Triple
T7370842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skogsön |
E169996
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Vaxholm |
E498140
|
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: Vaxholm | Statement: [Skogsön, locatedNear, Vaxholm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vaxholm Context triple: [Skogsön, locatedNear, Vaxholm]
-
A.
Vaxholm
chosen
Vaxholm is a small coastal town and municipality in the Stockholm archipelago of eastern Sweden, known for its historic fortress and picturesque waterfront.
-
B.
Värmdö
Värmdö is a large island and municipality in the Stockholm archipelago of Sweden, known for its coastal landscapes, holiday homes, and proximity to Stockholm.
-
C.
Storholmen
Storholmen is an island located in Lake Femunden, one of Norway’s largest inland lakes.
-
D.
Skarpö
Skarpö is an island in the Stockholm archipelago of Sweden, situated within Vaxholm Municipality and known for its coastal scenery and residential character.
-
E.
Värtahamnen
Värtahamnen is a major port and harbor area in Stockholm, Sweden, serving as an important hub for ferry, cargo, and cruise traffic in the Baltic Sea region.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f182df5c81908964fbaa3f8ec790 |
completed | March 27, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8276ec3b88190b720354787f7a735 |
completed | March 28, 2026, 7:09 p.m. |
Created at: March 27, 2026, 3:07 p.m.