Triple
T20496425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sickla Lake |
E502885
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Sickla Köpkvarter |
—
|
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: Sickla Köpkvarter | Statement: [Sickla Lake, locatedNear, Sickla Köpkvarter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sickla Köpkvarter Context triple: [Sickla Lake, locatedNear, Sickla Köpkvarter]
-
A.
Sickla Köpkvarter
chosen
Sickla Köpkvarter is a large shopping and entertainment district in the Sickla area of Nacka, just outside central Stockholm, Sweden.
-
B.
Stöllet
Stöllet is a small locality in central Sweden situated within Torsby Municipality in Värmland County.
-
C.
Sköllersta
Sköllersta is a locality in central Sweden situated within Örebro County, known as one of the settlements in Hallsberg Municipality.
-
D.
Kallhäll
Kallhäll is a suburban district in the Stockholm metropolitan area of Sweden, known for its residential neighborhoods and commuter connections.
-
E.
Sköndal
Sköndal is a residential district in southern Stockholm, Sweden, known for its green areas and proximity to lakes.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbdeb9c819090a30a7961146c93 |
completed | April 20, 2026, 9:38 p.m. |
Created at: April 16, 2026, 11:35 a.m.