Triple
T1757174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radcliffe |
E38573
|
entity |
| Predicate | hasNeighbour |
P5707
|
FINISHED |
| Object | Kearsley |
E159246
|
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: Kearsley | Statement: [Radcliffe, hasNeighbour, Kearsley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kearsley Context triple: [Radcliffe, hasNeighbour, Kearsley]
-
A.
Kearsley
chosen
Kearsley is a town in Greater Manchester, England, historically part of Lancashire and known for its industrial heritage.
-
B.
Torresdale
Torresdale is a residential neighborhood in the far northeastern section of Philadelphia, Pennsylvania, known for its proximity to the Delaware River and suburban character.
-
C.
Styal
Styal is a village in Cheshire, England, known for its historic cotton mill and role in the early Industrial Revolution.
-
D.
Blackley
Blackley is a suburban area of Manchester, England, known for its residential neighborhoods and proximity to the River Irk and local green spaces.
-
E.
Kilndown
Kilndown is a small rural village in Kent, England, known for its historic church and woodland surroundings.
- 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa643ce88481909d2feef3c5fd849f |
completed | March 6, 2026, 5:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5c4f7cc8190a60d3bd276711b27 |
completed | March 8, 2026, 5:45 p.m. |
Created at: March 4, 2026, 7:31 p.m.