Triple
T6273112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vágar Airport |
E140585
|
entity |
| Predicate | has scheduled flights to |
P19814
|
FINISHED |
| Object | Billund |
E367160
|
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: Billund | Statement: [Vágar Airport, has scheduled flights to, Billund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Billund Context triple: [Vágar Airport, has scheduled flights to, Billund]
-
A.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
-
B.
Thisted
Thisted is a coastal town and municipality in northwestern Jutland, Denmark, known for its scenic location by the Limfjord and its role as a regional commercial and cultural center.
-
C.
Haderslev
Haderslev is a historic town in southern Denmark known for its medieval cathedral, old town center, and role as a regional cultural and administrative hub.
-
D.
Billund, Denmark
chosen
Billund, Denmark is a small Danish town best known as the birthplace of LEGO and home to the original LEGOLAND theme park.
-
E.
Fagerborg
Fagerborg is a residential neighborhood in Oslo, Norway, known for its central location, historic buildings, and proximity to major educational institutions.
- 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_69c008cc158881908df6ec94a911c736 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063be5a148190a8752426d2d220f8 |
completed | March 22, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c2446ad060819094acd817ba5eadc9 |
completed | March 24, 2026, 7:59 a.m. |
Created at: March 22, 2026, 4:25 p.m.