Triple
T875078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stockholm Arlanda Airport |
E18898
|
entity |
| Predicate | focusCityFor |
P164
|
FINISHED |
| Object | Eurowings |
E72036
|
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: Eurowings | Statement: [Stockholm Arlanda Airport, focusCityFor, Eurowings]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eurowings Context triple: [Stockholm Arlanda Airport, focusCityFor, Eurowings]
-
A.
Eurowings
chosen
Eurowings is a German low-cost airline and Lufthansa subsidiary that operates short- and long-haul flights across Europe and selected international destinations.
-
B.
S7 Airlines
S7 Airlines is a major Russian airline based in Novosibirsk that operates extensive domestic and international routes, particularly across Russia, Europe, and Asia.
-
C.
Wizz Air
Wizz Air is a Hungarian ultra-low-cost airline known for operating an extensive network of budget flights across Europe and surrounding regions.
-
D.
Transavia
Transavia is a Dutch low-cost airline operating scheduled and charter flights across Europe and North Africa.
-
E.
Lufthansa
Lufthansa is Germany’s largest airline and a major global carrier known for its extensive international network and role in shaping modern airline alliances.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acae12948190923d31966c26a130 |
completed | March 1, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7ee0053d88190be8705b42d172ab7 |
completed | March 4, 2026, 8:32 a.m. |
Created at: March 1, 2026, 7:39 p.m.