Triple
T27384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pacific Ocean |
E547
|
entity |
| Predicate | coversFractionOfEarthSurface |
P1884
|
FINISHED |
| Object | about one-third |
—
|
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: about one-third | Statement: [Pacific Ocean, coversFractionOfEarthSurface, about one-third]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversFractionOfEarthSurface Context triple: [Pacific Ocean, coversFractionOfEarthSurface, about one-third]
-
A.
areaWater
Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
-
B.
hasPeakUsageInHemisphere
Indicates that the time period of highest usage or activity for something occurs within a specified hemisphere (e.g., Northern or Southern).
-
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.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
E.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a247798a348190bb943d38300ae3ef |
completed | Feb. 28, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69a24658749881909117b007ec3d8633 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a24778b73c81908e9f2eb8cdbcef73 |
completed | Feb. 28, 2026, 1:40 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.