Triple
T7259883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose City Park |
E159620
|
entity |
| Predicate | treeCanopy |
P8429
|
FINISHED |
| Object | significant |
—
|
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: significant | Statement: [Rose City Park, treeCanopy, significant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treeCanopy Context triple: [Rose City Park, treeCanopy, significant]
-
A.
hasCanopyDensity
Indicates the degree to which a canopy (such as a tree or forest cover) occupies or obscures the area beneath it.
-
B.
hasTreeCanopyProtection
Indicates that an entity is subject to rules or measures that preserve, limit removal of, or otherwise protect the tree canopy associated with it.
-
C.
treeVigor
Indicates the overall health, strength, and growth potential of a tree based on its physiological condition and environmental factors.
-
D.
treeUse
Indicates the way in which a tree is utilized or purposed within a given context.
-
E.
hasCanopy
chosen
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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb088dac8190b353f6ea3d686025 |
completed | March 27, 2026, 8:39 p.m. |
| PD | Predicate disambiguation | batch_69c6e76876608190ac4652bc7153302e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:57 p.m.