Triple
T7584036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiruna |
E179561
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Luleå |
E160272
|
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: Luleå | Statement: [Kiruna, connectedTo, Luleå]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luleå Context triple: [Kiruna, connectedTo, Luleå]
-
A.
Luleå
chosen
Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
-
B.
Umeå
Umeå is a university city in northern Sweden known for its cultural scene, research institutions, and role as a regional economic hub.
-
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.
Pajala
Pajala is a small town in northern Sweden’s Lapland region, known for its remote Arctic setting and as the backdrop of several works by author Mikael Niemi.
-
E.
Gällivare
Gällivare is a mining town in northern Sweden known for its significant iron ore deposits and role in the region’s mining industry.
- 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_69c69f327db881909a21ae3b156f8ded |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f993cd0c8190864f801074625a32 |
completed | March 27, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9d13a8b108190a0b13592f3a6362e |
completed | March 30, 2026, 1:26 a.m. |
Created at: March 27, 2026, 3:52 p.m.