Triple
T400843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opera Software |
E9276
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object | Oslo, Norway |
E3654
|
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: Oslo, Norway | Statement: [Opera Software, headquartersLocation, Oslo, Norway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oslo, Norway Context triple: [Opera Software, headquartersLocation, Oslo, Norway]
-
A.
Oslo
chosen
Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
-
B.
Lillehammer
Lillehammer is a Norwegian town in the Gudbrandsdalen valley, best known internationally for staging the 1994 Winter Olympics.
-
C.
Lysaker, Norway
Lysaker, Norway is a suburban area in Bærum just west of Oslo, known as a residential and commercial hub and historically associated with notable figures such as explorer Fridtjof Nansen.
-
D.
Copenhagen
Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
-
E.
Sarpsborg
Sarpsborg is a historic city and municipality in Viken county, Norway, known as one of the country’s oldest towns and an important industrial and administrative center in the Østfold region.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ec8e655c819081eff85c0ef55fa5 |
completed | Feb. 28, 2026, 1:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a41772e19c8190b02a212f13b4d8aa |
completed | March 1, 2026, 10:39 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.