Triple
T16242813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Askøy |
E394295
|
entity |
| Predicate | administrativeCentre |
P1474
|
FINISHED |
| Object | Kleppestø |
E1195476
|
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: Kleppestø | Statement: [Askøy, administrativeCentre, Kleppestø]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kleppestø Context triple: [Askøy, administrativeCentre, Kleppestø]
-
A.
Kleppestø
chosen
Kleppestø is a village in Vestland county, Norway, serving as the main commercial and service hub on the island of Askøy near Bergen.
-
B.
Blakset
Blakset is a small village in the municipality of Stryn in Vestland county, western Norway.
-
C.
Kepsut
Kepsut is a town and district in northwestern Turkey, situated within Balıkesir Province and known for its agricultural activities.
-
D.
Shompen
The Shompen are an isolated indigenous people of Great Nicobar Island, known for their semi-nomadic forest-based lifestyle and limited contact with the outside world.
-
E.
Snättringe
Snättringe is a residential district in the southern part of Stockholm County, Sweden, known for its suburban housing and proximity to Segeltorp.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24560060c8190ace4f4c0bd0d886d |
completed | April 17, 2026, 2:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000edf64a88190a9dd0c591c742977 |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:04 a.m.