Triple
T16806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North America |
E335
|
entity |
| Predicate | continentRankByArea |
P1020
|
FINISHED |
| Object | third-largest continent |
—
|
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 continent | Statement: [North America, continentRankByArea, third-largest continent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: continentRankByArea Context triple: [North America, continentRankByArea, third-largest continent]
-
A.
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).
-
B.
areaWater
Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
-
C.
continent
Indicates that one entity is a continent on which the other entity is geographically located or to which it belongs.
-
D.
basinCountry
Indicates the country or countries within whose territory a river basin or drainage area is primarily located or through which it significantly extends.
-
E.
rankByPopulationInUS
Indicates the relative ordering of entities based on the size of their populations within the United States.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a241ea1ea081908e8a81ca97531ba5 |
completed | Feb. 28, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69a23fec1fe8819080da6f2c745dc8fd |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a241e933288190b02ef5369f7b8834 |
completed | Feb. 28, 2026, 1:16 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.