Triple
T36119099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Røssvatnet |
E1044691
|
entity |
| Predicate | areaRankingInNorway |
P55798
|
FINISHED |
| Object | second largest lake by area |
—
|
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 lake by area | Statement: [Røssvatnet, areaRankingInNorway, second largest lake by area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaRankingInNorway Context triple: [Røssvatnet, areaRankingInNorway, second largest lake by area]
-
A.
rankInNorwayByArea
chosen
Indicates the position of an entity in an ordered list of areas within Norway, based on its size relative to others.
-
B.
rankInFinlandByArea
Indicates the position of an entity in an ordered list based on its area size within Finland.
-
C.
territoryRetainedByNorway
Indicates that a specified territory remains under the control, sovereignty, or possession of Norway.
-
D.
rankInGermanyByArea
Indicates the position of an entity in an ordered list based on its area size within Germany.
-
E.
rankInRussiaByArea
Indicates the position of an entity in an ordered list of entities in Russia sorted by their area size.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.