Triple
T13171358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vasastan |
E312981
|
entity |
| Predicate | hasGreenSpace |
P1495
|
FINISHED |
| Object | Observatorielunden |
E1025588
|
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: Observatorielunden | Statement: [Vasastan, hasGreenSpace, Observatorielunden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Observatorielunden Context triple: [Vasastan, hasGreenSpace, Observatorielunden]
-
A.
Observatorielunden
chosen
Observatorielunden is a central Stockholm park known for its hilltop observatory, green spaces, and views over the Vasastan district.
-
B.
Kagerplassen
Kagerplassen is a lake and recreational water area in South Holland, Netherlands, popular for boating, sailing, and watersports amid a landscape of polders and windmills.
-
C.
Løkken
Løkken is a Danish seaside town known for its sandy beaches, coastal dunes, and popular summer tourism on the North Sea.
-
D.
Østre Bolæren
Østre Bolæren is an island in the Bolærne archipelago in the Oslofjord, known for its coastal scenery, outdoor recreation, and former military installations.
-
E.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c2f22b881908a0af3af0a0af971 |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5e5eacc8190ae39dcdb12c9b563 |
completed | May 3, 2026, 7:14 a.m. |
Created at: April 9, 2026, 9:13 p.m.