Triple
T70058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Africa |
E1402
|
entity |
| Predicate | hasTotalArea |
P175
|
FINISHED |
| Object | about 30.37 million square kilometers |
—
|
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 30.37 million square kilometers | Statement: [Africa, hasTotalArea, about 30.37 million square kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTotalArea Context triple: [Africa, hasTotalArea, about 30.37 million square kilometers]
-
A.
area
chosen
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
B.
hasProtectedArea
Indicates that an entity possesses, includes, or is associated with a designated protected area for conservation or restricted use.
-
C.
hasProtectedAreaStatus
Indicates that an area is officially designated and managed as a protected area under relevant conservation or legal frameworks.
-
D.
hasAreaCode
Indicates that a specified telephone area code is assigned to or associated with a particular geographic region, location, or phone service entity.
-
E.
hasWaitingArea
Indicates that an entity provides or includes a designated space where people can wait before receiving a service or proceeding to another area.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eaa0df88190add55579b2b9fd02 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.