Triple
T16991362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tilio-Acerion ravine forests |
E412200
|
entity |
| Predicate | typicalHerbLayerSpecies |
P69428
|
FINISHED |
| Object | Mercurialis perennis |
—
|
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: Mercurialis perennis | Statement: [Tilio-Acerion ravine forests, typicalHerbLayerSpecies, Mercurialis perennis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalHerbLayerSpecies Context triple: [Tilio-Acerion ravine forests, typicalHerbLayerSpecies, Mercurialis perennis]
-
A.
commonUnderstorySpecies
chosen
Indicates that the related entities are species that commonly occur together in the understory layer of the same habitat or ecosystem.
-
B.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
C.
speciesComposition
Indicates the makeup and relative proportions of different species present within a defined group, sample, or environment.
-
D.
notableTreeSpecies
Indicates that the subject place or area is known for, or characterized by, the specified tree species.
-
E.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d280e3348190a27bd5dc7cf87c0e |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.