Triple
T22203013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ring 3 (Copenhagen) |
E548727
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Herlev |
—
|
NE NERFINISHED |
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: Herlev | Statement: [Ring 3 (Copenhagen), connects, Herlev]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herlev Context triple: [Ring 3 (Copenhagen), connects, Herlev]
-
A.
Herlev
chosen
Herlev is a suburban municipality and town in the Capital Region of Denmark, located just northwest of central Copenhagen.
-
B.
Hørsholm
Hørsholm is a suburban town in eastern Denmark, located north of Copenhagen in the Capital Region.
-
C.
Humlebæk
Humlebæk is a coastal town in eastern Denmark known for hosting the renowned Louisiana Museum of Modern Art.
-
D.
Hellerup
Hellerup is a suburban district just north of central Copenhagen, known for its affluent residential areas, seaside location, and role as a key transport and commercial hub.
-
E.
Tårnby
Tårnby is a town on the island of Amager in eastern Denmark, forming part of the Copenhagen metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b24c6fc81909e6ae62564846bd1 |
completed | April 28, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:36 p.m.