Triple
T12983940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Vättern |
E321719
|
entity |
| Predicate | rankingByAreaInSweden |
P1170
|
FINISHED |
| Object | second-largest lake in Sweden |
—
|
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 in Sweden | Statement: [Lake Vättern, rankingByAreaInSweden, second-largest lake in Sweden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingByAreaInSweden Context triple: [Lake Vättern, rankingByAreaInSweden, second-largest lake in Sweden]
-
A.
cityRankInSwedenBySize
Indicates the relative position of a city in Sweden when cities are ordered by their size (typically population or area).
-
B.
rankInNorwayByArea
Indicates the position of an entity in an ordered list of areas within Norway, based on its size relative to others.
-
C.
chartPositionSweden
Indicates the position or ranking something holds on a music or sales chart specifically in Sweden.
-
D.
rankInGermanyByArea
Indicates the position of an entity in an ordered list based on its area size within Germany.
-
E.
areaRank
chosen
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:39 p.m.