Triple
T4365730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Femunden |
E98766
|
entity |
| Predicate | rankInNorwayByArea |
P55798
|
FINISHED |
| Object | third-largest lake |
—
|
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: third-largest lake | Statement: [Femunden, rankInNorwayByArea, third-largest lake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInNorwayByArea Context triple: [Femunden, rankInNorwayByArea, third-largest lake]
-
A.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
B.
rankInRussiaByArea
Indicates the position of an entity in an ordered list of entities in Russia sorted by their area size.
-
C.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
D.
rankInBritishIslesByArea
Indicates the position of an entity in an ordered list of areas specifically within the British Isles, based on its size relative to others.
-
E.
areaOfMemberStatesApprox
Indicates the approximate total geographic area collectively covered by the member states of a given organization or grouping.
- F. None of above. chosen
Provenance (4 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_69b3454c772081908e20173e379e8ebe |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35200263081909bb326a4d7a8db99 |
completed | March 12, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69b34f53e3cc8190bf5d4dbe2413bf65 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:17 p.m.