Triple
T7993705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bleikøya |
E186070
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | inner Oslofjord |
E33322
|
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: inner Oslofjord | Statement: [Bleikøya, locatedIn, inner Oslofjord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: inner Oslofjord Context triple: [Bleikøya, locatedIn, inner Oslofjord]
-
A.
Oslofjord
chosen
Oslofjord is a large inlet in southeastern Norway known for its islands, coastal towns, and role as the maritime gateway to Oslo.
-
B.
Østensjø
Østensjø is a residential borough in the southeastern part of Oslo, Norway, known for its lake Østensjøvannet and extensive green areas.
-
C.
Drammensfjord
Drammensfjord is a branch of the Oslofjord in southeastern Norway, known for its deep waters, surrounding industrial and urban areas, and role as an important maritime route.
-
D.
Skudenesfjorden
Skudenesfjorden is a fjord in Rogaland county, southwestern Norway, lying along the coast by the island municipality of Karmøy and opening into the North Sea.
-
E.
Osafjorden
Osafjorden is a side fjord of Norway’s Hardangerfjord, known for its steep mountain scenery and tranquil, narrow waters.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c729afc81909d477b1623ac3f9d |
completed | March 31, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0fe312c81908c6874fa0aabe7d5 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:16 p.m.