Triple
T15048771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mall of Georgia |
E379298
|
entity |
| Predicate | hasRetailFloorArea |
P25135
|
FINISHED |
| Object | about 1.8 million square feet |
—
|
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 1.8 million square feet | Statement: [Mall of Georgia, hasRetailFloorArea, about 1.8 million square feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailFloorArea Context triple: [Mall of Georgia, hasRetailFloorArea, about 1.8 million square feet]
-
A.
hasFloorArea
Indicates that an entity possesses a specified amount of floor space as a measurable area.
-
B.
hasRetailArea
chosen
Indicates that an entity possesses or includes a designated space used for retail or commercial sales activities.
-
C.
hasCasinoFloorArea
Indicates the total floor area occupied by a casino within a given property or facility.
-
D.
hasFloor
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a structure.
-
E.
grossLeasableArea
Indicates the total floor area within a property that is available to be leased to tenants, excluding common or non-leasable spaces.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda8f71988190b4fe7f7de4ccb798 |
completed | April 15, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69de9a69d7848190b2b4662dd30f20e9 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 3 a.m.