Triple
T15030353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mörby centrum |
E378326
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Danderyd |
E26753
|
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: Danderyd | Statement: [Mörby centrum, serves, Danderyd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danderyd Context triple: [Mörby centrum, serves, Danderyd]
-
A.
Bromma
Bromma is a suburban district in western Stockholm, Sweden, known for its residential areas, green spaces, and the city’s secondary airport.
-
B.
Danderyd, Sweden
Danderyd, Sweden is an affluent suburban municipality just north of Stockholm, known for its high standard of living and residential character.
-
C.
Häggenås
Häggenås is a small locality in Jämtland County, northern Sweden, situated within Östersund Municipality.
-
D.
Danderyd Municipality
chosen
Danderyd Municipality is a small, affluent suburban municipality in the Stockholm metropolitan area of Sweden, known for its high standard of living and residential character.
-
E.
Fagersta
Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e2416081908dfba48d7f7b4a84 |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5b4d58481908afbc89263e07b50 |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 2:59 a.m.