Triple
T715089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago City Hall |
E14294
|
entity |
| Predicate | greenRoofArea |
P18455
|
FINISHED |
| Object | approximately 20,000 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: approximately 20,000 square feet | Statement: [Chicago City Hall, greenRoofArea, approximately 20,000 square feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenRoofArea Context triple: [Chicago City Hall, greenRoofArea, approximately 20,000 square feet]
-
A.
roofHeight
Indicates the vertical distance or elevation of a roof relative to a reference level or structure.
-
B.
roofFeature
Indicates that one entity is a feature, element, or characteristic that is part of or associated with a roof.
-
C.
grossLeasableArea
Indicates the total floor area within a property that is available to be leased to tenants, excluding common or non-leasable spaces.
-
D.
roofFunction
Indicates the functional role or purpose that a roof serves in relation to the structure it covers.
-
E.
areaApprox
Indicates that one entity’s area is approximately equal to the area of another entity.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a574b4d881908b6d0be386081efd |
completed | March 1, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f38898819089d79bad4f4ff2d2 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.