Triple
T18414024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sveaplan |
E441839
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Sveaplan (Swedish) |
—
|
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: Sveaplan (Swedish) | Statement: [Sveaplan, hasNameInLanguage, Sveaplan (Swedish)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sveaplan (Swedish) Context triple: [Sveaplan, hasNameInLanguage, Sveaplan (Swedish)]
-
A.
Sveaplan
chosen
Sveaplan is a traffic square and intersection area in central Stockholm, Sweden.
-
B.
Swedish Bremen-Verden
Swedish Bremen-Verden was a 17th-century Swedish-ruled duchy in northern Germany formed from the secularized former Prince-Archbishopric of Bremen and the Prince-Bishopric of Verden.
-
C.
the Swede
The Swede is a tense, paranoid guest in Stephen Crane’s short story “The Blue Hotel,” whose escalating fear and mistrust drive much of the story’s conflict and tragedy.
-
D.
Town of Sweden
The Town of Sweden is a suburban-rural municipality in western New York State that includes part of the village of Brockport and lies within the Rochester metropolitan area.
-
E.
Klippan
Klippan is a locality and municipal seat in Skåne County in southern Sweden, known for its historic church and small-town character.
- 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51a26d268819098e6791dc98efcda |
completed | April 19, 2026, 6:08 p.m. |
Created at: April 10, 2026, 10:47 a.m.