Triple
T15198484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valby |
E363201
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Vanløse |
E338246
|
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: Vanløse | Statement: [Valby, borderedBy, Vanløse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vanløse Context triple: [Valby, borderedBy, Vanløse]
-
A.
Vanløse
chosen
Vanløse is a residential district in the western part of Copenhagen, Denmark, known for its local shopping streets, green areas, and strong public transport connections.
-
B.
Uden
Uden is a town in the southern Netherlands known for its location in the province of North Brabant and its proximity to nature reserves and regional industry.
-
C.
Dovrebanen
Dovrebanen is a major Norwegian railway line connecting Oslo and Trondheim across the Dovrefjell mountain area.
-
D.
Tivoli Friheden
Tivoli Friheden is an amusement park and recreational attraction located in Aarhus, Denmark.
-
E.
Alværn
Alværn is a small settlement in Nesodden municipality in Viken county, Norway, known primarily as a residential area within commuting distance of Oslo.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b476208190a5119710c518bb1f |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed3342624819087be35acadd88136 |
completed | May 9, 2026, 6:24 a.m. |
Created at: April 10, 2026, 3:10 a.m.