Triple
T11039146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Småland |
E260962
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Ljungby |
E854805
|
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: Ljungby | Statement: [Småland, hasCity, Ljungby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ljungby Context triple: [Småland, hasCity, Ljungby]
-
A.
Ljungby
chosen
Ljungby is a small Swedish town in southern Småland known for its lakeside surroundings, forestry-based economy, and role as a local commercial and cultural center.
-
B.
Ronneby
Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
-
C.
Mjölby
Mjölby is a small Swedish town known for its agricultural surroundings and location in the southern part of Östergötland County.
-
D.
Sandviken
Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
-
E.
Hörby
Hörby is a small municipality in southern Sweden’s Skåne County, known for its rural landscape and traditional Swedish town character.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797fe93b081909d58bfd4b42715f0 |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e73e7f68819097213e4601c07ee8 |
completed | April 18, 2026, 8:19 p.m. |
Created at: April 8, 2026, 9:26 p.m.