Triple
T3750502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troms og Finnmark |
E81316
|
entity |
| Predicate | containsIsland |
P970
|
FINISHED |
| Object | Senja |
E79491
|
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: Senja | Statement: [Troms og Finnmark, containsIsland, Senja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Senja Context triple: [Troms og Finnmark, containsIsland, Senja]
-
A.
Senja
chosen
Senja is Norway’s second-largest island, renowned for its dramatic coastal mountains, fishing villages, and scenic Arctic landscapes.
-
B.
Bilibino
Bilibino is a small town in Russia’s Far East best known for hosting one of the world’s northernmost nuclear power plants.
-
C.
Somero
Somero is a small town and municipality in southwestern Finland known for its rural landscapes and agricultural heritage.
-
D.
Sanem
Sanem is a commune and town in southwestern Luxembourg known for its historic castle and proximity to the industrial city of Esch-sur-Alzette.
-
E.
Kurilsk
Kurilsk is a small Russian town on Iturup Island in the Kuril archipelago, serving as an administrative and fishing center in the North Pacific.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb6d0ac4819092c9a41cc60f518d |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db34aa5c8190ba3f22ee0f1f4208 |
completed | March 14, 2026, 3:51 a.m. |
Created at: March 8, 2026, 3:35 p.m.