Punnett died.
-
D.
Hellingly
Hellingly is a village and civil parish in East Sussex, England, known for its rural character and historic parish church.
-
E.
Bewdley
Bewdley is a historic riverside town in Worcestershire, England, known for its Georgian architecture and picturesque setting on the River Severn.
- 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4291f1d4819098985ac2b20b6c75 |
completed | March 31, 2026, 3:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd3438ae2481909549a05f195cda39 |
completed | April 1, 2026, 3:05 p.m. |
Created at: March 30, 2026, 5:30 p.m.