Triple
T190380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Pyramid of Giza |
E3706
|
entity |
| Predicate | baseArea |
P157
|
FINISHED |
| Object | about 5.3 hectares |
—
|
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 5.3 hectares | Statement: [Great Pyramid of Giza, baseArea, about 5.3 hectares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: baseArea Context triple: [Great Pyramid of Giza, baseArea, about 5.3 hectares]
-
A.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
B.
landArea
chosen
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
C.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
D.
ground
Indicates that one entity is in contact with or supported by the ground or a ground-like surface.
-
E.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594c385481909e1e088e45c460a4 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25673ce3c8190b1a3df5b814a0595 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.