Triple
T21320729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sveavägen |
E525605
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Vasastan |
—
|
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: Vasastan | Statement: [Sveavägen, passesThrough, Vasastan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vasastan Context triple: [Sveavägen, passesThrough, Vasastan]
-
A.
Vasastan
chosen
Vasastan is a central district in Stockholm, Sweden, known for its early 20th-century architecture, lively cafés, and residential character.
-
B.
Vaalimaa
Vaalimaa is a major road border crossing point between Finland and Russia, located in southeastern Finland near the Gulf of Finland.
-
C.
Savonia
Savonia is a historical and cultural region in eastern Finland known for its lakes, forests, and distinct Savonian dialect and traditions.
-
D.
Vasto
Vasto is a historic coastal town in Italy’s Abruzzo region, known for its medieval center and views over the Adriatic Sea.
-
E.
Alavus
Alavus is a small town and municipality in the South Ostrobothnia region of western Finland, known for its lakes and rural landscapes.
- 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ed0a2788190b6a71c8c720173dc |
completed | April 21, 2026, 1:42 p.m. |
Created at: April 16, 2026, 4:39 p.m.