Triple
T435997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russia |
E10011
|
entity |
| Predicate | largestCountryBy |
P3408
|
FINISHED |
| Object | land 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: land area | Statement: [Russia, largestCountryBy, land area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestCountryBy Context triple: [Russia, largestCountryBy, land area]
-
A.
hasLargestCountryByArea
chosen
Indicates that, among a set of compared entities, the subject is associated with the country that has the greatest land area.
-
B.
hasLargestCountryByPopulation
Indicates that, among a set of compared entities, the subject is associated with the country that has the highest population.
-
C.
isLargestContiguousLandmass
Indicates that one landmass is the largest single, unbroken continuous area of land compared to all other landmasses in the relevant context.
-
D.
hasLargestContinuousLandAreaOn
Indicates that an entity possesses the greatest uninterrupted expanse of land on a specified geographic region or surface compared to all other entities.
-
E.
hasLargestPopulationOn
Indicates that the subject entity has the greatest population among a specified set of entities within the context or scope defined by the object.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef0c97188190b62104cb639d4b60 |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddb98e081909efcf9f0a955a908 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.