Triple
T2945526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senja |
E79491
|
entity |
| Predicate | rankByAreaInNorway |
P1170
|
FINISHED |
| Object | second-largest island (after Hinnøya) |
—
|
LITERAL 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: second-largest island (after Hinnøya) | Statement: [Senja, rankByAreaInNorway, second-largest island (after Hinnøya)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInNorway Context triple: [Senja, rankByAreaInNorway, second-largest island (after Hinnøya)]
-
A.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
B.
rankByAreaInCanadaIslands
Indicates the numerical position of an island in Canada when all Canadian islands are ordered by their land area from largest to smallest.
-
C.
rankInRussiaByArea
Indicates the position of an entity in an ordered list of entities in Russia sorted by their area size.
-
D.
areaRank
chosen
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
E.
cityRankInSwedenBySize
Indicates the relative position of a city in Sweden when cities are ordered by their size (typically population or area).
- F. None of above.
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_69ad8b1089588190b74d9e2505e45762 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98b2752481908ec6f9a9cc24c0a7 |
completed | March 8, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69ad960a70ac8190816b5ae3e8631031 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:56 p.m.