Triple
T16812002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vestre Toten |
E408636
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Hurdal |
E862684
|
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: Hurdal | Statement: [Vestre Toten, locatedNear, Hurdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hurdal Context triple: [Vestre Toten, locatedNear, Hurdal]
-
A.
Hurdal
chosen
Hurdal is a rural municipality in Viken county, Norway, known for its forests, lakes, and outdoor recreation areas such as Hurdalssjøen.
-
B.
Oedheim
Oedheim is a small municipality in the Heilbronn district of Baden-Württemberg in southern Germany.
-
C.
Maselheim
Maselheim is a rural municipality in the district of Biberach in the federal state of Baden-Württemberg in southern Germany.
-
D.
Hjorthagen
Hjorthagen is a residential district in northeastern Stockholm, Sweden, known for its mix of historic workers’ housing and modern developments near the Royal National City Park and the Värtan harbor area.
-
E.
Harestua
Harestua is a village in Viken county, Norway, known for its residential community and proximity to the Harestua Solar Observatory.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2d0793c81909d938ac174a6e63a |
completed | April 18, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c79cdf9c8190aa20d536ca17ab81 |
completed | May 10, 2026, 5:59 p.m. |
Created at: April 10, 2026, 5:23 a.m.