Triple
T715094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago City Hall |
E14294
|
entity |
| Predicate | greenRoofContains |
P3576
|
FINISHED |
| Object | native prairie plants |
—
|
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: native prairie plants | Statement: [Chicago City Hall, greenRoofContains, native prairie plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenRoofContains Context triple: [Chicago City Hall, greenRoofContains, native prairie plants]
-
A.
growsIn
Indicates that one entity develops, thrives, or increases in size or number within a specified environment, medium, or location.
-
B.
roofFeature
chosen
Indicates that one entity is a feature, element, or characteristic that is part of or associated with a roof.
-
C.
cultivatedIndoors
Indicates that an entity is grown or maintained within an indoor environment rather than outdoors.
-
D.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
E.
hasCanopy
Indicates that one entity possesses or is characterized by a canopy associated with it.
- 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.