Triple
T10323693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blackeberg |
E242704
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Bromma |
E468914
|
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: Bromma | Statement: [Blackeberg, locatedIn, Bromma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bromma Context triple: [Blackeberg, locatedIn, Bromma]
-
A.
Bromma
chosen
Bromma is a suburban district in western Stockholm, Sweden, known for its residential areas, green spaces, and the city’s secondary airport.
-
B.
Södertälje
Södertälje is a Swedish city southwest of Stockholm known for its industrial heritage, diverse population, and strategic location linking Lake Mälaren with the Baltic Sea via the Södertälje Canal.
-
C.
Stockholm Östra
Stockholm Östra is a railway terminus in central Stockholm that serves as the main city station for the narrow-gauge Roslagsbanan commuter rail line.
-
D.
Enköping
Enköping is a small Swedish town known for its numerous themed parks and gardens, often called “Sweden’s nearest town” due to its central location relative to several major cities.
-
E.
Strömsborg
Strömsborg is a small islet in central Stockholm, Sweden, known for its historic buildings and picturesque waterfront setting near the Old Town.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d6ce683c8190bf5385dd04bf2de8 |
completed | April 7, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7503f3df88190bc5acb5e5295f787 |
completed | April 9, 2026, 7:07 a.m. |
Created at: April 6, 2026, 11:50 a.m.