Triple
T1282593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knivsta Municipality |
E27359
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Uppsala |
E36359
|
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: Uppsala | Statement: [Knivsta Municipality, locatedNear, Uppsala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uppsala Context triple: [Knivsta Municipality, locatedNear, Uppsala]
-
A.
Uppsala
chosen
Uppsala is a historic Swedish city north of Stockholm, known for its prestigious university, medieval cathedral, and role as a cultural and ecclesiastical center.
-
B.
Lund
Lund is a common Scandinavian surname of Swedish origin.
-
C.
Nyköping
Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
-
D.
Gothenburg
Gothenburg is Sweden’s second-largest city, a major port on the country’s west coast known for its maritime heritage, universities, and vibrant cultural scene.
-
E.
Jönköping
Jönköping is a city in southern Sweden, located at the southern end of Lake Vättern and known as a regional commercial and logistical hub.
- 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b47be08190828a1c0a11d94ce8 |
completed | March 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4682bac88190a25bcc211179296d |
completed | March 8, 2026, 9:50 a.m. |
Created at: March 1, 2026, 7:50 p.m.