Triple
T10603309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bansin |
E275805
|
entity |
| Predicate | nearbyPlace |
P2064
|
FINISHED |
| Object | Ahlbeck |
E275804
|
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: Ahlbeck | Statement: [Bansin, nearbyPlace, Ahlbeck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ahlbeck Context triple: [Bansin, nearbyPlace, Ahlbeck]
-
A.
Ahlbeck
chosen
Ahlbeck is a seaside resort town on the Baltic island of Usedom in Germany, known for its historic pier and well-preserved resort architecture.
-
B.
Birkett
Birkett is a well-known hillwalking guidebook and classification list of Lake District fells compiled by Bill Birkett.
-
C.
Ainsdale
Ainsdale is a coastal residential area and seaside district near Formby in Merseyside, England, known for its sandy beaches and nature reserves.
-
D.
Keelesdale
Keelesdale is a historic residential neighbourhood in Toronto, Ontario, known for its early suburban development and proximity to the former industrial and rail corridors of the old Township of York.
-
E.
Hawkenbury
Hawkenbury is a residential suburb and community area of Royal Tunbridge Wells 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6ded6d698819084f96f46ea941461 |
completed | April 8, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95eaffcd0819098e0a06a731b602f |
completed | April 10, 2026, 8:33 p.m. |
Created at: April 8, 2026, 7:32 p.m.