Triple
T6020737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jakobsberg station |
E134055
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Jakobsberg |
E123879
|
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: Jakobsberg | Statement: [Jakobsberg station, locatedIn, Jakobsberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jakobsberg Context triple: [Jakobsberg station, locatedIn, Jakobsberg]
-
A.
Jakobsberg
chosen
Jakobsberg is a major suburban district and commercial center in the Stockholm metropolitan area, serving as the administrative seat of Järfälla Municipality in Sweden.
-
B.
Gustavsberg
Gustavsberg is a locality in Sweden best known for its historic porcelain factory and role as a suburban community in the Stockholm archipelago.
-
C.
Mariaberget
Mariaberget is a historic, picturesque area on the western side of Södermalm in central Stockholm, known for its well-preserved old buildings and panoramic views over the city and Lake Mälaren.
-
D.
Köterberg
Köterberg is a prominent hill in northern Germany known for its panoramic views and popularity among hikers and motorcyclists.
-
E.
Kjerkeberget
Kjerkeberget is a forested hill in Norway that marks the highest natural point within Oslo’s municipal boundaries.
- 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_69c008742a5c8190b9cb9c2787a3d8b3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04fba86a48190984e95d5adf7c7f1 |
completed | March 22, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1136da26081909b753fa8a2a91084 |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:07 p.m.