Triple
T12419285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norrviken Lake |
E296722
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Rotebro |
E164396
|
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: Rotebro | Statement: [Norrviken Lake, locatedNear, Rotebro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rotebro Context triple: [Norrviken Lake, locatedNear, Rotebro]
-
A.
Rotebro
chosen
Rotebro is a suburban district in the northern Stockholm area of Sweden, known for its residential neighborhoods and commuter connections.
-
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.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
-
D.
Fagerborg
Fagerborg is a residential neighborhood in Oslo, Norway, known for its central location, historic buildings, and proximity to major educational institutions.
-
E.
Grefsen
Grefsen is a residential neighborhood in Oslo, Norway, known for its hillside location with views over the city and access to public transport and green areas.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d6efd748190a5d9396a343e41e1 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f634933b9881909fd592ede7c3e49c |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:55 p.m.