Triple
T11216390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swedish west coast |
E265448
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Marstrand |
E681369
|
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: Marstrand | Statement: [Swedish west coast, hasTown, Marstrand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marstrand Context triple: [Swedish west coast, hasTown, Marstrand]
-
A.
Marstrand
chosen
Marstrand is a historic seaside town and popular sailing destination on Sweden’s west coast, known for its fortress and picturesque archipelago setting.
-
B.
Grimstad
Grimstad is a coastal town and municipality in southern Norway known for its maritime heritage, charming wooden houses, and role as a summer tourist destination.
-
C.
Egersund
Egersund is a coastal town in southwestern Norway known for its fishing industry, historic wooden architecture, and scenic harbor.
-
D.
Balestrand
Balestrand is a picturesque village in western Norway known for its fjordside scenery, historic wooden hotels, and role as a gateway to exploring the Sognefjord region.
-
E.
Farsund
Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8e8eef48190932a85784ce15c86 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e49762e3188190ba3c0e01cf04f6a1 |
completed | April 19, 2026, 8:50 a.m. |
Created at: April 8, 2026, 9:30 p.m.