Triple
T784122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilmslow |
E16562
|
entity |
| Predicate | hasSuburb |
P747
|
FINISHED |
| Object | Handforth |
E178133
|
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: Handforth | Statement: [Wilmslow, hasSuburb, Handforth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Handforth Context triple: [Wilmslow, hasSuburb, Handforth]
-
A.
Handforth
chosen
Handforth is a village and civil parish in Cheshire, England, situated near the town of Wilmslow and forming part of the Greater Manchester commuter belt.
-
B.
Walsrode
Walsrode is a small town in Lower Saxony, Germany, known for its location in the Lüneburg Heath region and its large bird park, the Weltvogelpark Walsrode.
-
C.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
D.
Ennigerloh
Ennigerloh is a small town in the German state of North Rhine-Westphalia, known as the birthplace of mathematician Karl Weierstrass.
-
E.
Lünen
Lünen is a town in North Rhine-Westphalia, Germany, known as an industrial and commuter city in the Ruhr area.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a769dc6481908f12e872f997acf3 |
completed | March 1, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad3ff724248190aacb72d105f0bb34 |
completed | March 8, 2026, 9:23 a.m. |
Created at: March 1, 2026, 7:37 p.m.