Triple
T21946295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Darby, Pennsylvania |
E541940
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Kirklyn |
—
|
NE NERFINISHED |
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: Kirklyn | Statement: [Upper Darby, Pennsylvania, hasSubdivision, Kirklyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kirklyn Context triple: [Upper Darby, Pennsylvania, hasSubdivision, Kirklyn]
-
A.
Kirklyn
chosen
Kirklyn is a residential neighborhood located within Upper Darby Township in Delaware County, Pennsylvania.
-
B.
Kingsdale
Kingsdale is a remote limestone valley in the Yorkshire Dales of northern England, known for its dramatic karst scenery, caves, and walking routes.
-
C.
Kinsley
Kinsley is a village in West Yorkshire, England, situated within the metropolitan borough of the City of Wakefield.
-
D.
Kierling
Kierling is a small locality in Lower Austria best known as the place where writer Franz Kafka spent his final days and died.
-
E.
Kilnsey
Kilnsey is a small rural village in the Yorkshire Dales of northern England, known for its dramatic limestone crag and scenic countryside.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12427c2b48190949c41bd3be2d9f3 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:57 p.m.