Triple
T21248397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umeå Airport |
E523677
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Umeå |
—
|
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: Umeå | Statement: [Umeå Airport, serves, Umeå]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Umeå Context triple: [Umeå Airport, serves, Umeå]
-
A.
Umeå
chosen
Umeå is a university city in northern Sweden known for its cultural scene, research institutions, and role as a regional economic hub.
-
B.
Luleå
Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
-
C.
Skellefteå
Skellefteå is a city in northern Sweden known for its growing high-tech and green industry sector, particularly in battery manufacturing, as well as its ice hockey tradition.
-
D.
Sundsvall
Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
-
E.
Piteå
Piteå is a coastal town in northern Sweden known for its historic wooden architecture, archipelago, and role as a regional cultural and industrial center in Norrbotten County.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359b756c819085480ca4174c53c2 |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 3:55 p.m.