Triple
T715091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago City Hall |
E14294
|
entity |
| Predicate | greenRoofPurpose |
P13382
|
FINISHED |
| Object | urban heat island mitigation |
—
|
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: urban heat island mitigation | Statement: [Chicago City Hall, greenRoofPurpose, urban heat island mitigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenRoofPurpose Context triple: [Chicago City Hall, greenRoofPurpose, urban heat island mitigation]
-
A.
greenType
Indicates that one entity is classified as a specific type or category within the broader concept of "green" (e.g., a subtype, variant, or classification related to greenness).
-
B.
roofFunction
chosen
Indicates the functional role or purpose that a roof serves in relation to the structure it covers.
-
C.
roofFeature
Indicates that one entity is a feature, element, or characteristic that is part of or associated with a roof.
-
D.
evergreen
Indicates that something remains persistently relevant, active, or unchanged over time, without becoming outdated or obsolete.
-
E.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
- 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_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. |
Created at: March 1, 2026, 7:37 p.m.