Triple
T4093364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stockholm Palace |
E87755
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Uppland |
E110264
|
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: Uppland | Statement: [Stockholm Palace, locatedIn, Uppland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uppland Context triple: [Stockholm Palace, locatedIn, Uppland]
-
A.
Uppland
chosen
Uppland is a historical province in east-central Sweden that includes parts of the greater Stockholm area and key infrastructure such as Stockholm Arlanda Airport.
-
B.
Dalsland
Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
-
C.
Bohuslän
Bohuslän is a coastal province in western Sweden known for its rugged granite shoreline, fishing villages, and archipelago along the Skagerrak.
-
D.
Närke
Närke is a historical province in central Sweden known for its Central Swedish dialects and its location around the city of Örebro.
-
E.
Småland
Småland is a historical province in southern Sweden known for its forests, lakes, traditional red cottages, and as the birthplace of IKEA founder Ingvar Kamprad.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefcda2f408190bcf2b64535193162 |
completed | March 9, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a83aaabc81908a204008ebe292b2 |
completed | March 14, 2026, 6:26 p.m. |
Created at: March 9, 2026, 3:40 p.m.