Triple
T10536716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Västmanland |
E248581
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Arboga |
E857515
|
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: Arboga | Statement: [Västmanland, hasCity, Arboga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arboga Context triple: [Västmanland, hasCity, Arboga]
-
A.
Arboga
chosen
Arboga is a historic small town in central Sweden known for its medieval heritage and well-preserved old town.
-
B.
Rimforsa
Rimforsa is a small locality in Kinda Municipality in Östergötland County, Sweden.
-
C.
Strömholm
Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
-
D.
Gislaved
Gislaved is a tire brand known for producing reliable winter and all-season tires, particularly popular in Northern and Central Europe.
-
E.
Svalöv
Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a554fb4819081e9618bab051dc6 |
completed | April 7, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96b3d6f6c81908d8247da9d9caab2 |
completed | April 10, 2026, 9:27 p.m. |
Created at: April 6, 2026, 12:31 p.m.