Triple
T2919699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kungsholmen |
E78688
|
entity |
| Predicate | hasMetroStation |
P522
|
FINISHED |
| Object | Kristineberg |
E310295
|
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: Kristineberg | Statement: [Kungsholmen, hasMetroStation, Kristineberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kristineberg Context triple: [Kungsholmen, hasMetroStation, Kristineberg]
-
A.
Kristineberg
chosen
Kristineberg is a residential neighborhood in the western part of central Stockholm, known for its waterfront location and green areas.
-
B.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
C.
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."
-
D.
Lindholmen
Lindholmen is a waterfront district in Gothenburg, Sweden, known as a major hub for education, research, and technology companies.
-
E.
Lindholmen
Lindholmen is a small locality in Vallentuna Municipality in Stockholm County, Sweden, known for its residential character and proximity to natural and historical sites.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad96a53f8c8190b188d549f1161e84 |
completed | March 8, 2026, 3:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0866113688190ae222813b017c69f |
completed | March 10, 2026, 9 p.m. |
Created at: March 8, 2026, 2:54 p.m.