Triple
T4882962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huvudsta |
E109372
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Västra Skogen |
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: Västra Skogen | Statement: [Huvudsta, adjacentTo, Västra Skogen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Västra Skogen Context triple: [Huvudsta, adjacentTo, Västra Skogen]
-
A.
Hälsingland forests
Hälsingland forests are a vast, sparsely populated woodland region in central Sweden known for their boreal landscapes, wildlife, and traditional rural settlements.
-
B.
Dalsland
Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
-
C.
Härjedalen
Härjedalen is a sparsely populated historical province in central Sweden known for its mountainous landscapes, wilderness areas, and outdoor recreation.
-
D.
Skogås
Skogås is a suburban district in the southern Stockholm area of Sweden, known primarily as a residential community with good commuter connections to central Stockholm.
-
E.
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.
- 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_69bd440e9d64819083e82cf33b4d9570 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddfff0c81908fb148a6f6508334 |
completed | March 20, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be68070bb0819095bda199cc966d31 |
completed | March 21, 2026, 9:42 a.m. |
Created at: March 20, 2026, 1:27 p.m.