Triple
T34532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earth |
E687
|
entity |
| Predicate | hasSurfaceArea |
P175
|
FINISHED |
| Object | about 510 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 510 million square kilometers | Statement: [Earth, hasSurfaceArea, about 510 million square kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurfaceArea Context triple: [Earth, hasSurfaceArea, about 510 million square kilometers]
-
A.
surfaceType
Indicates the kind or classification of surface associated with an entity or interaction.
-
B.
area
chosen
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
C.
hasProtectedArea
Indicates that an entity possesses, includes, or is associated with a designated protected area for conservation or restricted use.
-
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.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490019948190a89bb0910c60d462 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a24872e4e481908567850168d65015 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.