Triple
T13954072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Färjestad BK |
E335607
|
entity |
| Predicate | basedIn |
P40
|
FINISHED |
| Object | Karlstad, Sweden |
E370713
|
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: Karlstad, Sweden | Statement: [Färjestad BK, basedIn, Karlstad, Sweden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karlstad, Sweden Context triple: [Färjestad BK, basedIn, Karlstad, Sweden]
-
A.
Karlskoga, Sweden
Karlskoga, Sweden is an industrial town in central Sweden best known for its historic arms manufacturer Bofors and its association with Alfred Nobel.
-
B.
Karlstad
chosen
Karlstad is a city in central Sweden known as the capital of Värmland County, situated on the northern shore of Lake Vänern.
-
C.
Södertälje, Sweden
Södertälje, Sweden is an industrial city southwest of Stockholm known for its major manufacturing plants, particularly in the automotive and heavy vehicle sectors.
-
D.
Karlskoga
Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
-
E.
Karlshamn
Karlshamn is a coastal town in southern Sweden known for its harbor, archipelago, and role as a regional industrial and transport hub.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e146720819085d0f5eae558b7a4 |
completed | April 14, 2026, 12:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1d0735c81909ec0eab090af08a1 |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:17 p.m.