Triple
T14056515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tårnby Municipality |
E338233
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Tårnby |
E1094147
|
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: Tårnby | Statement: [Tårnby Municipality, hasTown, Tårnby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tårnby Context triple: [Tårnby Municipality, hasTown, Tårnby]
-
A.
Tårnby
chosen
Tårnby is a town on the island of Amager in eastern Denmark, forming part of the Copenhagen metropolitan area.
-
B.
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.
-
C.
Herlev
Herlev is a suburban municipality and town in the Capital Region of Denmark, located just northwest of central Copenhagen.
-
D.
Ballerup
Ballerup is a suburban municipality near Copenhagen in eastern Denmark, known for its residential areas, business parks, and sports facilities.
-
E.
Birkerød
Birkerød is a suburban town in northeastern Zealand, Denmark, known for its residential character, green surroundings, and proximity to Copenhagen.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c8e6d008190af8892f34c5cefbd |
completed | April 14, 2026, 1:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd54fa19c081908e6467ee7b79f02a |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 9, 2026, 10:20 p.m.