Triple
T10717845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shellback |
E252727
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Karlshamn, Sweden |
E691024
|
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: Karlshamn, Sweden | Statement: [Shellback, placeOfBirth, Karlshamn, Sweden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karlshamn, Sweden Context triple: [Shellback, placeOfBirth, Karlshamn, 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.
Karlshamn
Karlshamn is a coastal town in southern Sweden known for its harbor, archipelago, and role as a regional industrial and transport hub.
-
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.
Danderyd, Sweden
Danderyd, Sweden is an affluent suburban municipality just north of Stockholm, known for its high standard of living and residential character.
-
E.
Älmhult, Sweden
Älmhult, Sweden is a small town in southern Sweden best known as the birthplace and original home of the global furniture company IKEA.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6ff36558c81908682adbe7b5dce05 |
completed | April 9, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbb71dd6f88190beb99ca75914fb09 |
completed | April 12, 2026, 3:15 p.m. |
Created at: April 8, 2026, 9:13 p.m.