Triple
T4196123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Winnipeg |
E89156
|
entity |
| Predicate | rankBySurfaceAreaInWorld |
P17270
|
FINISHED |
| Object | among the largest freshwater lakes in the world |
—
|
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: among the largest freshwater lakes in the world | Statement: [Lake Winnipeg, rankBySurfaceAreaInWorld, among the largest freshwater lakes in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankBySurfaceAreaInWorld Context triple: [Lake Winnipeg, rankBySurfaceAreaInWorld, among the largest freshwater lakes in the world]
-
A.
rankInWorldByArea
chosen
Indicates the position of an entity in a global ordering based on its total area size.
-
B.
rankingInCountryBySize
Indicates the position of an entity in an ordered list of entities within a specific country, based on their relative size.
-
C.
continentRankByArea
Indicates the relative position of a continent in an ordered list based on its total land area.
-
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.
continentRankByPopulation
Indicates the relative position of a continent in an ordered list based on its population 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_69aed9569a4481908b6c1fcec2a11e21 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af035e87148190a0f0bf48b813ffaa |
completed | March 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69af01959c4881909eb1adcb3bdadbe6 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:46 p.m.