Triple
T17229729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danderyd Municipality |
E418208
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Enebyberg |
E162456
|
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: Enebyberg | Statement: [Danderyd Municipality, containsSettlement, Enebyberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enebyberg Context triple: [Danderyd Municipality, containsSettlement, Enebyberg]
-
A.
Enebyberg
chosen
Enebyberg is a residential suburban area in the northern part of the Stockholm urban region in Sweden.
-
B.
Blackeberg
Blackeberg is a suburban district in western Stockholm, Sweden, best known internationally as the bleak, wintry backdrop of the Swedish vampire novel and film "Let the Right One In."
-
C.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
-
D.
Lindesberg
Lindesberg is a small historic town in central Sweden known for its mining heritage and lakeside setting.
-
E.
Vingåker
Vingåker is a small locality in Södermanland County, Sweden, known as the hometown of former Swedish Prime Minister Göran Persson.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42df62ec48190b2ed633a5bcc0255 |
completed | April 19, 2026, 1:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01793efa288190b63f641381566bb9 |
completed | May 11, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:39 a.m.