Triple
T10824747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frederiksberg |
E255466
|
entity |
| Predicate | hasGreenSpace |
P1495
|
FINISHED |
| Object | Søndermarken |
E888237
|
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: Søndermarken | Statement: [Frederiksberg, hasGreenSpace, Søndermarken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Søndermarken Context triple: [Frederiksberg, hasGreenSpace, Søndermarken]
-
A.
Søndermarken
chosen
Søndermarken is a historic public park in Copenhagen, Denmark, known for its wooded landscapes, walking paths, and proximity to Frederiksberg Gardens and the Copenhagen Zoo.
-
B.
Maarkedal
Maarkedal is a rural municipality in the Flemish Ardennes of East Flanders, Belgium, known for its hilly landscape and cycling routes.
-
C.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
-
D.
Nakskov
Nakskov is a historic port town in southern Denmark located on the island of Lolland, known for its maritime industry and coastal setting.
-
E.
Bragernes
Bragernes is a historic former town and district that now forms the northern part of the city of Drammen in Norway.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d734d0389c819090a892693c4046ed |
completed | April 9, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb1096cbc81908f3eda562c2da042 |
completed | April 14, 2026, 9:26 p.m. |
Created at: April 8, 2026, 9:19 p.m.