Triple
T8446812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cathedral Grove |
E199695
|
entity |
| Predicate | hasUnderstory |
P83412
|
FINISHED |
| Object | lush fern and moss understory |
—
|
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: lush fern and moss understory | Statement: [Cathedral Grove, hasUnderstory, lush fern and moss understory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnderstory Context triple: [Cathedral Grove, hasUnderstory, lush fern and moss understory]
-
A.
hasCanopy
Indicates that one entity possesses or is characterized by a canopy associated with it.
-
B.
commonUnderstorySpecies
Indicates that the related entities are species that commonly occur together in the understory layer of the same habitat or ecosystem.
-
C.
hasUnderpass
Indicates that one location or structure includes or is connected by an underpass beneath another feature or pathway.
-
D.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
-
E.
hasMeadow
Indicates that one entity possesses, contains, or includes a meadow as part of its area or composition.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe3152a3c819092efdeab718def7a |
completed | March 31, 2026, 3:07 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe30c2d088190b4cb89adb4e88273 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:09 p.m.